1069 Keras Jobs - Page 39

Job Overview: We are looking for a highly skilled AI & Agentic Developer to design, build, and deploy intelligent autonomous systems. This role involves developing AI-powered agents that can perceive, reason, and act independently, leveraging LLMs, reinforcement learning, and multi-agent systems. You will work on cutting-edge AI frameworks like LangChain, AutoGen, CrewAI, and MLOps pipelines for scalable deployment. Key Responsibilities: AI & Machine Learning Development: Develop, train, and fine-tune machine learning (ML) and deep learning (DL) models. Implement LLMs, NLP, reinforcement learning (RL), and computer vision (CV) models. Optimize retrieval-augmented generation (RAG) systems with vector databases (FAISS, Pinecone, Chroma). Work on multimodal AI systems integrating text, image, and audio processing. Agentic AI Systems Development: Build autonomous AI agents that can make decisions, learn from feedback, and interact with environments. Implement multi-agent frameworks using LangChain, CrewAI, AutoGen, BabyAGI, MetaGPT. Integrate AI agents with APIs, databases, and enterprise applications for real-world deployment. Software Engineering & MLOps: Design and deploy AI models using Docker, Kubernetes, and CI/CD pipelines. Implement MLOps workflows for continuous training, monitoring, and model retraining. Optimize AI solutions for cloud platforms (AWS, Azure, GCP) and edge computing. AI Governance & Security: Implement AI safety measures, including adversarial defense and bias mitigation. Ensure compliance with AI regulations (GDPR, HIPAA, SOC 2) and ethical AI principles. Secure AI agents against prompt injection, model poisoning, and adversarial attacks. Required Skills & Qualifications: Technical Skills: Strong programming skills in Python, Java, or R. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Experience with LLMs & NLP (Hugging Face, OpenAI API, BERT, GPT, Claude). Proficiency in multi-agent frameworks (LangChain, CrewAI, AutoGen). Knowledge of reinforcement learning (PPO, A3C, DDPG, SAC). Experience with vector databases (FAISS, Pinecone, Chroma) and knowledge graphs. Strong foundation in MLOps, cloud AI services (AWS, Azure AI, Google Vertex AI). Soft Skills: Strong analytical and problem-solving skills. Ability to work in a fast-paced, cross-functional team. Excellent communication and documentation skills. Preferred Qualifications: Masters. in Computer Science, AI, or Data Science. Certifications in AI/ML (AWS ML Specialist, Google ML Engineer, Microsoft AI Engineer). Experience with autonomous systems, robotics, or digital twins. 5-7 years of similar or equivalent experience.

Summary Position Summary Associate Vice President - Quality Engineer Specialist (AI) Role Overview: As a Quality Engineer Specialist Leader specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft and be the visionary driving force behind our transformation to AI-powered quality engineering, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while driving tangible value for Deloitte's business investments. Leveraging your extensive quality engineering and AI craftsmanship, along with advanced proficiency across multiple quality assurance disciplines and modern AI/GenAI frameworks and models, you will consistently demonstrate an exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a strong background in quality assurance, test automation, and a deep understanding of AI and GenAI technologies, including their application to quality engineering. This role is crucial in enhancing our testing frameworks and ensuring the highest quality standards for our products. The team US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Responsibilities: Strategic Vision and Alignment: Accountable for crafting and articulating a vision for AI/GenAI as it specifically applies to quality engineering in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams across various organizational levels. Advocacy and Technology Roadmap: Advocate for, develop, and communicate the AI/GenAI quality engineering implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress. Focus on reuse and leverage of existing quality assets to minimize overall costs with an eye on continuous improvement. Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs related to quality approaches, automation tools, test data management (e.g., subsetting, masking, generation, virtualization, anonymization), and standards, ensuring they are fit-for-purpose in product testing cycles. Implement advanced techniques such as BDD and GenAI-based automation to evolve testing frameworks and increase automation coverage, minimizing manual quality assurance to exceptional scenarios only. Establish and refine AI/ML/GenAI domain standards and best practices. Remain hands-on with test design and scripting/coding automations, contributing to team velocity during sprints, and actively engage with engineers across the SSDLC. Be self-driven to learn new technologies, experiment with them, and inspire quality engineers to apply new technologies effectively. Capability Evolution and Development: Mentor and develop quality engineers to become masters of their craft. Coach and develop their skills in modern engineering practices, specifically related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R&D collaborations with academia and communities. Iterative Value Delivery: Embrace an iterative/incremental approach to quality engineering. Apply a leaning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence. Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement. Expert Proficiency and Continuous Improvement: Possess deep expertise in modern software engineering and quality engineering practices. Identify inefficiencies and opportunities for innovation. Act as a role model and enhance the product engineering operating model to be lean, adaptable, and responsive to changes, ensuring that quality engineering teams can deliver business value efficiently and effectively. Guide and transform the organization to embrace lean principles and foster a culture of innovation. Tech/Quality Risk Management: Ensure appropriate quality tool use, adoption by quality engineers, and confirm/review that products are tested, scaled, and operated to be free of defects and are secure/compliant, including providing guidance for necessary optimizations. Identify potential quality risks and develop mitigation strategies. This involves proactive problem-solving and contingency planning to address any issues that may arise during development. Influential Communication: Influence, persuade, and drive decision-making processes. Communicate effectively in both written and verbal forms. Craft clear, structured arguments and technical trade-offs supported by evidence. Organizational Engagement and Collaboration: Engage stakeholders at all levels of the organization, from team members to middle management to executives. Build collaborative and constructive relationships. Co-create and drive momentum and value across multiple organizational levels. Key Qualifications: A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. 15+ years of hands-on experience in quality assurance/engineering, test automation including coding the test scripts, and in AI/ML, with last 2 years focused on GenAI as well. Proven experience in Python, TensorFlow, PyTorch, Keras, C#, Julia, and ML libraries. Strong experience in GenAI models and technologies such as OpenAI, Claude, Gemini, LangChain, Vector databases, and approaches like prompt engineering, fine-tuning, etc. Hands-on experience with automation-first techniques like BDD and test automation tools such as TOSCA, Selenium, Gherkin, Functionize, Testim, and AccelQ. Strong experience with cloud hyper-scalers like AWS, Azure, and GCP. Expertise in modern software engineering practices, including Agile methodologies, DevSecOps, SRE, MLOps, and deployment techniques like Blue-Green, and Canary to enable A/B testing approaches. Proven track record of leading and managing high-performing quality engineering teams. Exceptional interpersonal and organizational skills as well as strategic mindset with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. 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. Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. 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. 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. Professional development From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. Requisition code: 302376 Show more Show less

