1266 Vertex Jobs - Page 9

Summary Position Summary AI & Data In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment. The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. The offering portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets. AI & Data will work with our clients to: Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms. Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions. Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements. Job Title: Senior Generative AI Developer/Team Lead Job Summary: We are looking for a Generative AI Team Lead with hands-on experience to design, develop and deploy AI and Generative AI models that generate high quality content, such as text, images, chatbots, etc. The Ideal candidate will have expertise in deep learning, natural language processing, and computer vision. Key Responsibilities: Lead and deliver large-scale AI/Gen AI projects across multiple industries and domains. Liaison with on-site and client teams to understand various business problem statements and project requirements. Lead a team of Data Engineers, ML/AI Engineers, Prompt engineers, and other Data & AI professionals to deliver projects from inception to implementation. Brainstorm, build & improve AI/Gen AI models developed by the team & identify scope for model improvements & best practices. Assist and participate in pre-sales, client pursuits and proposals. Drive a human-led culture of Inclusion & Diversity by caring deeply for all team members. Qualifications: 6-10 years of relevant experience in Generative AI, Deep Learning, or NLP Bachelor’s or master’s degree in a quantitative field. Led a 3–5-member team on multiple end to end AI/GenAI projects Excellent communication and client/stakeholder management skills Must have strong hands-on experience with programming languages like Python, Cuda and SQL, and frameworks such as TensorFlow, PyTorch and Keras Hands-on experience with top LLM models like OpenAI GPT-3.5/4, Google Gemini, AWS Bedrock, LLaMA 3.0, and Mistral, along with RAG and Agentic workflows Well versed with GANs and Transformer architecture, knows about Diffusion models, up to date with new research/progress in the field of Gen AI Should follow research papers, comprehend and innovate/present the best approaches/solutions related to Generative AI components. Knowledge of hyperscaler offerings (NVIDIA, AWS, Azure, GCP, Oracle) and Gen AI tools (Copilot, Vertex AI). Knowledge of Vector DB, Neo4J/relevant Graph DBs Familiar with Docker containerization, GIT, etc. AI/Cloud certification from a premier institute is preferred. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303629

Summary Position Summary AI & Data In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment. The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. The offering portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets. AI & Data will work with our clients to: Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms. Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions. Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements. Job Title: Senior Generative AI Developer/Team Lead Job Summary: We are looking for a Generative AI Team Lead with hands-on experience to design, develop and deploy AI and Generative AI models that generate high quality content, such as text, images, chatbots, etc. The Ideal candidate will have expertise in deep learning, natural language processing, and computer vision. Key Responsibilities: Lead and deliver large-scale AI/Gen AI projects across multiple industries and domains. Liaison with on-site and client teams to understand various business problem statements and project requirements. Lead a team of Data Engineers, ML/AI Engineers, Prompt engineers, and other Data & AI professionals to deliver projects from inception to implementation. Brainstorm, build & improve AI/Gen AI models developed by the team & identify scope for model improvements & best practices. Assist and participate in pre-sales, client pursuits and proposals. Drive a human-led culture of Inclusion & Diversity by caring deeply for all team members. Qualifications: 6-10 years of relevant experience in Generative AI, Deep Learning, or NLP Bachelor’s or master’s degree in a quantitative field. Led a 3–5-member team on multiple end to end AI/GenAI projects Excellent communication and client/stakeholder management skills Must have strong hands-on experience with programming languages like Python, Cuda and SQL, and frameworks such as TensorFlow, PyTorch and Keras Hands-on experience with top LLM models like OpenAI GPT-3.5/4, Google Gemini, AWS Bedrock, LLaMA 3.0, and Mistral, along with RAG and Agentic workflows Well versed with GANs and Transformer architecture, knows about Diffusion models, up to date with new research/progress in the field of Gen AI Should follow research papers, comprehend and innovate/present the best approaches/solutions related to Generative AI components. Knowledge of hyperscaler offerings (NVIDIA, AWS, Azure, GCP, Oracle) and Gen AI tools (Copilot, Vertex AI). Knowledge of Vector DB, Neo4J/relevant Graph DBs Familiar with Docker containerization, GIT, etc. AI/Cloud certification from a premier institute is preferred. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303629

Summary Position Summary AI & Data In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment. The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. The offering portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets. AI & Data will work with our clients to: Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms. Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions. Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements. Job Title: Senior Generative AI Developer/Team Lead Job Summary: We are looking for a Generative AI Team Lead with hands-on experience to design, develop and deploy AI and Generative AI models that generate high quality content, such as text, images, chatbots, etc. The Ideal candidate will have expertise in deep learning, natural language processing, and computer vision. Key Responsibilities: Lead and deliver large-scale AI/Gen AI projects across multiple industries and domains. Liaison with on-site and client teams to understand various business problem statements and project requirements. Lead a team of Data Engineers, ML/AI Engineers, Prompt engineers, and other Data & AI professionals to deliver projects from inception to implementation. Brainstorm, build & improve AI/Gen AI models developed by the team & identify scope for model improvements & best practices. Assist and participate in pre-sales, client pursuits and proposals. Drive a human-led culture of Inclusion & Diversity by caring deeply for all team members. Qualifications: 6-10 years of relevant experience in Generative AI, Deep Learning, or NLP Bachelor’s or master’s degree in a quantitative field. Led a 3–5-member team on multiple end to end AI/GenAI projects Excellent communication and client/stakeholder management skills Must have strong hands-on experience with programming languages like Python, Cuda and SQL, and frameworks such as TensorFlow, PyTorch and Keras Hands-on experience with top LLM models like OpenAI GPT-3.5/4, Google Gemini, AWS Bedrock, LLaMA 3.0, and Mistral, along with RAG and Agentic workflows Well versed with GANs and Transformer architecture, knows about Diffusion models, up to date with new research/progress in the field of Gen AI Should follow research papers, comprehend and innovate/present the best approaches/solutions related to Generative AI components. Knowledge of hyperscaler offerings (NVIDIA, AWS, Azure, GCP, Oracle) and Gen AI tools (Copilot, Vertex AI). Knowledge of Vector DB, Neo4J/relevant Graph DBs Familiar with Docker containerization, GIT, etc. AI/Cloud certification from a premier institute is preferred. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303629

Summary Position Summary AI & Data In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment. The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. The offering portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets. AI & Data will work with our clients to: Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms. Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions. Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements. Job Title: Senior Generative AI Developer/Team Lead Job Summary: We are looking for a Generative AI Team Lead with hands-on experience to design, develop and deploy AI and Generative AI models that generate high quality content, such as text, images, chatbots, etc. The Ideal candidate will have expertise in deep learning, natural language processing, and computer vision. Key Responsibilities: Lead and deliver large-scale AI/Gen AI projects across multiple industries and domains. Liaison with on-site and client teams to understand various business problem statements and project requirements. Lead a team of Data Engineers, ML/AI Engineers, Prompt engineers, and other Data & AI professionals to deliver projects from inception to implementation. Brainstorm, build & improve AI/Gen AI models developed by the team & identify scope for model improvements & best practices. Assist and participate in pre-sales, client pursuits and proposals. Drive a human-led culture of Inclusion & Diversity by caring deeply for all team members. Qualifications: 6-10 years of relevant experience in Generative AI, Deep Learning, or NLP Bachelor’s or master’s degree in a quantitative field. Led a 3–5-member team on multiple end to end AI/GenAI projects Excellent communication and client/stakeholder management skills Must have strong hands-on experience with programming languages like Python, Cuda and SQL, and frameworks such as TensorFlow, PyTorch and Keras Hands-on experience with top LLM models like OpenAI GPT-3.5/4, Google Gemini, AWS Bedrock, LLaMA 3.0, and Mistral, along with RAG and Agentic workflows Well versed with GANs and Transformer architecture, knows about Diffusion models, up to date with new research/progress in the field of Gen AI Should follow research papers, comprehend and innovate/present the best approaches/solutions related to Generative AI components. Knowledge of hyperscaler offerings (NVIDIA, AWS, Azure, GCP, Oracle) and Gen AI tools (Copilot, Vertex AI). Knowledge of Vector DB, Neo4J/relevant Graph DBs Familiar with Docker containerization, GIT, etc. AI/Cloud certification from a premier institute is preferred. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303629

