542 Generative Ai Jobs - Page 10

Responsibilities: - Contribute and build an internal product library that is focused on solving business problems related to prediction & recommendation. Research unfamiliar methodologies, techniques to fine tune existing models in the product suite and, recommend better solutions and/or technologies. Improve features of the product to include newer machine learning algorithms in the likes of product recommendation, real time predictions, fraud detection, offer personalization etc Collaborate with client teams to on-board data, build models and score predictions. Participate in building automations and standalone applications around machine learning algorithms to enable a One Click solution to getting predictions and recommendations. Analyze large datasets, perform data wrangling operations, apply statistical treatments to filter and fine tune input data, engineer new features and eventually aid the process of building machine learning models. Run test cases to tune existing models for performance, check criteria and define thresholds for success by scaling the input data to multifold. Demonstrate a basic understanding of different machine learning concepts such as Regression, Classification, Matrix Factorization, K-fold Validations and different algorithms such as Decision Trees, Random Forrest, K-means clustering. Demonstrate working knowledge and contribute to building models using deep learning techniques, ensuring robust, scalable and high-performance solutions Minimum Qualifications: Education: Master's or PhD in a quantitative discipline (Statistics, Economics, Mathematics, Computer Science) is highly preferred. Deep Learning Mastery: Extensive experience with deep learning frameworks (TensorFlow, PyTorch, or Keras) and advanced deep learning projects across various domains, with a focus on multimodal data applications. Generative AI Expertise: Proven experience with generative AI models and techniques, such as RAG, VAEs, Transformers, and applications at scale in content creation or data augmentation. Programming and Big Data: Expert-level proficiency in Python and big data/cloud technologies (Databricks and Spark) with a minimum of 4-5 years of experience . Recommender Systems and Real-time Predictions: Expertise in developing sophisticated recommender systems, including the application of real-time prediction frameworks. Machine Learning Algorithms: In-depth experience with complex algorithms such as logistic regression, random forest, XGBoost, advanced neural networks, and ensemble methods. Experienced with machine learning algorithms such as logistic regression, random forest, XG boost, KNN, SVM, neural network, linear regression, lasso regression and k-means. Desirable Qualifications: Generative AI Tools Knowledge: Proficiency with tools and platforms for generative AI (such as OpenAI, Hugging Face Transformers). Databricks and Unity Catalog: Experience leveraging Databricks and Unity Catalog for robust data management, model deployment, and tracking. Working experience in CI/CD tools such as GIT & BitBucket

Role & responsibilities Proficient in backend development using Python and Node.js. Strong experience with frontend frameworks using React or Angular. Hands-on knowledge and experience with Microsoft Azure cloud services, including Azure Foundry, Functions, Blob, and container tools such as Azure Kubernetes. Ability to design and manage data pipelines ensuring high-quality data is available for AI model training and deployment. Experience working with structured and unstructured data that span across SQL databases and NoSQL databases such as MongoDB or CosmosDB. Experience with various AI tools like LangChain, Autogen, and LangGraph. Proficient with API development and management. Experience building and working with CI/CD pipelines and version control tools like GIT. Experience developing and delivering event driven architectures. Experience in using and implementing open-source large language models such as Llama, Mistral, and assorted embedding models

We are looking for a Senior Generative AI Engineer who is passionate about cutting-edge AI innovation and has significant hands-on experience in building and deploying Generative AI models. In this role, you will be responsible for designing, fine-tuning, and optimizing large language models (LLMs), implementing innovative GenAI solutions, and contributing to the architecture of AI-driven platforms that deliver real business value. You will collaborate with cross-functional teams including data scientists, machine learning engineers, product managers, and cloud infrastructure teams to build scalable, reliable, and secure AI systems. This is a high-impact position where you will directly influence the AI roadmap and innovation strategy. Key Responsibilities : - Design, develop, and fine-tune state-of-the-art Generative AI and LLM models tailored for various business use cases. - Build, integrate, and optimize solutions using transformer-based architectures (e.g., GPT, BERT, T5, LLaMA, Mistral). - Apply techniques such as fine-tuning, prompt engineering, RLHF (Reinforcement Learning from Human Feedback), and knowledge distillation to improve model performance. - Work with vector databases (e.g., FAISS, Pinecone, Weaviate) for implementing retrieval-augmented generation (RAG) pipelines. - Develop and deploy embedding models and integrate them into LLM pipelines. - Collaborate with engineering and product teams to deploy scalable AI systems using MLOps practices and CI/CD pipelines. - Leverage LangChain, Hugging Face Transformers, OpenAI APIs, and similar frameworks/tools to accelerate development. - Optimize model performance across different environments (cloud/on-premise). - Develop end-to-end pipelines, from data preprocessing to real-time inference and monitoring. - Ensure high standards of software quality, including testing, version control, code reviews, and documentation. - Stay up to date with the latest research in Generative AI and translate breakthroughs into production-ready solutions. Required Skills & Qualifications : - Experience : 7+ years in AI/ML, data science, or software engineering; at least 3 - 4 years in Generative AI/LLMs. - Advanced Python programming skills, including familiarity with object-oriented design and software engineering best practices. - Deep expertise in PyTorch, TensorFlow, Transformers (Hugging Face), LangChain, and OpenAI or Anthropic APIs. - Experience in LLM fine-tuning, parameter-efficient tuning methods (LoRA, PEFT), RLHF, and model evaluation. - Experience with embeddings, vector stores (FAISS, Pinecone), semantic search, and RAG systems. - Hands-on experience with AWS, GCP, or Azure; knowledge of MLOps tools (SageMaker, Vertex AI, MLflow, Kubeflow) for training, deploying, and monitoring models. - Familiarity with structured/unstructured data handling and integrating AI systems with SQL/NoSQL databases. - Strong analytical thinking, problem-solving ability, and a keen interest in research and innovation.