Flex is the diversified manufacturing partner of choice that helps market-leading brands design, build and deliver innovative products that improve the world. We believe in the power of diversity and inclusion and cultivate a workplace culture of belonging that views uniqueness as a competitive edge and builds a community that enables our people to push the limits of innovation to make great products that create value and improve people's lives. A career at Flex offers the opportunity to make a difference and invest in your growth in a respectful, inclusive, and collaborative environment. If you are excited about a role but don't meet every bullet point, we encourage you to apply and join us to create the extraordinary. To support our extraordinary teams who build great products and contribute to our growth, we’re looking to add " Information Technology Manager " position will be based in " chennai " What a typical day looks like : Consults with clients to analyze and understand functions to be automated, client needs, objectives, desired features and input and output requirements, writes and maintains functional and technical specifications. To work with operation and support departments developing new local systems or system intergration included: To develop and implement information systems and databases using appropriate technologies including Mircrosoft.net, C#, ASP.net, SQL, etc. To produce reports using Tableau, Crystal reports, visual studio and SQL reporting services. To develop mobile Apps using visual studio, ASP.net, Jquery, Javascript, CSS, Swift(Xcode) for IOS and Andriod studio. Develop and implement AI algorithms and models. Work with engineers to build and deploy machine learning models. Expertise in REST API development, NoSQL design, RDBMS design. Strong problem-solving skills and a commitment to delivering high-quality software. Working Knowledge of MS SQL Server with Good command on SQL Queries Knowledge of data structures, algorithms, and software design patterns. Experience with version control systems Work with Corp. and regional IT team to deploy corp. standard solutions to site. Support and Maintain existing systems and applications, ensuring operational efficiency. Write system/application development documentation including process maps, query lists, report lists and formats. Lead and guide a team of developers, delegating tasks, cross training, and enhancing their skills sets and knowledge/expertise. The experience we’re looking to add to our team: Typically requires a Bachelors degree or equivalent systems experience. Typically requires a minimum of 7 years of system development experience. Experience in leading a team of developers in completing various projects Systems and web development experience in the .NET framework including C# / VB.net and Oracle / SQL server database is requirement. Experience with AI/ML frameworks, such as TensorFlow, Keras, or PyTorch. Good English skills are required. Experience in ERP, customs systems are preferred. Experience in Mobile Apps developments are preferred. What you’ll receive for the great work you provide: Health Insurance Paid Time Off RK103 Site Flex is an Equal Opportunity Employer and employment selection decisions are based on merit, qualifications, and abilities. We celebrate diversity and do not discriminate based on: age, race, religion, color, sex, national origin, marital status, sexual orientation, gender identity, veteran status, disability, pregnancy status, or any other status protected by law. We're happy to provide reasonable accommodations to those with a disability for assistance in the application process. Please email accessibility@flex.com and we'll discuss your specific situation and next steps (NOTE: this email does not accept or consider resumes or applications. This is only for disability assistance. To be considered for a position at Flex, you must complete the application process first). Show more Show less