Summary Position Summary AI & Data In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment. The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. The offering portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets. AI & Data will work with our clients to: Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms. Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions. Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements. Job Title: Senior Generative AI Developer/Team Lead Job Summary: We are looking for a Generative AI Team Lead with hands-on experience to design, develop and deploy AI and Generative AI models that generate high quality content, such as text, images, chatbots, etc. The Ideal candidate will have expertise in deep learning, natural language processing, and computer vision. Key Responsibilities: Lead and deliver large-scale AI/Gen AI projects across multiple industries and domains. Liaison with on-site and client teams to understand various business problem statements and project requirements. Lead a team of Data Engineers, ML/AI Engineers, Prompt engineers, and other Data & AI professionals to deliver projects from inception to implementation. Brainstorm, build & improve AI/Gen AI models developed by the team & identify scope for model improvements & best practices. Assist and participate in pre-sales, client pursuits and proposals. Drive a human-led culture of Inclusion & Diversity by caring deeply for all team members. Qualifications: 6-10 years of relevant experience in Generative AI, Deep Learning, or NLP Bachelor’s or master’s degree in a quantitative field. Led a 3–5-member team on multiple end to end AI/GenAI projects Excellent communication and client/stakeholder management skills Must have strong hands-on experience with programming languages like Python, Cuda and SQL, and frameworks such as TensorFlow, PyTorch and Keras Hands-on experience with top LLM models like OpenAI GPT-3.5/4, Google Gemini, AWS Bedrock, LLaMA 3.0, and Mistral, along with RAG and Agentic workflows Well versed with GANs and Transformer architecture, knows about Diffusion models, up to date with new research/progress in the field of Gen AI Should follow research papers, comprehend and innovate/present the best approaches/solutions related to Generative AI components. Knowledge of hyperscaler offerings (NVIDIA, AWS, Azure, GCP, Oracle) and Gen AI tools (Copilot, Vertex AI). Knowledge of Vector DB, Neo4J/relevant Graph DBs Familiar with Docker containerization, GIT, etc. AI/Cloud certification from a premier institute is preferred. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303629

If you are looking for a career at a dynamic company with a people-first mindset and a deep culture of growth and autonomy, ACV is the right place for you! Competitive compensation packages and learning and development opportunities, ACV has what you need to advance to the next level in your career. We will continue to raise the bar every day by investing in our people and technology to help our customers succeed. We hire people who share our passion, bring innovative ideas to the table, and enjoy a collaborative atmosphere. Who We Are ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV), has applied innovation and user-designed, data driven applications and solutions. We are building the most trusted and efficient digital marketplace with data solutions for sourcing, selling and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of the industry and we want you to join us on our journey. Our network of brands include ACV Auctions, ACV Transportation, ClearCar, MAX Digital and ACV Capital within its Marketplace Products, as well as, True360 and Data Services. ACV Auctions in Chennai, India are looking for talented individuals to join our team. As we expand our platform, we're offering a wide range of exciting opportunities across various roles in corporate, operations, and product and technology. Our global product and technology organization spans product management, engineering, data science, machine learning, DevOps and program leadership. What unites us is a deep sense of customer centricity, calm persistence in solving hard problems, and a shared passion for innovation. If you're looking to grow, lead, and contribute to something larger than yourself, we'd love to have you on this journey. Let's build something extraordinary together. Join us in shaping the future of automotive! At ACV we focus on the Health, Physical, Financial, Social and Emotional Wellness of our Teammates and to support this we offer industry leading benefits and wellness programs. What You Will Do ACV’s Machine Learning (ML) team is looking to grow its MLOps team. Multiple ACV operations and product teams rely on the ML team’s solutions. Current deployments drive opportunities in the marketplace, in operations, and sales, to name a few. As ACV has experienced hyper growth over the past few years, the volume, variety, and velocity of these deployments has grown considerably. Thus, the training, deployment, and monitoring needs of the ML team has grown as we’ve gained traction. MLOps is a critical function to help ourselves continue to deliver value to our partners and our customers. Successful candidates will demonstrate excellent skill and maturity, be self-motivated as well as team-oriented, and have the ability to support the development and implementation of end-to-end ML-enabled software solutions to meet the needs of their stakeholders. Those who will excel in this role will be those who listen with an ear to the overarching goal, not just the immediate concern that started the query. They will be able to show their recommendations are contextually grounded in an understanding of the practical problem, the data, and theory as well as what product and software solutions are feasible and desirable. The Core Responsibilities Of This Role Are Working with fellow machine learning engineers to build, automate, deploy, and monitor ML applications. Developing data pipelines that feed ML models. Deploy new ML models into production. Building REST APIs to serve ML models predictions. Monitoring performance of models in production. Required Qualifications Graduate education in a computationally intensive domain or equivalent work experience. 5+ years of prior relevant work or lab experience in ML projects/research Advanced proficiency with Python, SQL etc. Experience with building and deploying REST APIs (FastAPI, Flask) Experience with distributed caching technologies (Redis) Experience with real-time data streaming and processing (Kafka) Experience with cloud services (AWS / GCP) and kubernetes, docker, CI/CD. Preferred Qualifications Experience with MLOps-specific tooling like Vertex AI, Ray, Feast, Kubeflow, or MLFlow, etc. are a plus. Experience with building data pipelines Experience with training ML models Our Values Trust & Transparency | People First | Positive Experiences | Calm Persistence | Never Settling At ACV, we are committed to an inclusive culture in which every individual is welcomed and empowered to celebrate their true selves. We achieve this by fostering a work environment of acceptance and understanding that is free from discrimination. ACV is committed to being an equal opportunity employer regardless of sex, race, creed, color, religion, marital status, national origin, age, pregnancy, sexual orientation, gender, gender identity, gender expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires reasonable accommodation, please let us know. Data Processing Consent When you apply to a job on this site, the personal data contained in your application will be collected by ACV Auctions Inc. and/or one of its subsidiaries ("ACV Auctions"). By clicking "apply", you hereby provide your consent to ACV Auctions and/or its authorized agents to collect and process your personal data for purpose of your recruitment at ACV Auctions and processing your job application. ACV Auctions may use services provided by a third party service provider to help manage its recruitment and hiring process. For more information about how your personal data will be processed by ACV Auctions and any rights you may have, please review ACV Auctions' candidate privacy notice here. If you have any questions about our privacy practices, please contact datasubjectrights@acvauctions.com.

Job Title: Data Scientist – Agentic AI | Cloud AI | AR/VR Location: Gurgaon- 5 days WFO Experience: 3 to 5 Years Employment Type: Full-time ⸻ About the Role We’re looking for a hands-on Data Scientist who’s excited by the next frontier of AI — from Agentic AI systems and multi-agent collaboration to cloud-based AI services and immersive experiences in AR/VR. This is your chance to work on cutting-edge innovation across verticals such as retail, healthcare, gaming, and enterprise tech. ⸻ Key Responsibilities • Build, deploy, and optimize AI/ML models with a focus on Agentic AI and multi-agent coordination frameworks (e.g., AutoGen, LangChain, etc.) • Leverage Google Cloud AI and Azure AI Services (Vision AI, Vertex AI, Azure ML) for scalable training, inference, and deployment • Apply Computer Vision techniques for object detection, image classification, and spatial tracking in AR/VR contexts • Collaborate cross-functionally with product, engineering, and design teams to bring AI-driven AR/VR applications to life • Utilize Multi-Cloud Pipelines (MCP) for managing end-to-end workflows in a hybrid cloud setup • Continuously experiment with emerging AI techniques in the realm of generative agents, prompt engineering, and memory-based systems ⸻ Must-Have Skills • 2–5 years of hands-on experience in AI/ML model development and deployment • Strong Python skills with experience in frameworks like TensorFlow, PyTorch, or OpenCV

About Us: Soul AI is a pioneering company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in delivering high-quality human-curated data and AI-first scaled operations services. Based in San Francisco and Hyderabad, we are a fast-moving team on a mission to build AI for Good, driving innovation and societal impact. Role Overview :We are seeking a skilled AI/ML Engineer to join our client’s team (Top Tier Consulting Fir m) and operationalize our machine learning workflows. You will work closely with data scientists, engineers, and product teams to design, deploy, monitor, and maintain scalable ML pipelines in production. The ideal candidate has a strong foundation in ML systems, DevOps principles, and cloud-native technologies . Key Responsibilitie s:Collaborate with cross-functional teams to define ML problem statements and translate them into technical task s.Design and implement robust data pipelines for collecting, cleaning, and validating large dataset s.Develop, train, and evaluate machine learning models using appropriate algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch ).Package and deploy ML models as scalable services or APIs, ensuring performance, security, and reliabilit y.Monitor and maintain models in production, including retraining and performance tunin g.Implement best practices in MLOps: experiment tracking, versioning, CI/CD pipelines, and model monitorin g.Document methodologies, workflows, and technical decisions clearly for both technical and non-technical audience s.Stay up to date with industry trends and contribute to evaluating and adopting new tools or frameworks where relevan t.Required Skill s:Strong programming skills in Python and experience with ML libraries (scikit-learn, PyTorch, TensorFlow ).Solid understanding of machine learning fundamentals, including data preprocessing, feature engineering, model selection, and evaluatio n.Hands-on experience with SQL and data manipulation using tools like panda s.Experience deploying models in production environments, including serving models via REST API s.Familiarity with containerization (Docker) and orchestration (Kubernetes is a plus ).Knowledge of cloud platforms (AWS, GCP, or Azure) and experience with relevant ML tools (e.g., SageMaker, Vertex AI) is a plu s.Good understanding of software engineering best practices: version control, testing, code review s.Nice-to-Hav e:Experience with big data frameworks (e.g., Spark) for processing large dataset s.Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases ).Familiarity with MLOps workflows and tools for monitoring data/model drif t.Domain-specific expertise in NLP, Computer Vision, or Time Series Analysi s.Educational Qualification s:Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related fiel d.