Job Summary: We are seeking a highly skilled and hands-on AI Engineer with 3+ years of proven experience in building and deploying solutions using Generative AI and Large Language Models (LLMs). You will work on cutting-edge applications leveraging transformer-based architectures, fine-tuning, prompt engineering, and scalable AI deployments. This role is ideal for engineers passionate about AI research and real-world productization of generative AI technologies. Key Responsibilities: Design, develop, and deploy solutions using LLMs (e.g., GPT, LLaMA, Mistral, Claude, PaLM, etc.) for various NLP and content generation tasks. Work on fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) pipelines. Integrate LLMs into enterprise applications with APIs and orchestrate workflows using Python, LangChain, or similar frameworks. Optimize model performance, latency, and cost for production use. Collaborate with data scientists, MLOps engineers, and product managers to deliver scalable AI features. Conduct experiments, analyze results, and publish internal findings or contribute to whitepapers. Ensure ethical, secure, and responsible use of AI technologies in all implementations. Required Skills & Experience: 3+ years of hands-on experience working with Generative AI, LLMs, and NLP technologies. Strong programming skills in Python and experience with libraries like Transformers (Hugging Face), LangChain, PyTorch, TensorFlow, etc. Proven track record of fine-tuning LLMs, developing embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models on cloud platforms (AWS, Azure, GCP) and using ML pipelines or MLOps tools. Solid understanding of deep learning, NLP architectures, tokenization, and evaluation metrics for generative models. Experience in API development and integration of LLMs into user-facing applications. Preferred Qualifications: Masters or PhD in Computer Science, AI/ML, Data Science, or related field. Experience with OpenAI APIs, Anthropic, Cohere, or open-source LLMs (e.g., Mistral, Falcon, LLaMA 3). Understanding of RLHF (Reinforcement Learning from Human Feedback) and model alignment techniques. Contributions to open-source AI projects or publications in GenAI/LLM.

Role Purpose The purpose of this role is to develop minimum viable product (MVP) and comprehensive AI solutions that meet and exceed clients expectations and add value to business. Do Manage the product/ solution development using the desired AI techniques Lead development and implementation of custom solutions through thoughtful use of modern AI technology Review and evaluate the use cases and decide whether a product can be developed to add business value Create the overall product development strategy and integrating with the larger interfaces Create AI models and framework and implement them to cater to a business problem Draft the desired user Interface and create AI models as per business problem Analyze technology environment and client requirements to define product solutions using AI framework/ architecture Implement the necessary security features as per products requirements Review the used case and see the latest AI that can be used in products development Identify problem areas and perform root cause analysis and provide relevant solutions to the problem Tracks industry and application trends and relates these to planning current and future AI needs Create and delegate work plans to the programming team for product development Interact with Holmes advisory board for knowledge sharing and best practices Responsible for developing and maintaining client relationships with the key strategic partners and decision makers Drive discussions and provide consultation around product design as per customer needs Participate in client interactions and gather insights regarding product development Interact with vertical delivery and business teams and provide and correct responses to RFP/ client requirements Assist in products demonstration and receive feedback from the client Design presentations for seminars, meetings and enclave primarily focused over product Team Management Resourcing Forecast talent requirements as per the current and future business needs Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Deliver No.Performance ParameterMeasure1.Continuous technical project management & deliveryAdoption of new technologies, IP creation, MVP creation, Number of patents filed, Research papers created2.Client CentricityNo. of automation done, On-Time Delivery, cost of delivery, optimal resource allocation3.Capability Building & Team Management% trained on new age skills, Team attrition %, Number of webinars conducted (internal/external) Mandatory Skills: Generative AI. Experience: 5-8 Years.

ABOUT THE ROLE Role Description: The UI Developer is responsible for designing, developing, and maintaining user interfaces for software applications and solutions that meet business needs. This role involves working closely with product managers, designers, and other engineers to create high-quality, scalable software solutions. Roles & Responsibilities: Take ownership of complex software projects from conception to deployment. Manage software delivery scope, risk, and timeline. Possess strong rapid prototyping skills and can quickly translate concepts into working code. Contribute to front-end development using cloud technology. Develop innovative solutions using generative AI technologies. Conduct code reviews to ensure code quality and adherence to best practices. Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations. Identify and resolve technical challenges effectively. Stay updated with the latest trends and advancements in UI development. Work closely with the product team, business team, and other stakeholders. Design, develop, and implement user interfaces and modules, including custom reports, interfaces, and enhancements. Analyze and understand the functional and technical requirements of applications, solutions, and systems and translate them into software architecture and design specifications. Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software. Identify and resolve software bugs and performance issues. Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality software on time. Maintain detailed documentation of software designs, code, and development processes. Customize modules to meet specific business requirements. Work on integrating with other systems and platforms to ensure seamless data flow and functionality. Provide ongoing support and maintenance for applications, ensuring that they operate smoothly and efficiently. Develop intuitive and responsive user interfaces (UIs) that enable users to efficiently interact with multiple datasets, leveraging modern front-end frameworks and libraries. Collaborate with UX designers to translate design mockups and wireframes into interactive and visually appealing user interfaces. Implement UI animations and transitions to enhance the user experience and provide feedback to users. Optimize UI performance by identifying and addressing bottlenecks, ensuring smooth and fast interactions. Ensure accessibility standards are met, making the UI usable for people with disabilities. Participate in Agile ceremonies (Daily Scrum/Refinement/Retro) to partner with the product owner and team to discuss, set, and deliver two-week developmental goals. Keep abreast of technology upgrades and advancements and provide recommendations to improve process efficiencies. Basic Qualifications and Experience: Masters degree and 1 to 3 years of experience in Computer Science, IT, or a related field OR Bachelors degree with 3 - 5 years of experience in Computer Science, IT, or a related field OR Diploma with 7 - 9 years of experience in Computer Science, IT, or a related field Functional Skills: Must-Have Skills: Strong knowledge of information systems and network technologies. Proficiency in programming languages such as JavaScript (preferred), HTML/CSS. Strong understanding of software development methodologies, including Agile and Scrum. Experience with version control systems like Git. Experience with front-end frameworks such as React.js or Angular.js. Experience with responsive and adaptive design principles. Knowledge of UI/UX best practices and design patterns. Experience with UI testing frameworks such as Jest, Enzyme, or Cypress. Experience with modern front-end frameworks and libraries (e.g., React, Node.js), and expertise in building responsive and user-friendly UIs. Good-to-Have Skills: Strong understanding of cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker). Experience with monitoring and logging tools (e.g., Prometheus, Grafana). Experience with data processing tools like Hadoop or similar. Experience with UI performance optimization techniques. Familiarity with accessibility standards and tools for testing accessibility. Knowledge of data governance principles and familiarity with Great Expectations for data validation. Hands-on experience building data pipelines using applications like Databricks. Solid grasp of infrastructure as code, developing and operating programmatic pipelines for cloud services, and using automated DevSecOps frameworks to run a cloud SDLC. Knowledge or experience in basic DevOps support and deployment including Docker, Kubernetes, CICD, etc. Professional Certifications: Relevant certifications such as CISSP, CompTIA Network+, or MCSE (preferred). Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills. Ability to work effectively with global, virtual teams. High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Strong presentation and public speaking skills. Shift Information: This position requires you to work a later shift and may be assigned a second or third shift schedule. Candidates must be willing and able to work during evening or night shifts, as required based on business requirements.

Were hiring a Generative AI Trainer ( Full-time & Freelance ) to lead engaging training sessions and guide learners through real-world AI applications. Youll be teaching the latest in Gen AI tools like LLMs, Prompt Engineering, Lang Chain , and more. Key Responsibilities: Deliver structured offline and online training on Generative AI topics Teach concepts including LLMs, Prompt Engineering, Lang Chain, Hugging Face , etc. Support learners with project work, queries, and assessments Create and update training material, hands-on exercises, and case studies Ensure high engagement and learner satisfaction Stay up-to-date with latest AI research and industry practices Key Skills Required: Strong expertise in Python , Machine Learning , and Deep Learning Practical experience with Large Language Models (GPT, Llama, etc.) , NLP , and RAG Knowledge of Lang Chain, Hugging Face, Transformers , and Prompt Engineering Familiarity with Flask/Django , SQL , and Tableau is a plus Hands-on experience with real-time AI/ML/Gen AI projects is a must Strong communication skills and a passion for teaching

Your Role & Responsibilities: Looking to make a significant impact This is your chance to become a key part of a dynamic team of talented professionals, leading the development and deployment of innovative, industry-leading, cloud-based AI services. We are seeking an experienced AI & Cloud Software Engineering Manager to join us. This leadership role focuses on guiding, mentoring, and managing a team of engineers in designing, developing, and deploying AI-based services. You will be instrumental in problem-solving, automating wide ranges of tasks, and interfacing with other teams, offering managers, and customers to solve complex problems. You will build a strong, agile, and modern team culture aimed at creating world-class development and deployment environments. Your efforts will ensure industry-leading user experiences for our customers. As an essential part of the leadership team, you will contribute to the cloud services architecture and design while mentoring the next generation of cloud engineers. Responsibilities : Lead, mentor, and manage a team of AI and cloud software engineers. Oversee the planning, execution, and delivery of AI-based services and cloud solutions. Provide technical direction and architectural oversight for AI and cloud projects. Interface with other teams, managers, and customers to align project goals and deliverables. Address and resolve technical challenges and roadblocks faced by the team. Monitor and evaluate team performance, providing feedback and development opportunities. Stay updated with the latest trends in AI and cloud technologies to encourage continuous improvement. Ensure the delivery of industry-leading user experiences for customers. Allocate resources effectively to meet project and organizational goals. Maintain comprehensive documentation of projects and processes, and report progress to senior management. Required education Bachelor's Degree Required technical and professional expertise Minimum 12-15 years of experience as Full Stack Developer with a focus on AI projects Experience with AI and machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, LLMs, Generative AI. Familiarity with AI model deployment and integration. Solid understanding of backend technologies, including server-side languages (Node.js, Python, Java, etc.) and databases (Cassandra, PostgreSQL, etc.). Understanding and experience with RESTful APIs, Java/J2EE, Kafka & GitHub. Strong experience with Cloud Technologies, Kubernetes based microservices architecture, Kafka, Object Storage, Cassandra database and docker container technologies. Knowledge on IBM Cloud Technologies will be an added advantage. At least 6 years of hands-on development experience building applications with one or more of the following: Java, Spring, Liberty, Node.js, Express.js, Golang, NoSQL DB, Redis, distributed caches, containers etc., At least 3 years of experience in building and operating highly secured, distributed cloud services with one or more of the following: IBM Cloud, AWS, Azure, SRE, CI/CD, Docker, Container orchestration, performance testing, etc., At least 3 years of experience in web technologies: HTTP, REST, JSON, HTML, Ajax, JavaScript etc., Solid understanding of the micro-services architecture and modern cloud programming practices. Strong ability to design a clean, developer-friendly API. Passionate about constant, continuous learning and applying new technologies as well as mentoring others. Keen troubleshooting skills and strong verbal/written communication skills. Preferred technical and professional experience Preferred Skills: Experience in using messaging brokers like RabbitMQ, Kafka etc. Operating Systems (such as Red Hat, Ubuntu, etc.) Knowledge of network protocols such as TCP/IP, HTTP, etc. Experience and working knowledge of version Control systems like Github and build tools like Maven/Gradle Ability to learn and apply new technologies quickly Experience in working on a SaaS application with high industry standard CI/CD, and development cycle processes Strong sense of ownership of deliverables UI test automation skills - Selenium and/or Puppeteer Beyond the requirements, candidates should be passionate about in the role: Continuous learning and ability to adapt to change Working across global teams and collaborating across teams and organization boundaries Finding innovative ways to solve complex problems with cutting edge technologies.

Job description We are having a F2F weekend drive for the requirement of a Data Scientist + Gen AI at our LTIM Bangalore Whitefield office. Date - 14th June 2025 Experience - 6+ Years Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS, AI/ML, NLP Location - LTIMindtree Bangalore Whitefield Office Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model Deployment Generic JD- More than 6 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen.