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. PwC US - Acceleration Center is seeking a highly skilled MLOps/LLMOps Engineer who will play a critical role in the deployment, scaling, and maintenance of Generative AI models. This position involves close collaboration with data scientists, ML/GenAI engineers, and DevOps teams to ensure seamless integration and operation of GenAI models within production environments at PwC as well as our clients. The ideal candidate will have a strong background in MLOps practices, along with experience and interest in Generative AI technologies. Years of Experience: Candidates with 4+ years of hands on experience Core Qualifications 3+ years of hands-on experience developing and deploying AI models in production environments with 1 year of experience in developing proofs of concept and prototypes Strong background in software development, with experience in building and maintaining scalable, distributed systems Strong programming skills in languages like Python and familiarity in ML frameworks and libraries (e.g., TensorFlow, PyTorch) Knowledge of containerization and orchestration tools like Docker and Kubernetes. Familiarity with cloud platforms (AWS, GCP, Azure) and their ML/AI service offerings Experience with continuous integration and delivery tools such as Jenkins, GitLab CI/CD, or CircleCI. Experience with infrastructure as code tools like Terraform or CloudFormation. Technical Skills Must to Have: Proficiency with MLOps tools such as MLflow, Kubeflow, Airflow, or similar for managing machine learning workflows and lifecycle. Practical understanding of generative AI frameworks (e.g., HuggingFace Transformers, OpenAI GPT, DALL-E) Expertise in containerization technologies like Docker and orchestration tools such as Kubernetes for scalable model deployment. Expertise in MLOps and LLMOps practices, including CI/CD for ML models Strong knowledge of one or more cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google Vertex AI) Nice To Have Experience with advanced GenAI applications such as natural language generation, image synthesis, and creative AI. Familiarity with experiment tracking and model registry tools. Knowledge of high-performance computing and parallel processing techniques. Contributions to open-source MLOps or GenAI projects. Key Responsibilities Develop and implement MLOps strategies tailored for Generative AI models to ensure robustness, scalability, and reliability. Design and manage CI/CD pipelines specialized for ML workflows, including the deployment of generative models such as GANs, VAEs, and Transformers. Monitor and optimize the performance of AI models in production, employing tools and techniques for continuous validation, retraining, and A/B testing. Collaborate with data scientists and ML researchers to understand model requirements and translate them into scalable operational frameworks. Implement best practices for version control, containerization, infrastructure automation, and orchestration using industry-standard tools (e.g., Docker, Kubernetes). Ensure compliance with data privacy regulations and company policies during model deployment and operation. Troubleshoot and resolve issues related to ML model serving, data anomalies, and infrastructure performance. Stay up-to-date with the latest developments in MLOps and Generative AI, bringing innovative solutions to enhance our AI capabilities. Project Delivery Design and implement scalable and reliable deployment pipelines for ML/GenAI models to move them from development to production environments Ensure models are deployed with appropriate versioning and rollback mechanisms to maintain stability and ease of updates. Oversee the cloud infrastructure setup, automated data ingestion pipelines, ensuring they meets the needs of GenAI workloads in terms of computation power, storage, and network requirements. Create detailed documentation for deployment pipelines, monitoring setups, and operational procedures to ensure transparency and ease of maintenance. Actively participate in retrospectives to identify areas for improvement in the deployment process. Client Engagement Collaborate with clients to understand their business needs, goals, and specific requirements for Generative AI solutions. Collaborate with solution architects to design ML/LLMOps that meet client needs Present technical approaches and results to both technical and non-technical stakeholders Conduct training sessions and workshops for client teams to help them understand, operate, and maintain the deployed AI models. Create comprehensive documentation and user guides to assist clients in managing and leveraging the Generative AI solutions effectively. Innovation And Knowledge Sharing Stay updated with the latest trends, research, and advancements in MLOps/LLMOps and Generative AI, and apply this knowledge to improve existing systems and processes. Develop internal tools and frameworks to accelerate ML/GenAI model development and deployment Mentor junior team members on MLOps/LLMOps best practices Contribute to technical blog posts and whitepapers on MLOps/LLMOps Professional And Educational Background Any graduate /BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Master’s Degree /MBA

Line of Service Advisory Industry/Sector Not Applicable Specialism SAP Management Level Senior Manager Job Description & Summary At PwC, our people in business application consulting specialise in consulting services for a variety of business applications, helping clients optimise operational efficiency. These individuals analyse client needs, implement software solutions, and provide training and support for seamless integration and utilisation of business applications, enabling clients to achieve their strategic objectives. As a SAP consulting generalist at PwC, you will focus on providing consulting services across various SAP applications to clients, analysing their needs, implementing software solutions, and offering training and support for effective utilisation of SAP applications. Your versatile knowledge will allow you to assist clients in optimising operational efficiency and achieving their strategic objectives. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations Job Description & Summary: A career within…. Responsibilities: AI Architecture & Development · Design and implement generative AI models (e.g., Transformers, GANs, VAEs, Diffusion Models). · Architect Retrieval-Augmented Generation (RAG) systems and multi-agent frameworks. · Fine-tune pre-trained models for domain-specific tasks (e.g., NLP, vision, genomics). · Ensure model scalability, performance, and interpretability. System Integration & Deployment · Integrate AI models into full-stack applications using modern frameworks (React, Node.js, Django). · Deploy models using cloud platforms (AWS SageMaker, Azure ML, GCP Vertex AI). · Implement CI/CD pipelines and containerization (Docker, Kubernetes). Collaboration & Leadership · Work with data scientists, engineers, and domain experts to translate business/scientific needs into AI solutions. · Lead architectural decisions across model lifecycle: training, deployment, monitoring, and versioning. · Provide technical mentorship and guidance to junior team members. Compliance & Documentation · Ensure compliance with data privacy standards (HIPAA, GDPR). · Maintain comprehensive documentation for models, systems, and workflows. - Required Qualifications: · Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field. · 5+ years in AI/ML development; 3+ years in architecture or technical leadership roles. · Proficiency in Python, JavaScript, and frameworks like TensorFlow, PyTorch. · Experience with cloud platforms (AWS, Azure, GCP) and DevOps tools. · Strong understanding of NLP, computer vision, or life sciences applications. - Preferred Qualifications: · Experience in domains like marketing, capital markets, or life sciences (e.g., drug discovery, genomics). · Familiarity with Salesforce Einstein and other enterprise AI tools. · Knowledge of regulatory standards (FDA, EMA) and ethical AI practices. · Experience with multimodal data (text, image, genomic, clinical). Mandatory skill sets: Gen AI Architect Preferred skill sets: Gen AI Years of experience required: 10+yrs Education qualification: Btech MBA MCA MTECH Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master of Business Administration, Chartered Accountant Diploma, Bachelor of Engineering, Master of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills SAP Gen AI Hub Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Application Software, Business Model Development, Business Process Modeling, Business Systems, Coaching and Feedback, Communication, Creativity, Developing Training Materials, Embracing Change, Emerging Technologies, Emotional Regulation, Empathy, Enterprise Integration, Enterprise Software, Implementation Research, Implementation Support, Implementing Technology, Inclusion, Influence, Innovative Design, Intellectual Curiosity {+ 26 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date

We are looking for a Principal Technical Consultant – Data Engineering & AI who can lead modern data and AI initiatives end-to-end — from enterprise data strategy to scalable AI/ML solutions and emerging Agentic AI systems. This role demands deep expertise in cloud-native data architectures, advanced machine learning, and AI solution delivery, while also staying at the frontier of technologies like LLMs, RAG pipelines, and AI agents. You’ll work with C-level clients to translate AI opportunities into engineered outcomes. Roles and Responsibilities AI Solution Architecture & Delivery: Design and implement production-grade AI/ML systems, including predictive modeling, NLP, computer vision, and time-series forecasting. Architect and operationalize end-to-end ML pipelines using MLflow, SageMaker, Vertex AI, or Azure ML — covering feature engineering, training, monitoring, and CI/CD. Deliver retrieval-augmented generation (RAG) solutions combining LLMs with structured and unstructured data for high-context enterprise use cases. Data Platform & Engineering Leadership: Build scalable data platforms with modern lakehouse patterns using: Ingestion: Kafka, Azure Event Hubs, Kinesis Storage & Processing: Delta Lake, Iceberg, Snowflake, BigQuery, Spark, dbt Workflow Orchestration: Airflow, Dagster, Prefect Infrastructure: Terraform, Kubernetes, Docker, CI/CD pipelines Implement observability and reliability features into data pipelines and ML systems. Agentic AI & Autonomous Workflows (Emerging Focus): Explore and implement LLM-powered agents using frameworks like LangChain, Semantic Kernel, AutoGen, or CrewAI. Develop prototypes of task-oriented AI agents capable of planning, tool use, and inter-agent collaboration for domains such as operations, customer service, or analytics automation. Integrate agents with enterprise tools, vector databases (e.g., Pinecone, Weaviate), and function-calling APIs to enable context-rich decision making. Governance, Security, and Responsible AI: - Establish best practices in data governance, access controls, metadata management, and auditability. Ensure compliance with security and regulatory requirements (GDPR, HIPAA, SOC2). Champion Responsible AI principles including fairness, transparency, and safety. Consulting, Leadership & Practice Growth: Lead large, cross-functional delivery teams (10–30+ FTEs) across data, ML, and platform domains. Serve as a trusted advisor to clients’ senior stakeholders (CDOs, CTOs, Heads of AI). Mentor internal teams and contribute to the development of accelerators, reusable components, and thought leadership. Key Skills 12+ years of experience across data platforms, AI/ML systems, and enterprise solutioning Cloud-native design experience on Azure, AWS, or GCP Expert in Python, SQL, Spark, ML frameworks (scikit-learn, PyTorch, TensorFlow) Deep understanding of MLOps, orchestration, and cloud AI tooling Hands-on with LLMs, vector DBs, RAG pipelines, and foundational GenAI principles Strong consulting acumen: client engagement, technical storytelling, stakeholder alignment Qualifications Master’s or PhD in Computer Science, Data Science, or AI/ML Certifications: Azure AI-102, AWS ML Specialty, GCP ML Engineer, or equivalent Exposure to agentic architectures, LLM fine-tuning, or multi-agent collaboration frameworks Experience with open-source contributions, conference talks, or whitepapers in AI/Data