Senior Backend Developer Experience: 4 - 8 Years Exp Salary : Competitive Preferred Notice Period : Within 30 Days Shift : 10:00AM to 7:00PM IST Opportunity Type: Onsite (Ahmedabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Python, JS, MLOps, Microservices, SQL, DevOps, Generative AI Good to have skills : AWS, Azure Attri (One of Uplers' Clients) is Looking for: Senior Backend Developer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description Our engineering team is growing and we are looking to bring on board a Senior Backend Developer who can help us transition to the next phase of the company. You will be pivotal in refining our system architecture, ensuring the various tech stacks play well with each other, and smoothening the DevOps process. A must have well verse understanding of software paradigm, and curiosity to carve out designs of varying ML, MLOps, and LLMOps problem statements. You will determine to lead your team into right direction towards very end of implementation for underlined project. By joining our team, you will get exposure to working across a swath of modern technologies while building an enterprise-grade ML platform in the most promising area. Responsibilities: Be the bridge between engineering and product teams. Understand long-term product roadmap and architect a system design that will scale with our plans. Take ownership of converting product insights into detailed engineering requirements. Work break-down among team, and orchestrating the development of components for each sprint. Very well verse with solution designing, and documentation (HLD/LLD). Developing "Zero Defect Software" with extreme efficiency by utilizing modern cutting-edge tools (ChatGPT, Co-pilot etc). Adapt, and impart the mindset to build a unit of software that is secured, instrumented, and resilient. Author high-quality, highly-performance, and unit-tested code running on a distributed environment using containers. Continually evaluate and improve DevOps processes for a cloud-native codebase. Strong design skills in defining API Data Contracts / OOAD / Microservices / Data Models and Concurrency concepts. An ardent leader with an obsession for quality, refinement, innovation, and empowering leadership. Qualifications: Work Experience 5-7 years of experience with hands-on experience with development of full fledge Systems/Micro-services using Python, or JS programming. 3+ years experience having Senior engineering responsibilities. 3+ years of people mentorship/leadership experience managing engineers preferably with good exposure in leading multiple development teams. 3+ years of experience in object-oriented design, and agile development methodologies. Basic experience in developing/deploying cloud-native software using GCP / AWS / Azure. Proven track record building large-scale Product grade (high-throughput, low-latency, and scalable) systems. A well-versed understanding and designing skills of SQL/NoSQL/OLAP DBs. Up-to date with modern cutting-edge technologies to boost efficiency and delivery of team. (Bonus: To have an understanding of Generative AI frameworks/Libraries such RAG, Langchain, LLAMAindex etc.) Skills Strong documentation skills. As a team, we heavily rely on elaborate documentation for everything we are working on. Ability to take authoritative decision, and hold accountability. Ability to motivate, lead, and empower others. Strong independent contributor as well as a team player. Working knowledge of ML and familiarity with concepts of MLOps You will excel in this role if You have a product mindset. You understand, care about, and can relate to our customers. You take ownership, collaborate, and follow through to the very end. You love solving difficult problems, stand your ground, and get what you want from engineers. Resonate with our core values of innovation, curiosity, accountability, trust, fun, and social good. How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: Attri, an AI organization, leads the way in enterprise AI, offering advanced solutions and services driven by AI agents and powered by Foundation Models. Our comprehensive suite of AI-enabled tools drives business impact, enhances quality, mitigates risk, and also helps unlock growth opportunities. About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Design, develop, and maintain Conversational AI models including Chat BOTs. Develop robust unit and integration tests using testing frameworks/ manual to guarantee code quality and application stability. Expertly debug and troubleshoot complex application issues. Integrate Gen AI capabilities to enhance the product efficiency and effectiveness. Proven experience building Conversational AI models / Chat BOTs using Kore.ai platform. In depth understanding of Gen AI capabilities Proficiency in unit testing frameworks. Experience in Data Analytics and Python Exceptional problem solving and debugging skills. Excellent communication and collaboration skills. Experience in Agile Scrum practice. Experience in JIRA and Confluence Ability to work independently and manage multiple tasks effectively while contributing to a team environment.

We are seeking a talented Java backend Software Engineer with expertise in software engineering to join our team. As a Full Stack Software Engineer, your primary responsibility will be to develop & integrate Generative AI solutions that focus on technology improvements. Specifically, you will be working on projects involving Generative AI solutions for Technology Assistants & Data Management Efficiencies and will contribute for Java backend development such as IDE plugins Data Connections & Integrators. Responsibilities : - Collaborate with cross-functional teams such as Data Scientists, Product Partners and Partner Team Developers to identify opportunities for process improvements that can be solved using machine learning and generative AI. - Write clean, high-performance, high-quality, maintainable code. - Create connectors to various Content and Collaboration tools using tool specific API's such as Jira, Slack, Git etc - Create backend applications using Java, docker & in-house frameworks to orchestrate AI applications - Design and develop Engineering Solutions & generative AI Applications for above ensuring scalability, efficiency, and maintainability of such solutions. - Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs. - Stay abreast of the latest advancements in the field of Generative AI Application Development and actively contribute to the research and development of new Generative AI Applications. Requirements: - A Master's or Ph.D. degree in Computer Science or a related field. - Proven experience working as a Software Engineer, with a focus on Java, and exposure to Generative AI Applications such as chatGPT. - Strong proficiency in programming languages such as Java, Kotlin, Scala etc ( Mandatory) - Experience or Exposure in creating IDE Plugins for PyCharm, VS Code, IntelliJ & Web Consoles ( Nice to have ) - Experience in python and data pipelines ( nice to have) - Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies. - Experience with large language models (LLMs) & prompt engineering techniques, vector DB's ( Nice to have ) - Strong communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders. - Proven ability to adapt and learn new technologies and frameworks quickly. - A proactive mindset with a passion for continuous learning and research. Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Develop and maintain responsive web applications using ReactJS Manage application state using React Hooks or Redux Toolkit Integrate and consume RESTful APIs for frontend-backend communication Implement quality assurance best practices including validations and error handling Collaborate using Git and manage workflows through CI/CD pipelines Work with the team on repository setup and code management Collaborate with backend developers to integrate database systems Contribute to Gen AI feature integrations and enhancements Ensure performance optimization and code scalability Primary Skills: Proficient in Full Stack Development/UI development with ReactJS Strong experience with API integrations State management using React Hooks or Redux Toolkit Familiarity with QA processes, validations, and automated deployment using CI/CD tools Solid understanding of Git workflows and version control Secondary Skills: Working knowledge of Generative AI concepts and applications Experience with repository creation and codebase setup Exposure to backend database integration (e.g. PostgreSQL, OpenSearch etc.) Familiarity with Node.js or backend frameworks is a bonus

The Company India's marquee global technology & consulting company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the technology product and service industries as well as a blue-chip roster of clients for their Consulting engagements. They are a respected career company and a long-term wealth creator. The Job We are seeking a highly skilled Generative AI Senior Lead with 11+ Years of IT industry experience in which 5/6 years should be in AI/ML/DS domain, including Gen AI technologies to lead the design and deployment of cutting-edge AI solutions. The ideal candidate will possess deep expertise in Generative AI , strong analytical skills, and excellent communication abilities to engage with clients and internal teams. This role involves designing AI architectures, implementing scalable models, and ensuring solutions align with business objectives. Roles & Responsibilities: Client Interaction: Collaborate with clients to understand business needs and define AI solutions. Solution Design: Develop AI architectures addressing client objectives and technical requirements. Metrics Definition: Define success criteria and measurable KPIs with stakeholders. Technical Implementation: Guide teams in deploying AI solutions efficiently. Performance Monitoring: Ensure AI model accuracy and recommend improvements as needed. Client Collaboration: Act as the main point of contact between clients and internal teams. Knowledge Sharing: Keep up with Generative AI advancements and contribute insights. Documentation: Maintain detailed technical reports and project records. Solution Design & Communication: Ability to design end-to-end AI solutions, from requirement elicitation to deployment strategy. Experience in architecting systems including data preprocessing, model integration, and optimization. Excellent verbal and written communication skills for client engagement and stakeholder Your Profile Technical Proficiency: Machine Learning Algorithms: Linear/logistic regression, decision trees, random forests, SVMs, neural networks. Data Science Tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras. Cloud Platforms: AWS, Azure, GCP. Natural Language Processing (NLP): Transformer models, attention mechanisms, word embeddings. Computer Vision: CNNs, RNNs, object detection. Robotics: Reinforcement learning, motion planning, control systems. Data Ethics & Responsible AI: Strong understanding of bias in ML, algorithmic fairness, ethical data handling, and transparency. Solution Design & Communication: Ability to design end-to-end AI solutions, from requirement elicitation to deployment strategy. Experience in architecting systems including data preprocessing, model integration, and optimization. Excellent verbal and written communication skills for client engagement and stakeholder presentations. Secondary Skill Set: Domain Knowledge: Understanding of industry applications (healthcare, finance, manufacturing). Project Management: Ability to oversee timelines, milestones, and deliverables, coordinating cross-functional teams. Data Understanding: Strong grasp of feature engineering, preprocessing, and quality assurance.

Join us for an exciting SDE Traineeship at Meesho. Based on the performance at Meesho, successful candidates will be considered for a full-time opportunity (FTE). The FTE salary offered will be INR 20,00,000 p.a. fixed + Benefits . Position: Software Development Engineer - Trainee Location : Bengaluru APPLY HERE: https://p.hck.re/6TcJ About the role: As an SDE Trainee , we expect you to be motivated in solving real-life complex problems and creating compelling experiences for our resellers. Being a small company we have a culture of creative problem- solving, intellectual design, fast-paced development, and passionate product delivery. The pace of our growth is incredible. If you want to tackle hard, interesting and UNIQUE problems, and create an impact within an entrepreneurial environment, JOIN US! Key Responsibilities: Collaborate with teams to develop new features for Meesho customers and suppliers Leverage state-of-the-art technologies and write highly performant code Take end-to-end ownership of features, from ideation to production Technical Requirements: 0-1 years of experience Strong problem-solving skills Excellent understanding of data structures and algorithms, and their space & time complexities Strong hands-on and practical working experience with at least one programming language: Java/Python/Javascript Excellent coding skills should be able to convert design into code fluently.

Design & develop end-to-end machine learning models & GenAI workflows Fetch & process data from BigQuery & various sources for model development Build & deploy models using Python & frameworks like Scikit Learn, XGBoost/CatBoost, TensorFlow & Gemini Required Candidate profile 4+ years of experience in the Data Science domain and should have hands on exp in Python, Machine Learning and/or Generative AI (Artificial Intelligence) This is an Individual contributor role

The Company India's marquee global technology & consulting company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the technology product and service industries as well as a blue-chip roster of clients for their Consulting engagements. They are a respected career company and a long-term wealth creator. The Job We are seeking an 6 Years of IT industry experience in which 2/3 years should be in AI/ML/DS domain, including Gen AI technologies. We are seeking an accomplished Generative AI Technical Lead to spearhead the development, implementation, and optimization of Generative AI solutions. As the Lead Developer, you will play a pivotal role in prompt engineering, pipeline creation, workflow establishment, and ensuring the quality of the technical outputs generated by the team. This role requires strong technical expertise in Generative AI, hands-on experience in development, and the ability to lead and guide a team effectively. Primary Skill Set: Generative AI Expertise: Good understanding of various Generative AI techniques, including GANs, VAEs, and other relevant architectures. Proven experience in applying these techniques to real-world problems for tasks such as image and text generation. Conversant with Gen AI development tools like Prompt engineering, Langchain, Semantic Kernels, Function calling. Exposure to both API based and opens source LLMs based solution design. Technical Proficiency: Machine learning algorithms: Linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks Data science tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras Cloud computing platforms: AWS, Azure, GCP Natural language processing (NLP): Transformer models, attention mechanisms, word embeddings Computer vision: Convolutional neural networks, recurrent neural networks, object detection Robotics: Reinforcement learning, motion planning, control systems Data ethics: Bias in machine learning, fairness in algorithms Your Profile Roles & Responsibilities: Technical Leadership: Lead a team of developers in the creation, implementation, and optimization of Generative AI solutions. Provide technical guidance, resolve challenges, and foster a collaborative environment. Prompt Engineering: Spearhead the design and development of prompt engineering strategies to influence and control the output of Generative AI models. Optimize prompts for desired results. Pipeline Design: Design end-to-end data pipelines that encompass data preprocessing, feature engineering, model training, and deployment. Ensure pipelines are efficient, scalable, and well-documented. Technical Review: Review the technical outputs generated by the team, including code, models, and pipelines. Ensure high-quality and maintainable solutions that adhere to best practices. Testing and Validation: Implement testing methodologies to validate the performance and accuracy of Generative AI models. Develop and execute unit tests, integration tests, and validation strategies. Deployment Strategy: Collaborate with DevOps and deployment teams to deploy trained models into production environments. Ensure smooth integration and monitor performance post-deployment. Workflow Optimization: Identify opportunities to optimize development workflows, enhance productivity, and streamline processes. Implement tools and practices to improve efficiency. Collaboration: Interface with cross-functional teams, including data scientists, architects, and business stakeholders. Collaborate on solution design, implementation, and project milestones. Documentation: Maintain comprehensive documentation of technical designs, code, and workflows. Ensure documentation is up-to-date, accessible, and understandable for team members.