About Teramind Teramind is the leading platform for user behavior analytics, serving multiple use cases from insider risk mitigation to business process optimization. With our comprehensive suite of solutions, organizations gain unprecedented visibility into user activities while enhancing security, optimizing productivity, and ensuring compliance. Trusted by Fortune 500 companies and businesses of all sizes across industries, our innovative platform helps organizations protect sensitive data, maximize workforce performance, and create safer, more efficient digital workplaces. Through real-time monitoring and advanced analytics, we enable businesses to safeguard their most sensitive information while optimizing employee productivity in both in-office and remote work environments. Our Core Values At Teramind, our values drive everything we do. We embrace innovation as a fundamental principle, constantly pushing boundaries to improve our products, streamline processes, and enhance customer experiences. We foster resourcefulness by empowering our team members with the autonomy and confidence to solve problems independently while providing collaborative support when needed. As a globally inclusive organization, we celebrate diversity and create an adaptable work culture where respect and collaboration thrive across our international teams. Above all, we are committed to excellence, delivering the highest quality in every aspect of our work and consistently exceeding expectations in service to our clients and each other. About the Role As our AI Data Engineering Lead , you will be a pivotal figure in shaping and executing our AI/ML strategy. You will spearhead the design, development, and deployment of cutting-edge AI applications, with a strong focus on building data infrastructure to power Large Language Models (LLMs), agentic frameworks, and multi-agent systems. This role demands a blend of hands-on technical expertise, strategic thinking, and leadership to build and scale our AI capabilities on the Google Cloud Platform (GCP). You'll not only architect robust systems but also champion data engineering excellence and build and lead a team of talented AI engineers. What You’ll Do Architect & Build: Design scalable, AI-first data infrastructure on GCP (Vertex AI, BigQuery, Dataflow, Pub/Sub) to power LLMs and agentic systems. Pipeline Mastery: Develop high-performance, real-time data pipelines to process user behavior and drive ML systems. End-to-End AI Systems: Lead the design, development, and deployment of AI/LLM applications using LangChain, HuggingFace, AutoGen, and more. Operationalize ML: Build MLOps pipelines with robust CI/CD, monitoring, testing, and model evaluation — especially for LLM outputs. Drive Evaluation: Create frameworks to assess safety, performance, and quality of generative AI applications. Code & Lead: Write production-grade Python, contribute to core infrastructure, and raise the bar for technical excellence. Collaborate Strategically: Work with Product, AIML leadership, and cross-functional partners to align tech execution with company vision. Help us Grow the Team: Mentor and grow a team of AI engineers as we scale — help us build not just software, but a world-class engineering culture. Requirements 5+ years of experience in Software, Data, and/or ML engineering Expert in Python, with strong knowledge of data engineering tools, GCP (Vertex AI, Dataflow, BigQuery) , and AI pipelines Hands-on with CI/CD, model monitoring, and observability in ML systems. Experience launching production-grade GenAI systems, especially involving LLMs, agentic workflows, or multi-agent coordination. Familiarity with AI/LLM frameworks (Langchain, LlamaIndex, HuggingFace) and modern prompt engineering techniques. Bonus Points For Master's or PhD in CS, AI, ML, or related fields Experience with AWS, Azure, or other cloud AI stacks Experience with Graph databases (e.g., Neo4j) and proficiency in SQL and NoSQL databases Background in big data (Spark, Flink) or open-source AI contributions Understanding of responsible AI, ethics, and data governance Benefits This is a remote job. Work from anywhere! We’ve been thriving as a fully-remote team since 2014. To us, remote work means flexibility and having truly diverse, global teams. Additionally: Collaboration with a forward-thinking team where new ideas come to life, experience is valued, and talent is incubated. Competitive salary Career growth opportunities Flexible paid time off Laptop reimbursement Ongoing training and development opportunities About our recruitment process We don’t expect a perfect fit for every requirement we’ve outlined. If you can see yourself contributing to the team, we want to hear your story. You can expect up to 3 interviews. In some scenarios, we’re able to streamline the process to have minimal rounds. Director-level roles and above should expect a more thorough process, with multiple rounds of interviews. All roles require reference and background checks Teramind is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration without regard to race, age, religion, color, marital status, national origin, gender, gender identity or expression, sexual orientation, disability, or veteran status.

AI/ML Developer Location: Remote / Hybrid / Onsite (Pune) Experience: 1–3+ years (flexible for strong candidates) Note: Only candidates with a notice period of 30 days or less will be considered. Final face-to-face interview in Pune is mandatory. Preference for candidates currently in Pune or willing to relocate . Immediate joiners preferred About the Role We are looking for a talented and innovative AI/ML Developer to join our growing technology team. In this role, you will design, develop, and deploy machine learning models that solve real-world problems and create measurable business impact. Working alongside software engineers, data scientists, and product managers, you'll contribute to building intelligent systems that power the next generation of AI solutions. Key Responsibilities Design and implement machine learning algorithms and AI models for business applications. Handle large, complex datasets: data cleaning, preprocessing, feature engineering, and EDA. Train, validate, and optimize models using TensorFlow , PyTorch , or Scikit-learn . Deploy models using Docker , Kubernetes , MLflow , or cloud platforms ( AWS , GCP , Azure ). Monitor and retrain deployed models to ensure performance and reliability. Collaborate with engineering and product teams to integrate ML models into production. Stay updated with emerging trends, tools, and best practices in AI/ML. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science , Engineering , Mathematics , or a related field. Strong proficiency in Python , with hands-on experience using: Scikit-learn , TensorFlow , PyTorch , Hugging Face Transformers Experience with Natural Language Processing (NLP) , including: NER, Text Classification, QA, RAG, and chatbot development Exposure to deep learning for image processing (e.g., YOLO, CNNs, Stable Diffusion) Solid understanding of ML fundamentals: regression, classification, clustering, unsupervised learning Experience building APIs using FastAPI or Flask Familiarity with Docker , Kubernetes , and modern deployment tools Comfortable using Git and version control best practices Experience with at least one cloud provider: AWS , GCP , or Azure Preferred Qualifications Projects in Computer Vision , NLP , or Reinforcement Learning Hands-on with cloud ML services like: AWS SageMaker , Google Vertex AI , or Azure ML Open-source contributions or published research Understanding of CI/CD for ML , model lifecycle management, and production workflows Why Join Us? Work on impactful AI/ML products solving real-world problems Collaborate with passionate engineers, researchers, and innovators Access cutting-edge tools, open-source models, and cloud infrastructure Grow continuously through hands-on projects, learning, and innovation Job Type: Full-time Pay: ₹480,000.00 - ₹600,000.00 per year Benefits: Health insurance Provident Fund Work from home Location Type: In-person Schedule: Day shift Monday to Friday Ability to commute/relocate: Hinjewadi, Pune, Maharashtra: Reliably commute or planning to relocate before starting work (Preferred) Application Question(s): What is your current CTC? What is your expected CTC ? What is your legal notice period ? What is your current location ? How many years of experience do you have ? We are hiring candidates who must be available for an on-site interview at our Pune office. Education: Bachelor's (Preferred) Experience: Python: 1 year (Preferred) AI: 1 year (Preferred) Machine learning: 1 year (Preferred) Deep learning: 1 year (Preferred) Location: Hinjewadi, Pune, Maharashtra (Preferred) Work Location: In person