Role & responsibilities We are seeking a skilled Data Engineer with advanced expertise in Python, PySpark, Databricks, and Machine Learning, along with a working knowledge of Generative and Agentic AI. This role is critical in ensuring data integrity and driving innovation across enterprise systems. You will design and implement ML-driven solutions to enhance Data Governance & Data Privacy initiatives through automation, self-service capabilities, and scalable, AI-enabled innovation. Key Responsibilities: Implement ML and Generative/Agentic AI solutions to optimize Data Governance processes. Design, develop, and maintain scalable data pipelines using Python, PySpark, and Databricks. Develop automation frameworks to support data quality, lineage, classification, and access control. Develop and deploy machine learning models to uncover data patterns, detect anomalies, and enhance data governance and privacy compliance Collaborate with data stewards, analysts, and governance teams to build self-service data capabilities. Work with Databricks, Azure Data Lake, AWS, and other cloud-based data platforms for data engineering. Build, configure, and integrate APIs for seamless system interoperability. Ensure data integrity, consistency, and compliance across systems and workflows. Integrate AI models to support data discovery, metadata enrichment, and intelligent recommendations. Optimize data architecture to support analytics, reporting, and governance use cases. Monitor and improve the performance of ML/AI components in production environments. Stay updated with emerging AI and data engineering technologies to drive continuous innovation. Technical Skills: Strong programming skills in Python, PySpark, SQL for data processing and automation. Experience with Databricks and Snowflake (preferred) for building and maintaining data pipelines. Experience with Machine Learning model development and Generative/Agentic AI frameworks (e.g. LLMs, Transformers, LangChain) especially in the Data Management space Experience working with REST APIs & JSON for service integration Experience working with cloud-based platforms such as Azure, AWS, or GCP Power BI dashboard development experience is a plus. Soft Skills: Strong problem-solving skills and attention to detail. Excellent communication and collaboration abilities, with experience working across technical and business teams

Location: Any / Remote / Work From Home Employment Type: Full-time Job Summary: We are seeking skilled and innovative AI Engineers with a minimum 2-4 years of experience in developing and deploying AI solutions . The ideal candidate should have practical knowledge in AWS , Amazon Bedrock , LLMs , Claude AI , and Custom AI Development . You will contribute to the design and implementation of cutting-edge Generative AI (GenAI) and Mainstream AI applications across diverse business domains. This is an excellent opportunity to work with emerging technologies in an agile, fast-paced environment with full ownership of AI engineering pipelines. Key Responsibilities: Develop custom machine learning models and fine-tune foundation models for enterprise use Design and implement LLM-based and Generative AI solutions tailored to client use cases Work with OpenAI, Anthropic, HuggingFace models and their APIs to build secure, scalable AI systems Perform prompt engineering and experiment with parameter tuning and context optimization Build APIs and backend services to integrate AI models into product workflows Collaborate with product, data, and DevOps teams to deliver end-to-end AI-powered solutions Ensure best practices for AI model governance, security, performance, and ethical use Stay current with advancements in LLMs, vector databases (e.g., Pinecone, FAISS), and GenAI tooling Document architecture, experiments, and processes clearly and effectively Participate in peer reviews, client meetings, and cross-functional planning discussions Required Qualifications: Minimum 2-4 years of professional experience in AI/ML , with specific focus on LLMs and GenAI Strong experience working on AWS Bedrock , Lambda, and related services Proficiency in Python , including experience with libraries like HuggingFace, LangChain, etc. Familiarity with Anthropic , OpenAI , or other foundation models in production settings Experience with custom AI model development and model fine-tuning Good understanding of cloud-native AI deployments and API integrations Ability to apply prompt engineering techniques to optimize LLM responses Exposure to vector databases and RAG pipelines Strong problem-solving, communication, and team collaboration skills Preferred Qualifications (STRONG PLUS): Hands-on experience with LangChain, RAG pipelines, or agent frameworks Familiarity with AWS Sagemaker, DynamoDB, Lambda, or other AI tooling in AWS Knowledge of Docker or Kubernetes for containerizing AI workloads Understanding of MLOps principles and tools (MLflow, SageMaker Pipelines, etc.) Contributions to open-source AI projects or published GenAI applications AI/ML certifications Familiarity with enterprise use cases in biotech, healthcare, or manufacturing What We Offer: Remote work option Competitive salary package Exciting projects in the field of LLMs, AI, and cloud-native development Continuous learning opportunities in Generative AI and cloud AI tools A collaborative and fast-paced environment with a forward-thinking team Access to state-of-the-art tools and flexible project ownership How to Apply: Please submit your resume and cover letter outlining your relevant experience and why you'd be a great fit for Arocom. We differentiate candidates based on professionalism. We admire the new age methods like a video resume. If you have one please share the URL along with your resume. Your privacy is important to us, so we will not be contacting candidates by phone. If your application is selected, we will email you a link to schedule your interview at your convenient time. Please check your emails regularly, including your SPAM folder. Arocom encourages work from home and has a Bring Your Own Device (BYOD) policy. Employees / Consultants working from home are expected to use their personal laptops/desktops for work-related tasks.

The Company India's marquee global technology & consulting company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the technology product and service industries as well as a blue-chip roster of clients for their Consulting engagements. They are a respected career company and a long-term wealth creator. The Job We are seeking an experienced 3+ years of IT experience ( 2 Years in AI/ML/DS Domain). Gen AI Development : Data collection and preparation: Collect and prepare data for training and evaluating LLMs. This may involve cleaning and processing text data, or creating synthetic data. Model development: Design and implement LLM models. This may involve choosing the right architecture, training the model, and tuning the hyperparameters. Model evaluation: Evaluate the performance of LLM models. This may involve measuring the accuracy of the model on a held-out dataset, or assessing the quality of the generated text. Model deployment: Deploy LLM models to production. This may involve packaging the model, creating a REST API, and deploying the model to a cloud computing platform. Responsible AI: Should have proficient knowledge in Responsible AI and Data Privacy principles to ensure ethical data handling, transparency, and accountability in all stages of AI development. Must demonstrate a commitment to upholding privacy standards, mitigating bias, and fostering trust within data-driven initiatives. Experience in working with ML toolkit like R, NumPy, MatLab etc.. Experience in data mining, statistical analysis and data visualization Your Profile Roles and Responsibility: LLM Development/Deployment Pipeline creation, workflows Study and transform Gen AI PoCs to production grade deployment Design machine learning systems, Run machine learning tests and experiments Research and implement appropriate ML algorithms and tools Develop machine learning applications according to requirements Select appropriate datasets and data representation methods Perform statistical analysis and fine-tuning using test results Train and retrain systems when necessary