Are you passionate about building AI systems that create real-world impact? We are hiring a Senior AI Engineer with 5+ years of experience to design, develop, and deploy cutting-edge AI/ML solutions. 📍 Location: [Trivandrum / Kochi / Remote – customize based on your need] 💼 Experience: 5+ years 💰 Salary: ₹15–20 LPA 🚀 Immediate Joiners Preferred 🔧 What You’ll Do Design and implement ML/DL models for real business problems Build data pipelines and perform preprocessing for large datasets Use advanced techniques like NLP, computer vision, reinforcement learning Deploy AI models using MLOps best practices Collaborate with data scientists, developers & product teams Stay ahead of the curve with the latest research and tools ✅ What We’re Looking For 5+ years of hands-on AI/ML development experience Strong in Python, with experience in TensorFlow, PyTorch, Scikit-learn, Hugging Face Knowledge of NLP, CV, DL architectures (CNNs, RNNs, Transformers) Experience with cloud platforms (AWS/GCP/Azure) and AI services Solid grasp of MLOps, model versioning, deployment, monitoring Strong problem-solving, communication, and mentoring skills 💻 Tech Stack You’ll Work With Languages: Python, SQL Libraries: TensorFlow, PyTorch, Keras, Transformers, Scikit-learn Tools: Git, Docker, Kubernetes, MLflow, Airflow Platforms: AWS, GCP, Azure, Vertex AI, SageMaker Skills: cloud platforms (aws, gcp, azure),docker,computer vision,git,pytorch,airflow,hugging face,nlp,ml,ai,deep learning,kubernetes,mlflow,mlops,tensorflow,scikit-learn,python,machine learning

Job Title: Data Scientist – Agentic AI | Cloud AI | AR/VR Location: Gurgaon- 5 days WFO Experience: 2 to 5 Years Employment Type: Full-time ⸻ About the Role We’re looking for a hands-on Data Scientist who’s excited by the next frontier of AI — from Agentic AI systems and multi-agent collaboration to cloud-based AI services and immersive experiences in AR/VR. This is your chance to work on cutting-edge innovation across verticals such as retail, healthcare, gaming, and enterprise tech. ⸻ Key Responsibilities • Build, deploy, and optimize AI/ML models with a focus on Agentic AI and multi-agent coordination frameworks (e.g., AutoGen, LangChain, etc.) • Leverage Google Cloud AI and Azure AI Services (Vision AI, Vertex AI, Azure ML) for scalable training, inference, and deployment • Apply Computer Vision techniques for object detection, image classification, and spatial tracking in AR/VR contexts • Collaborate cross-functionally with product, engineering, and design teams to bring AI-driven AR/VR applications to life • Utilize Multi-Cloud Pipelines (MCP) for managing end-to-end workflows in a hybrid cloud setup • Continuously experiment with emerging AI techniques in the realm of generative agents, prompt engineering, and memory-based systems ⸻ Must-Have Skills • 2–5 years of hands-on experience in AI/ML model development and deployment • Strong Python skills with experience in frameworks like TensorFlow, PyTorch, or OpenCV

Job Information Date Opened 07/11/2025 City Saidapet Country India Job Role AI/ML Engineering State/Province Tamil Nadu Industry IT Services Job Type Full time Zip/Postal Code 600096 Job Description Introduction to the Role: Are you passionate about building intelligent systems that learn, adapt, and deliver real-world value? Join our high-impact AI & Machine Learning Engineering team and be a key contributor in shaping the next generation of intelligent applications. As an AI/ML Engineer , you’ll have the unique opportunity to develop, deploy, and scale advanced ML and Generative AI (GenAI) solutions in production environments, leveraging cutting-edge technologies, frameworks, and cloud platforms . In this role, you will collaborate with cross-functional teams including data engineers, product managers, MLOps engineers, and architects to design and implement production-grade AI solutions across domains. If you're looking to work at the intersection of deep learning, GenAI, cloud computing, and MLOps — this is the role for you. Accountabilities: Design, develop, train, and deploy production-grade ML and GenAI models across use cases including NLP, computer vision, and structured data modeling. Leverage frameworks such as TensorFlow , Keras , PyTorch , and LangChain to build scalable deep learning and LLM-based solutions. Develop and maintain end-to-end ML pipelines with reusable, modular components for data ingestion, feature engineering, model training, and deployment. Implement and manage models on cloud platforms such as AWS , GCP , or Azure using services like SageMaker , Vertex AI , or Azure ML . Apply MLOps best practices using tools like MLflow , Kubeflow , Weights & Biases , Airflow , DVC , and Prefect to ensure scalable and reliable ML delivery. Incorporate CI/CD pipelines (using Jenkins, GitHub Actions, or similar) to automate testing, packaging, and deployment of ML workloads. Containerize applications using Docker and orchestrate scalable deployments via Kubernetes . Integrate LLMs with APIs and external systems using LangChain, Vector Databases (e.g., FAISS, Pinecone), and prompt engineering best practices. Collaborate closely with data engineers to access, prepare, and transform large-scale structured and unstructured datasets for ML pipelines. Build monitoring and retraining workflows to ensure models remain performant and robust in production. Evaluate and integrate third-party GenAI APIs or foundational models where appropriate to accelerate delivery. Maintain rigorous experiment tracking, hyperparameter tuning, and model versioning. Champion industry standards and evolving practices in ML lifecycle management , cloud-native AI architectures , and responsible AI. Work across global, multi-functional teams, including architects, principal engineers, and domain experts. Essential Skills / Experience: 4–7 years of hands-on experience in developing, training, and deploying ML/DL/GenAI models . Strong programming expertise in Python with proficiency in machine learning , data manipulation , and scripting . Demonstrated experience working with Generative AI models and Large Language Models (LLMs) such as GPT, LLaMA, Claude, or similar. Hands-on experience with deep learning frameworks like TensorFlow , Keras , or PyTorch . Experience in LangChain or similar frameworks for LLM-based app orchestration. Proven ability to implement and scale CI/CD pipelines for ML workflows using tools like Jenkins , GitHub , GitLab , or Bitbucket Pipelines . Familiarity with containerization (Docker) and orchestration tools like Kubernetes . Experience working with cloud platforms (AWS, Azure, GCP) and relevant AI/ML services such as SageMaker , Vertex AI , or Azure ML Studio . Knowledge of MLOps tools such as MLflow , Kubeflow , DVC , Weights & Biases , Airflow , and Prefect . Strong understanding of data engineering concepts , including batch/streaming pipelines, data lakes, and real-time processing (e.g., Kafka ). Solid grasp of statistical modeling , machine learning algorithms , and evaluation metrics. Experience with version control systems (Git) and collaborative development workflows. Ability to translate complex business needs into scalable ML architectures and systems. Desirable Skills / Experience: Working knowledge of vector databases (e.g., FAISS , Pinecone , Weaviate ) and semantic search implementation. Hands-on experience with prompt engineering , fine-tuning LLMs, or using techniques like LoRA , PEFT , RLHF . Familiarity with data governance , privacy , and responsible AI guidelines (bias detection, explainability, etc.). Certifications in AWS, Azure, GCP, or ML/AI specializations. Experience in high-compliance industries like pharma , banking , or healthcare . Familiarity with agile methodologies and working in iterative, sprint-based teams. Work Environment & Collaboration: You will be a key member of an agile, forward-thinking AI/ML team that values curiosity, excellence, and impact. Our hybrid work culture promotes flexibility while encouraging regular in-person collaboration to foster innovation and team synergy. You'll have access to the latest technologies, mentorship, and continuous learning opportunities through hands-on projects and professional development resources. Why Join Us? Build and deploy cutting-edge LLM and GenAI applications that solve real-world problems Collaborate with thought leaders across engineering, product, and data science Work in a dynamic, cloud-native, and automation-driven AI environment Accelerate your growth through certification programs and continuous learning Be part of an innovation-first team that values openness, agility, and integrity About Agilisium - Agilisium, is an AWS technology Advanced Consulting Partner that enables companies to accelerate their "Data-to-Insights-Leap. With $25+ million in annual revenue and over 40% year-over-year growth, Agilisium is one of the fastest-growing IT solution providers in Southern California. Our most important asset? People. Talent management plays a vital role in our business strategy. We’re looking for “drivers”; big thinkers with growth and strategic mindset — people who are committed to customer obsession, aren’t afraid to experiment with new ideas. And we are all about finding and nurturing individuals who are ready to do great work. At Agilisium, you’ll collaborate with great minds while being challenged to meet and exceed your potential