Responsibilities The Graphic Designer role for the Large Deals Business Narrative team integrates into a complex, strategic sales environment. In this role, Graphic Designers will support assigned activities under the guidance of a Lead Designer or Writer. Primary responsibilities include creating proposal response documents and presentations, marketing collateral, brand Identity packages, customized communication in both physical and digital formats, microsites, and multimedia elements such as video and audio recordings. Additionally, Graphic Designers are expected to engage in conceptualization activities, participate in strategy discussions, and attend team-wide enablement meetings. Responsibilities: Strong graphic design fundamentals (typography, color theory, hierarchy, contrast, and grid/alignments). Ability to abide by brand guidelines and possess a strong knowledge of design standards. Assist Lead Designers in the creation of various design projects throughout the entire project lifecycle. Enhance graphic visualization concepts based on guidance from Lead Designers to produce finalized artifacts. Capable of understanding specifics required to produce various presentation and design artifacts (dimensions, DPI, file size, etc.). Manage multiple concurrent assignments with defined timelines with the assistance of workload planning from Designer and Writer team leaders Demonstrate proficiency in designing PPT decks, brand identity, campaign branding, posters, booklets, handouts, emailers, sales videos, and animated PPTs for client meetings. Must Have skills: Demonstrate the ability to understand Large Deals sales activities and create plans from brainstorming ideas to the final execution of deliverables for assigned projects. Be present in-person with a team during critical activities for assigned projects. Exhibit strong teamwork and interpersonal skills, articulating ideas clearly during meetings to help non-creative stakeholders visualize concepts. Showcase problem-solving skills by presenting multiple solutions that communicate complex information clearly. Fluency in both spoken and written English is necessary to succeed in this role. Possess sound knowledge of design tools such as Adobe Photoshop, Illustrator, InDesign, Premiere, After Effects, and MS Office tools like PowerPoint and Word. Knowledge of additional design tools like 3D Studio Max or Generative AI is a bonus. Preferred Skills: Domain->Communication Design->Graphic Design Educational Requirements Bachelor of Arts Service Line Strategic Large Deals team * Location of posting is subject to business requirements

We are seeking a highly skilled Senior Machine Learning Engineer to join our dynamic team. The ideal candidate will have a deep understanding of Machine Learning, AI, and cloud platforms like Azure. You will play a key role in designing, developing, and deploying ML models and Generative AI solutions to solve complex business problems. Role overview Engineering Masters degree or PhD in Data Science, Statistics, Mathematics, or related fields 5 years+ experience in a Machine Learning Engineer role into large corporate organizations Experience of working with ML models in a cloud ecosystem. Statistics & amp; Machine Learning Statistics : Strong understanding of statistical analysis and modelling techniques (e.g., regression analysis, hypothesis testing, time series analysis) Classical ML : Very strong knowledge in classical ML algorithms for regression & classification, supervised and unsupervised machine learning, both theoretical and practical (e.g. using scikit-learn, xgboost) ML niche : Expertise in at least one of the following ML specialisations: Timeseries forecasting / Natural Language Processing / Computer Vision Deep Learning: Good knowledge of Deep Learning fundamentals (CNN, RNN, transformer architecture, attention mechanism, ) and one of the deep learning frameworks (pytorch, tensorflow, keras) Generative A I: Good understanding of Generative AI specificities and previous experience in working with Large Language Models is a plus (e.g. with openai, langchain). MLOps Model strategy : Expertise in designing, implementing, and testing machine learning strategies. Model integration : Very strong skills in integrating a machine learning algorithm in a data science application in production. Model performance : Deep understanding of model performance evaluation metrics and existing libraries (e.g., scikit-learn, evidently) Model deployment: Experience in deploying and managing machine learning models in production either using specific cloud platform, model serving frameworks, or containerization. Model monitoring : Experience with model performance monitoring tools is a plus (Grafana, Prometheus). Software Engineering Python: Very strong coding skills in Python including modularity, OOP, data & config manipulation frameworks (e.g., pandas, pydantic) etc. Python ecosystem : Strong knowledge of tooling in Python ecosystem such as dependency management tooling (venv, poetry), documentation frameworks (e.g. sphinx, mkdocs, jupyter-book), testing frameworks (unittest,pytest) Software engineering practices: Experience in putting in place good software engineering practices such as design patterns, testing (unit, integration), clean code, code formatting etc. Debugging: Ability to troubleshoot and debug issues within machine learning pipelines. Data Science Experimentation and Analytics Data Visualization: Knowledge of data visualization tools such as plotly, seaborn, matplotlib, etc. to visualise, interpret and communicate the results of machine learning models to stakeholders. Basic knowledge of PowerBI is a plus. Data Cleaning: Experience with data cleaning and preprocessing techniques such as feature scaling, dimensionality reduction, and outlier detection (e.g. with pandas, scikit-learn). Data Science Experiments: Understanding of experimental design and A/B testing methodologies. Data Processing: Databricks/Spark: Basic knowledge of PySpark for big data processing Databases : Basic knowledge of SQL to query data in internal systems Data Formats: Familiarity with different data storage formats such as Parquet and Delta. DevOps Azure DevOps : Experience using a DevOps platform such as Azure DevOps for using Boards, Repositories, Pipelines Git : Experience working with code versioning (git), branch strategies, and collaborative work with pull requests. Proficient with the most basic git commands. CI / CD : Experience in implementing/maintaining pipelines for continuous integration (including execution of testing strategy) and continuous deployment is preferable. Cloud Platform: Azure Cloud: Previous experience with services like Azure Machine Learning Services and/or Azure Databricks on Azure is preferable. Soft skills: Strong analytical and problem-solving skills, with attention to detail Excellent verbal and written communication and pedagogical skills with technical and non-technical teams Excellent teamwork and collaboration skills Adaptability and reactivity to new technologies, tools, and techniques Fluent in English. What would you do here: Managing the lifecycle of machine learning models Develop and implement machine learning models to solve complex business problems. Ensure that models are accurate, efficient, reliable, and scalable. Deploy machine learning models to production environments, ensuring that models are integrated with software systems. Monitor machine learning models in production, ensuring that models are performing as expected and that any errors or performance issues are identified and resolved quickly. Maintain machine learning models over time. This includes updating models as new data becomes available, retraining models to improve performance, and retiring models that are no longer effective. Develop and implement policies and procedures for ensuring the ethical and responsible use of machine learning models. This includes addressing issues related to bias, fairness, transparency, and accountability. Continuous Improvements: Stay up to date with the latest developments in the field: read research papers, attend conferences, and participate in trainings to expand their knowledge and skills. Identify and evaluate new technologies and tools that can improve the efficiency and effectiveness of machine learning projects. Propose and implement optimizations for current machine learning workflows and systems. Proactively identify areas of improvement within the pipelines. Make sure that created code is compliant with our set of engineering standards. Collaboration with other data experts (Data Engineers, Platform Engineers, and Data Analysts) Participate to pull requests reviews coming from other team members. Ask for review and comments when submitting their own work. Actively participate to the day-to-day life of the project (Agile rituals), the data science team (DS meeting) and the rest of the Global Engineering team.