Job Summary We are seeking a forward-thinking AI Architect to design, lead, and scale enterprise-grade AI systems and solutions across domains. This role demands deep expertise in machine learning, generative AI, data engineering, cloud-native architecture, and orchestration frameworks. You will collaborate with cross-functional teams to translate business requirements into intelligent, production-ready AI solutions. Key Responsibilities Architecture & Strategy : Design end-to-end AI architectures that include data pipelines, model development, MLOps, and inference serving. Create scalable, reusable, and modular AI components for different use cases (vision, NLP, time series, etc.). Drive architecture decisions across AI solutions, including multi-modal models, LLMs, and agentic workflows. Ensure interoperability of AI systems across cloud (AWS/GCP/Azure), edge, and hybrid environments. Technical Leadership Guide teams in selecting appropriate models (traditional ML, deep learning, transformers, etc.) and technologies. Lead architectural reviews and ensure compliance with security, performance, and governance policies. Mentor engineering and data science teams in best practices for AI/ML, GenAI, and MLOps. Model Lifecycle & Engineering Oversee implementation of model lifecycle using CI/CD for ML (MLOps) and/or LLMOps workflows. Define architecture for Retrieval Augmented Generation (RAG), vector databases, embeddings, prompt engineering, etc. Design pipelines for fine-tuning, evaluation, monitoring, and retraining of models. Data & Infrastructure Collaborate with data engineers to ensure data quality, feature pipelines, and scalable data stores. Architect systems for synthetic data generation, augmentation, and real-time streaming inputs. Define solutions leveraging data lakes, data warehouses, and graph databases. Client Engagement / Product Integration Interface with business/product stakeholders to align AI strategy with KPIs. Collaborate with DevOps teams to integrate models into products via APIs/microservices. Required Skills & Experience Core Skills : Strong foundation in AI/ML/DL (Scikit-learn, TensorFlow, PyTorch, Transformers, Langchain, etc.) Advanced knowledge of Generative AI (LLMs, diffusion models, multimodal models, etc.) Proficiency in cloud-native architectures (AWS/GCP/Azure) and containerization (Docker, Kubernetes) Experience with orchestration frameworks (Airflow, Ray, LangGraph, or similar) Familiarity with vector databases (Weaviate, Pinecone, FAISS), LLMOps platforms, and RAG design Architecture & Programming Solid experience in architectural patterns (microservices, event-driven, serverless) Proficient in Python and optionally Java/Go Knowledge of APIs (REST, GraphQL), streaming (Kafka), and observability tooling (Prometheus, ELK, Grafana) Tools & Platforms ML lifecycle tools: MLflow, Kubeflow, Vertex AI, Sagemaker, Hugging Face, etc. Prompt orchestration tools: LangChain, CrewAI, Semantic Kernel, DSPy (nice to have) Knowledge of security, privacy, and compliance (GDPR, SOC2, HIPAA, etc.) (ref:hirist.tech)

Senior Zuora Developer-Offshore2 Job Title: Senior Zuora Developer Location: Offshore No of Positions: 2 Job Summary Key Responsibilities Lead the implementation of Quote-to-Cash, CPQ, and Billing systems, ensuring alignment with industry best practices. Configure Zuora Billing, Subscription Management, and finance settings to optimize performance and accuracy. Integrate Zuora with ERP systems like Salesforce, NetSuite, SAP, Oracle, Vertex, and Avalara for seamless data flow. Act as a Subject Matter Expert (SME) on Subscription Business Models and Consumption-Based Billing strategies. Collaborate with cross-functional teams and consulting partners to deliver scalable and robust solutions. Provide technical guidance, troubleshooting, and support to ensure high availability and reliability of Zuora implementations. Qualifications Certification: Certified Zuora Administrator and other relevant technical certifications. Experience: 5+ years of technical experience, with 4+ years specifically in Zuora Billing and Subscription Management. Proven track record in implementing Quote-to-Cash, CPQ, and Billing systems for enterprise clients. Demonstrated ability to manage complex workflows, configurations, and integrations in Zuora. Previous experience working with consulting partners is highly desirable.,

MinutestoSeconds is a dynamic organization specializing in outsourcing services, digital marketing, IT recruitment, and custom IT projects. We partner with SMEs, mid-sized companies, and niche professionals to deliver tailored solutions. We would love the opportunity to work with YOU!! Requirements JD: About the Role: We are looking for a highly motivated and innovative AI/ML Engineer to join our growing team. You will play a key role in designing, developing, and deploying machine learning models and AI-driven solutions that solve real-world business problems. This is a hands-on role requiring a deep understanding of ML algorithms, data preprocessing, model optimization, and scalable deployment. Key Responsibilities: Design and implement scalable ML solutions for classification, regression, clustering, and recommendation use cases Collaborate with data scientists, engineers, and product teams to translate business requirements into ML use cases Preprocess large datasets using Python, SQL, and modern ETL tools Train, validate, and optimize machine learning and deep learning models Deploy models using MLOps best practices (CI/CD, model monitoring, versioning) Continuously improve model performance and integrate feedback loops Research and experiment with the latest in AI/ML trends, including GenAI, LLMs, and transformers Document models and solutions for reproducibility and compliance Required Skills: Strong proficiency in Python, with hands-on experience in NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc. Solid understanding of supervised and unsupervised learning, NLP, and time-series forecasting Experience with cloud platforms such as AWS, GCP, or Azure (preferred: SageMaker, Vertex AI, or Azure ML Studio) Familiarity with Docker, Kubernetes, and MLOps practices Proficient in writing efficient and production-grade code Excellent problem-solving and critical-thinking skills Good to Have: Experience with LLMs, Generative AI, or OpenAI APIs Exposure to big data frameworks like Spark or Hadoop Knowledge of feature stores, data versioning tools (like DVC or MLflow) Published work, research papers, or contributions to open-source ML projects

BU - SALT SL - Tax Tech Location Bangalore 1) Proposed designation Consultant 2) Role Type Individual Contributor 3) Reporting to Manager 4) Geo to be supported US 5) Work Timing 11:30 AM to 8:30 PM IST 6) Roles and responsibilities This hands-on role expects the candidate to apply functional and technical knowledge of SAP and third party tax engines like Onesource/Vertex Establishes and maintains relationships with business leaders. Uses deep business knowledge to drive engagement on major tax integration projects Gather business requirements, lead analysis and drive high level E2E design Drive configuration and development activities to meet business requirements through a combination of internal and external teams Manages external software vendors and System Integrators on project implementation, ensuring adherence to established SLAs Take a domain lead role on IT projects to ensure that all business stakeholders included and ensure they receive sufficient and timely communications Provides leadership to teams and integrates technical expertise and business understanding to create superior solutions for the company and customers. Consults with team members and other organizations, customer and vendors on complex issues. Mentors others in the team on process/technical issues. Uses formal system implementation methodologies during project preparation, requirements gathering, design, build/test and deployment Experience in handling support incidents, major incidents and problems would be an added advantage 7) Educational Qualification BE/B.Tech/MCA 8) Work experience Between 4 to 9 years relevant experience 9) Mandatory Skills SAP Onesource Vertex Indirect tax integration 10) Prefered skills Indirect tax concepts SAP native tax 11) Key behavioural attributes/requirements Hands on experience in Tax Engine Integration(OneSource/Vertex/Avalara) with ERP systems (Oracle/SAP) Understanding of Indirect Tax Concepts Good understanding of O2C and P2P processes Hands on experience in Tax engine configurations (OneSource or Vertex) Experience in troubleshooting tax related issues and solution design Knowledge of Avalara and VAT compliance is a plus 12) Other Information Interview Process: 2 technical round + HR round Does the job role involves travelling : Yes Does the busy season apply to this role No,

Job Overview PitchBook’s Product Owner works collaboratively with key Product stakeholders and teams to deliver the department’s product roadmap. This role takes an active part in aligning our engineering activities with Product Objectives across new product capabilties as well as data and scaling improvements to our core technologies, with a focus on AI/ML data extraction, collection, and enrichment capabilities. Team Overview The Data Technology team within PitchBook’s Product organization develops solutions to support and accelerate our data operations processes. This domain impacts core workflows of data capture, ingestion, and hygiene across our core private and public capital markets datasets. This role works on our AI/ML Collections Data Extraction & Enrichment teams, closely integrated with Engineering and Product Management to ensure we are delivering against our Product Roadmap. These teams provide backend AI/ML services that power PitchBook’s data collection activities and related internal conent management systems. Outline Of Duties And Responsibilities Be a domain expert for your product area(s) and understand user workflows and needs Actively define backlog priority for your team(s) in collaboration with Product and Engineering Manage delivery of features according to the Product Roadmap Validate the priority and impact of incoming requirements from Product Management and Engineering Break down prioritized requirements into well-structured backlog items for the engineering team to complete Create user stories and acceptance criteria that indicate successful implementation of requirements Communicate requirements, acceptance criteria, and technical details to stakeholders across multiple PitchBook departments Define, create, and manage metrics that represent team performance Manage, track, and mitigate risks or blockers of Feature delivery Support execution of AI/ML collections work related but not limited to AI/ML data extraction, collection, and enrichment services. Support PitchBook’s values and vision Participate in various company initiatives and projects as requested Experience, Skills And Qualifications Bachelor's degree in Information Systems, Engineering, Data Science, Business Administration, or a related field 3+ years of experience as a Product Manager or Product Owner within AI/ML or enterprise SaaS domains A proven record of shipping high impact data pipeline or data collection-related tools and services Familiarity with AI/ML workflows, especially within model development, data pipelines, or classification systems Experience collaborating with globally distributed product engineering and operations teams across time zones Excellent communication skills to drive clarity and alignment between business stakeholders and technical teams Bias for action and a willingness to roll up your sleeves and do what is necessary to meet team goals Experience translating user-centric requirements and specifications into user stories and tasks Superior attention to detail including the ability to manage multiple projects simultaneously Strong verbal and written communication skills, including strong audience awareness Experience with shared SDLC and workspace tools like JIRA, Confluence, and data reporting platforms Preferred Qualifications Direct experience with applied AI/ML Engineering services. Strong understanding of supervised and unsupervised ML models, including their training data needs and lifecycle impacts Background in fintech supporting content collation, management, and engineering implementation Experience with data quality measurements, annotation systems, knowledge graphs, and ML Model evaluation Exposure to cloud –based ML infrastructure and data pipeline orchestration tools such as AWS SageMaker, GCP Vertex AI, Airflow, and dbt Certifications related to Agile Product Ownership / Product Management such as CSPO, PSPO, POPM are a plus Working Conditions The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. This role collaborates with Seattle and New York-based stakeholders, and typical overlap is between 6:30 – 8:30AM Pacific. Limited corporate travel may be required to remote offices or other business meetings and events. Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We’ve found that we’re at our best when we’re purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues. 037_PitchBookDataInc PitchBook Data, Inc Legal Entity

Job Title: AI/ML Architect / Senior AI/ML Engineer (8+ Years Experience) Location: [Onsite/Remote/Hybrid – Customize as per your need] Employment Type: Full-time 🔍 About the Role: We are seeking a seasoned AI/ML Architect / Senior Engineer with 10+ years of hands-on experience in Artificial Intelligence, Machine Learning, and Data Science. The ideal candidate will have worked across various industries (e.g., healthcare, finance, retail, manufacturing, etc.) and demonstrated a deep understanding of the end-to-end ML lifecycle — from data ingestion to model deployment and monitoring. You’ll play a strategic and technical leadership role in designing and scaling intelligent systems while staying ahead of evolving market trends in AI, ML, and GenAI. 🎯 Key Responsibilities: Architect, design, and implement scalable AI/ML solutions across multiple domains. Translate business problems into technical solutions using data-driven methodologies. Lead model development, deployment, and operationalization using MLOps best practices. Evaluate and incorporate emerging trends such as Generative AI (e.g., LLMs) , AutoML , Federated Learning , and Responsible AI . Mentor and guide junior engineers and data scientists. Collaborate with product managers, data engineers, and stakeholders for end-to-end delivery. Establish best practices in experimentation, model validation, reproducibility, and monitoring. Work with modern data stack and cloud ecosystems (AWS, Azure, GCP). 🧠 Required Skills and Experience: 8+ years of experience in AI/ML, Data Science, or related roles. Proficient in Python, R, SQL, and key libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.). Strong experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, etc.). Expertise in developing, tuning, and deploying ML/DL models in production environments. Experience in NLP, Computer Vision, Time-Series Forecasting, and/or GenAI. Familiar with model explainability (SHAP, LIME), fairness, and bias mitigation techniques. Solid knowledge of cloud-based architectures (Azure, AWS, or GCP). Experience across domains such as fintech, healthcare, e-commerce, logistics, or manufacturing. 🌐 Preferred Qualifications: Master's or Ph.D. in Computer Science, Data Science, Statistics, or a related field. Experience integrating AI with business applications (e.g., ERP, CRM, RPA platforms). Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines. Familiarity with data governance, privacy-preserving AI, and compliance standards (GDPR, HIPAA). 🌟 Why Join Us? Work with cross-functional, forward-thinking teams on impactful projects. Opportunity to lead initiatives in cutting-edge AI and industry 4.0 innovations . Flexible work culture with continuous learning and growth opportunities. Access to the latest tools, cloud infrastructure, and high-compute environments.

Project Role : Technology Architect Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning Services Minimum 12 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: As an AI/ML lead, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying CCAI and Gen AI models as part of the solution, utilizing deep learning, neural networks and chatbots. Should have hands-on experience in creating, deploying, and optimizing chatbots and voice applications using Google Conversational Agents and other tools. Roles & Responsibilities: I. Solutioning and designing CCAI applications and systems utilizing Google Cloud Machine Learning Services, dialogue flow CX, agent assist, conversational AI. II. Design, develop, and maintain intelligent chatbots and voice applications using Google Dialogflow CX. III. Integrate Dialogflow agents with various platforms, such as Google Assistant, Facebook Messenger, Slack, and websites. Hands-on experience with IVR integration and telephony systems such as Twilio, Genesys, Avaya IV. Integrate with IVR systems and Proficiency in webhook setup and API integration. V. Develop Dialogflow CX - flows, pages, webhook as well as playbook and integration of tool into playbooks. VI. Creation of agents in Agent builder and integrating them into end end to pipeline using python. VII. Apply GenAI-Vertex AI models as part of the solution, utilizing deep learning, neural networks, chatbots, and image processing. VIII. Work with Google Vertex AI for building, training and deploying custom AI models to enhance chatbot capabilities IX. Implement and integrate backend services (using Google Cloud Functions or other APIs) to fulfill user queries and actions. X. Document technical designs, processes, and setup for various integrations. XI. Experience with programming languages such as Python/Node.js Professional & Technical Skills: - Must To Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding. - Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, - Strong understanding of AI/ML algorithms, NLP and techniques. - Experience with chatbot , generative AI models, prompt Engineering. - Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information: 1 The candidate should have a minimum of 10 years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI. 2 The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions., 15 years full time education

JOB DESCRIPTION Roles & responsibilities Here are some of the key responsibilities of Sr Generative AI Engineer : Research and Development: Conduct original research on generative AI models, focusing on model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. Maintain a strong publication record in top-tier conferences and journals, showcasing contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). Multimodal Model Development: Design and experiment with multimodal generative models that integrate various data types, including text, images, and other modalities to enhance AI capabilities. Agentic AI Systems: Develop and design autonomous AI systems that exhibit agentic behavior, capable of making independent decisions and adapting to dynamic environments. Model Development and Implementation: Lead the design, development, and implementation of generative AI models and systems, ensuring a deep understanding of the problem domain. Select suitable models, train them on large datasets, fine-tune hyperparameters, and optimize overall performance. Algorithm Optimization: Optimize generative AI algorithms to enhance their efficiency, scalability, and computational performance through techniques such as parallelization, distributed computing, and hardware acceleration, maximizing the capabilities of modern computing architectures. Data Preprocessing and Feature Engineering: Manage large datasets by performing data preprocessing and feature engineering to extract critical information for generative AI models. This includes tasks such as data cleaning, normalization, dimensionality reduction, and feature selection. Model Evaluation and Validation: Evaluate the performance of generative AI models using relevant metrics and validation techniques. Conduct experiments, analyze results, and iteratively refine models to meet desired performance benchmarks. Technical Leadership: Provide technical leadership and mentorship to junior team members, guiding their development in generative AI through work reviews, skill-building, and knowledge sharing. Documentation and Reporting: Document research findings, model architectures, methodologies, and experimental results thoroughly. Prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Continuous Learning and Innovation: Stay abreast of the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities. Foster a culture of learning and innovation within the team to drive continuous improvement. Mandatory technical & functional skills Strong programming skills in Python and frameworks like PyTorch or TensorFlow. In depth knowledge on Deep Learning - CNN, RNN, LSTM, Transformers LLMs ( BERT, GEPT, etc.) and NLP algorithms. Also, familiarity with frameworks like Langgraph/CrewAI/Autogen to develop, deploy and evaluate AI agents. Ability to test and deploy open source LLMs from Huggingface, Meta- LLaMA 3.1, BLOOM, Mistral AI etc. Ensure scalability and efficiency, handle data tasks, stay current with AI trends, and contribute to model documentation for internal and external audiences. Cloud computing experience, particularly with Google/Azure Cloud Platform, is essential. With strong foundation in understating Data Analytics Services offered by Google or Azure ( BigQuery/Synapse) Hands-on ML platforms offered through GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker Large scale deployment of GenAI/DL/ML projects, with good understanding of MLOps /LLM Ops Preferred Technical & Functional Skills Strong oral and written communication skills with the ability to communicate technical and non-technical concepts to peers and stakeholders Ability to work independently with minimal supervision, and escalate when needed Key behavioral attributes/requirements Ability to mentor junior developers Ability to own project deliverables, not just individual tasks Understand business objectives and functions to support data needs RESPONSIBILITIES Roles & responsibilities Here are some of the key responsibilities of Sr Generative AI Engineer : Research and Development: Conduct original research on generative AI models, focusing on model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. Maintain a strong publication record in top-tier conferences and journals, showcasing contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). Multimodal Model Development: Design and experiment with multimodal generative models that integrate various data types, including text, images, and other modalities to enhance AI capabilities. Agentic AI Systems: Develop and design autonomous AI systems that exhibit agentic behavior, capable of making independent decisions and adapting to dynamic environments. Model Development and Implementation: Lead the design, development, and implementation of generative AI models and systems, ensuring a deep understanding of the problem domain. Select suitable models, train them on large datasets, fine-tune hyperparameters, and optimize overall performance. Algorithm Optimization: Optimize generative AI algorithms to enhance their efficiency, scalability, and computational performance through techniques such as parallelization, distributed computing, and hardware acceleration, maximizing the capabilities of modern computing architectures. Data Preprocessing and Feature Engineering: Manage large datasets by performing data preprocessing and feature engineering to extract critical information for generative AI models. This includes tasks such as data cleaning, normalization, dimensionality reduction, and feature selection. Model Evaluation and Validation: Evaluate the performance of generative AI models using relevant metrics and validation techniques. Conduct experiments, analyze results, and iteratively refine models to meet desired performance benchmarks. Technical Leadership: Provide technical leadership and mentorship to junior team members, guiding their development in generative AI through work reviews, skill-building, and knowledge sharing. Documentation and Reporting: Document research findings, model architectures, methodologies, and experimental results thoroughly. Prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Continuous Learning and Innovation: Stay abreast of the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities. Foster a culture of learning and innovation within the team to drive continuous improvement. Mandatory technical & functional skills Strong programming skills in Python and frameworks like PyTorch or TensorFlow. In depth knowledge on Deep Learning - CNN, RNN, LSTM, Transformers LLMs ( BERT, GEPT, etc.) and NLP algorithms. Also, familiarity with frameworks like Langgraph/CrewAI/Autogen to develop, deploy and evaluate AI agents. Ability to test and deploy open source LLMs from Huggingface, Meta- LLaMA 3.1, BLOOM, Mistral AI etc. Ensure scalability and efficiency, handle data tasks, stay current with AI trends, and contribute to model documentation for internal and external audiences. Cloud computing experience, particularly with Google/Azure Cloud Platform, is essential. With strong foundation in understating Data Analytics Services offered by Google or Azure ( BigQuery/Synapse) Hands-on ML platforms offered through GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker Large scale deployment of GenAI/DL/ML projects, with good understanding of MLOps /LLM Ops Preferred Technical & Functional Skills Strong oral and written communication skills with the ability to communicate technical and non-technical concepts to peers and stakeholders Ability to work independently with minimal supervision, and escalate when needed Key behavioral attributes/requirements Ability to mentor junior developers Ability to own project deliverables, not just individual tasks Understand business objectives and functions to support data needs #KGS QUALIFICATIONS This role is for you if you have the below Educational Qualifications PhD or equivalent degree in Computer Science/Applied Mathematics/Applied Statistics/Artificial Intelligence Preferences to research scholars from IITs, NITs and IIITs ( Research Scholars who are submitted their thesis) Work Experience 8 to 11 Years of experience with strong record of publications in top tier conferences and journals