We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization . You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value. Roles & Responsibilities 1) Technical Leadership Lead the technical design and architecture of complex Generative AI systems. Ensure solutions align with business objectives, scalability requirements, and technical feasibility. Guide development teams through best practices , architecture reviews, and technical decision-making processes. 2) Solution Architecture Design and develop end-to-end Generative AI solutions , including data pipelines , model training, deployment, and real-time monitoring. Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments. Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks. Design, train, and fine-tune AI/ML models , especially Generative AI and Large Language Models (LLMs) , to address specific use cases. Build conversational AI solutions and chatbots using frameworks such as LangChain , RAG (Retrieval-Augmented Generation) , and Chain-of-Thought (COT) prompting . 3) Production Deployment Lead the deployment of Generative AI models into production environments . Optimize deployment pipelines leveraging tools like Docker, Kubernetes , and cloud-native services for orchestration. Ensure seamless integration of GenAI solutions into existing CI/CD pipelines. 4) Data Processing & Feature Engineering Build scalable ETL workflows for managing structured, semi-structured, and unstructured data. Implement data wrangling , preprocessing, and feature engineering pipelines to prepare data for Generative AI applications. Optimize workflows to extract meaningful insights from large datasets . 5) Model Optimization Identify and implement optimization strategies such as hyperparameter tuning , feature engineering , and model selection for performance enhancement. Focus on computational efficiency and scaling models to production-level performance. 6) Pilot/POCs Development Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements. Collaborate with delivery and product teams to scale successful pilots to production-grade solutions. 7) Evangelization Promote and drive the adoption of Generative AI solutions across customer and delivery teams. Provide technical leadership and mentorship to teams working on GenAI projects. Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders. 8) Continuous Improvement Stay at the forefront of AI advancements , frameworks, and tools, including emerging concepts in Generative AI. Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications. Required Skills & Qualifications 10+ years of experience in AI/ML architecture, model development, and production deployment Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions Hands-on experience with frameworks like LangChain , Retrieval-Augmented Generation (RAG) , and advanced prompting techniques Proficiency in advanced techniques such as embeddings and Chain-of-Thought (COT) prompting Experience working with cloud platforms , primarily GCP , with optional experience in AWS or Azure Strong understanding of MLOps tools, pipelines, and model monitoring in production Proficiency in Python and SQL for model development and data processing Experience with data preprocessing, ETL workflows , and feature engineering for AI applications Strong knowledge of containerization tools like Docker and orchestration platforms like Kubernetes Solid understanding of CI/CD pipelines for continuous deployment and integration of AI solutions Experience working with large datasets for structured and unstructured AI applications Deep experience in model optimization, including hyperparameter tuning and computational efficiency strategies Proven track record of leading POCs/pilots and scaling them to production-grade deployments Preferred Skills Familiarity with Reinforcement Learning from Human Feedback (RLHF) . Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks. Strong understanding of orchestration for large-scale production environments. Key Attributes Strong technical leadership and mentorship abilities. Excellent communication and stakeholder management skills. Strategic thinking with the ability to architect scalable and future-ready AI systems. Passion for solving business challenges using state-of-the-art AI techniques. Commitment to staying updated with the latest advancements in AI/ML technologies. Why Join Us? Lead the development of cutting-edge Generative AI solutions for real-world applications. Be part of a collaborative, innovative, and technology-driven team. Opportunity to work with advanced AI/ML tools and frameworks. Drive innovation through technical leadership , mentorship, and solution evangelization. Continuous professional growth with access to the latest AI/ML technologies and frameworks.

Role Purpose The purpose of this role is to develop minimum viable product (MVP) and comprehensive AI solutions that meet and exceed clients expectations and add value to business. Do Manage the product/ solution development using the desired AI techniques Lead development and implementation of custom solutions through thoughtful use of modern AI technology Review and evaluate the use cases and decide whether a product can be developed to add business value Create the overall product development strategy and integrating with the larger interfaces Create AI models and framework and implement them to cater to a business problem Draft the desired user Interface and create AI models as per business problem Analyze technology environment and client requirements to define product solutions using AI framework/ architecture Implement the necessary security features as per products requirements Review the used case and see the latest AI that can be used in products development Identify problem areas and perform root cause analysis and provide relevant solutions to the problem Tracks industry and application trends and relates these to planning current and future AI needs Create and delegate work plans to the programming team for product development Interact with Holmes advisory board for knowledge sharing and best practices Responsible for developing and maintaining client relationships with the key strategic partners and decision makers Drive discussions and provide consultation around product design as per customer needs Participate in client interactions and gather insights regarding product development Interact with vertical delivery and business teams and provide and correct responses to RFP/ client requirements Assist in products demonstration and receive feedback from the client Design presentations for seminars, meetings and enclave primarily focused over product Team Management Resourcing Forecast talent requirements as per the current and future business needs Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Deliver No.Performance ParameterMeasure 1. Continuous technical project management & deliveryAdoption of new technologies, IP creation, MVP creation, Number of patents filed, Research papers created 2. Client CentricityNo. of automation done, On-Time Delivery, cost of delivery, optimal resource allocation 3. Capability Building & Team Management% trained on new age skills, Team attrition %, Number of webinars conducted (internal/external) Mandatory Skills: Generative AI.

The Role Machine learning and data science are interdisciplinary fields that require a combination of skills in mathematics, statistics, programming, and domain-specific knowledge to extract meaningful insights from data and develop predictive models. Skills Requirements Mandatory Skillset - ML Techniques, any ML Framework, Gen AI COncepts, Azure, Python Secondary Skillset - AWS, or Google Cloud Requirements Work closely with cross-functional teams to understand business requirements and translate them into machine learning solutions. Collect, clean, and pre-process large datasets to prepare them for machine learning models. Develop and implement machine learning algorithms and models for solving specific business problems. Collaborate with data engineers to ensure seamless integration of machine learning models into production systems. Fine-tune models for optimal performance and conduct thorough testing and validation. Stay updated on the latest advancements in machine learning and artificial intelligence and assess their potential impact on our projects. Effectively communicate complex technical concepts and findings to non-technical stakeholders. Monitor and maintain deployed models and update them as needed to adapt to changes in data or business requirements. Adhere to ethical standards and ensure that machine learning solutions comply with relevant regulations. Proficiency in Python with hands-on experience in cloud platforms including GCP, AWS, and Azure; strong skills in API integration.