JOB DESCRIPTION Roles & responsibilities Here are some of the key responsibilities of Sr Generative AI Engineer : Research and Development: Conduct original research on generative AI models, focusing on model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. Maintain a strong publication record in top-tier conferences and journals, showcasing contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). Multimodal Model Development: Design and experiment with multimodal generative models that integrate various data types, including text, images, and other modalities to enhance AI capabilities. Agentic AI Systems: Develop and design autonomous AI systems that exhibit agentic behavior, capable of making independent decisions and adapting to dynamic environments. Model Development and Implementation: Lead the design, development, and implementation of generative AI models and systems, ensuring a deep understanding of the problem domain. Select suitable models, train them on large datasets, fine-tune hyperparameters, and optimize overall performance. Algorithm Optimization: Optimize generative AI algorithms to enhance their efficiency, scalability, and computational performance through techniques such as parallelization, distributed computing, and hardware acceleration, maximizing the capabilities of modern computing architectures. Data Preprocessing and Feature Engineering: Manage large datasets by performing data preprocessing and feature engineering to extract critical information for generative AI models. This includes tasks such as data cleaning, normalization, dimensionality reduction, and feature selection. Model Evaluation and Validation: Evaluate the performance of generative AI models using relevant metrics and validation techniques. Conduct experiments, analyze results, and iteratively refine models to meet desired performance benchmarks. Technical Leadership: Provide technical leadership and mentorship to junior team members, guiding their development in generative AI through work reviews, skill-building, and knowledge sharing. Documentation and Reporting: Document research findings, model architectures, methodologies, and experimental results thoroughly. Prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Continuous Learning and Innovation: Stay abreast of the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities. Foster a culture of learning and innovation within the team to drive continuous improvement. Mandatory technical & functional skills Strong programming skills in Python and frameworks like PyTorch or TensorFlow. In depth knowledge on Deep Learning - CNN, RNN, LSTM, Transformers LLMs ( BERT, GEPT, etc.) and NLP algorithms. Also, familiarity with frameworks like Langgraph/CrewAI/Autogen to develop, deploy and evaluate AI agents. Ability to test and deploy open source LLMs from Huggingface, Meta- LLaMA 3.1, BLOOM, Mistral AI etc. Ensure scalability and efficiency, handle data tasks, stay current with AI trends, and contribute to model documentation for internal and external audiences. Cloud computing experience, particularly with Google/Azure Cloud Platform, is essential. With strong foundation in understating Data Analytics Services offered by Google or Azure ( BigQuery/Synapse) Hands-on ML platforms offered through GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker Large scale deployment of GenAI/DL/ML projects, with good understanding of MLOps /LLM Ops Preferred Technical & Functional Skills Strong oral and written communication skills with the ability to communicate technical and non-technical concepts to peers and stakeholders Ability to work independently with minimal supervision, and escalate when needed Key behavioral attributes/requirements Ability to mentor junior developers Ability to own project deliverables, not just individual tasks Understand business objectives and functions to support data needs RESPONSIBILITIES Roles & responsibilities Here are some of the key responsibilities of Sr Generative AI Engineer : Research and Development: Conduct original research on generative AI models, focusing on model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. Maintain a strong publication record in top-tier conferences and journals, showcasing contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). Multimodal Model Development: Design and experiment with multimodal generative models that integrate various data types, including text, images, and other modalities to enhance AI capabilities. Agentic AI Systems: Develop and design autonomous AI systems that exhibit agentic behavior, capable of making independent decisions and adapting to dynamic environments. Model Development and Implementation: Lead the design, development, and implementation of generative AI models and systems, ensuring a deep understanding of the problem domain. Select suitable models, train them on large datasets, fine-tune hyperparameters, and optimize overall performance. Algorithm Optimization: Optimize generative AI algorithms to enhance their efficiency, scalability, and computational performance through techniques such as parallelization, distributed computing, and hardware acceleration, maximizing the capabilities of modern computing architectures. Data Preprocessing and Feature Engineering: Manage large datasets by performing data preprocessing and feature engineering to extract critical information for generative AI models. This includes tasks such as data cleaning, normalization, dimensionality reduction, and feature selection. Model Evaluation and Validation: Evaluate the performance of generative AI models using relevant metrics and validation techniques. Conduct experiments, analyze results, and iteratively refine models to meet desired performance benchmarks. Technical Leadership: Provide technical leadership and mentorship to junior team members, guiding their development in generative AI through work reviews, skill-building, and knowledge sharing. Documentation and Reporting: Document research findings, model architectures, methodologies, and experimental results thoroughly. Prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Continuous Learning and Innovation: Stay abreast of the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities. Foster a culture of learning and innovation within the team to drive continuous improvement. Mandatory technical & functional skills Strong programming skills in Python and frameworks like PyTorch or TensorFlow. In depth knowledge on Deep Learning - CNN, RNN, LSTM, Transformers LLMs ( BERT, GEPT, etc.) and NLP algorithms. Also, familiarity with frameworks like Langgraph/CrewAI/Autogen to develop, deploy and evaluate AI agents. Ability to test and deploy open source LLMs from Huggingface, Meta- LLaMA 3.1, BLOOM, Mistral AI etc. Ensure scalability and efficiency, handle data tasks, stay current with AI trends, and contribute to model documentation for internal and external audiences. Cloud computing experience, particularly with Google/Azure Cloud Platform, is essential. With strong foundation in understating Data Analytics Services offered by Google or Azure ( BigQuery/Synapse) Hands-on ML platforms offered through GCP : Vertex AI or Azure : AI Foundry or AWS SageMaker Large scale deployment of GenAI/DL/ML projects, with good understanding of MLOps /LLM Ops Preferred Technical & Functional Skills Strong oral and written communication skills with the ability to communicate technical and non-technical concepts to peers and stakeholders Ability to work independently with minimal supervision, and escalate when needed Key behavioral attributes/requirements Ability to mentor junior developers Ability to own project deliverables, not just individual tasks Understand business objectives and functions to support data needs #KGS QUALIFICATIONS This role is for you if you have the below Educational Qualifications PhD or equivalent degree in Computer Science/Applied Mathematics/Applied Statistics/Artificial Intelligence Preferences to research scholars from IITs, NITs and IIITs ( Research Scholars who are submitted their thesis) Work Experience 8 to 11 Years of experience with strong record of publications in top tier conferences and journals