Summary Position Summary Associate Vice President - Quality Engineer Specialist (AI) Role Overview: As a Quality Engineer Specialist Leader specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft and be the visionary driving force behind our transformation to AI-powered quality engineering, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while driving tangible value for Deloitte's business investments. Leveraging your extensive quality engineering and AI craftsmanship, along with advanced proficiency across multiple quality assurance disciplines and modern AI/GenAI frameworks and models, you will consistently demonstrate an exemplary track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a strong background in quality assurance, test automation, and a deep understanding of AI and GenAI technologies, including their application to quality engineering. This role is crucial in enhancing our testing frameworks and ensuring the highest quality standards for our products. The team US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Responsibilities: Strategic Vision and Alignment: Accountable for crafting and articulating a vision for AI/GenAI as it specifically applies to quality engineering in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams across various organizational levels. Advocacy and Technology Roadmap: Advocate for, develop, and communicate the AI/GenAI quality engineering implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress. Focus on reuse and leverage of existing quality assets to minimize overall costs with an eye on continuous improvement. Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs related to quality approaches, automation tools, test data management (e.g., subsetting, masking, generation, virtualization, anonymization), and standards, ensuring they are fit-for-purpose in product testing cycles. Implement advanced techniques such as BDD and GenAI-based automation to evolve testing frameworks and increase automation coverage, minimizing manual quality assurance to exceptional scenarios only. Establish and refine AI/ML/GenAI domain standards and best practices. Remain hands-on with test design and scripting/coding automations, contributing to team velocity during sprints, and actively engage with engineers across the SSDLC. Be self-driven to learn new technologies, experiment with them, and inspire quality engineers to apply new technologies effectively. Capability Evolution and Development: Mentor and develop quality engineers to become masters of their craft. Coach and develop their skills in modern engineering practices, specifically related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R&D collaborations with academia and communities. Iterative Value Delivery: Embrace an iterative/incremental approach to quality engineering. Apply a leaning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence. Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement. Expert Proficiency and Continuous Improvement: Possess deep expertise in modern software engineering and quality engineering practices. Identify inefficiencies and opportunities for innovation. Act as a role model and enhance the product engineering operating model to be lean, adaptable, and responsive to changes, ensuring that quality engineering teams can deliver business value efficiently and effectively. Guide and transform the organization to embrace lean principles and foster a culture of innovation. Tech/Quality Risk Management: Ensure appropriate quality tool use, adoption by quality engineers, and confirm/review that products are tested, scaled, and operated to be free of defects and are secure/compliant, including providing guidance for necessary optimizations. Identify potential quality risks and develop mitigation strategies. This involves proactive problem-solving and contingency planning to address any issues that may arise during development. Influential Communication: Influence, persuade, and drive decision-making processes. Communicate effectively in both written and verbal forms. Craft clear, structured arguments and technical trade-offs supported by evidence. Organizational Engagement and Collaboration: Engage stakeholders at all levels of the organization, from team members to middle management to executives. Build collaborative and constructive relationships. Co-create and drive momentum and value across multiple organizational levels. Key Qualifications: A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. 15+ years of hands-on experience in quality assurance/engineering, test automation including coding the test scripts, and in AI/ML, with last 2 years focused on GenAI as well. Proven experience in Python, TensorFlow, PyTorch, Keras, C#, Julia, and ML libraries. Strong experience in GenAI models and technologies such as OpenAI, Claude, Gemini, LangChain, Vector databases, and approaches like prompt engineering, fine-tuning, etc. Hands-on experience with automation-first techniques like BDD and test automation tools such as TOSCA, Selenium, Gherkin, Functionize, Testim, and AccelQ. Strong experience with cloud hyper-scalers like AWS, Azure, and GCP. Expertise in modern software engineering practices, including Agile methodologies, DevSecOps, SRE, MLOps, and deployment techniques like Blue-Green, and Canary to enable A/B testing approaches. Proven track record of leading and managing high-performing quality engineering teams. Exceptional interpersonal and organizational skills as well as strategic mindset with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. 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. Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. 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. 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. Professional development From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. Requisition code: 302376 Show more Show less

Role –Senior Gen AI Engineer Location - Chennai - CKC Mode of Interview - In Person Data - 7th June 2025 (Saturday) Job Description Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data. Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) Work on tasks involving language modeling, text generation, understanding, and contextual comprehension. Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets. Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS. Integrate AI models with our company's data to enhance and augment existing applications. Role & Responsibility Handle data preprocessing, augmentation, and generation of synthetic data. Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) Develop and Maintaining AI Pipelines Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. Ensure the robustness, efficiency, and scalability of AI systems. Stay updated with the latest advancements in AI and machine learning technologies. Skills & Experience Strong foundation in machine learning, deep learning, and computer science. Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). Experience with natural language processing (NLP) and computer vision is a plus. Ability to work independently and as part of a team. Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. Experience in developing and deploying AI models in production environments. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions Should be able to bring new ideas and innovative solutions to our clients Show more Show less

Role Summary: The Technical Lead/Manager will be responsible for leading the AI CoE team, driving the implementation of AI-powered solutions for the organization. They will coordinate across multiple teams, work closely with stakeholders, and oversee the technical aspects of AI/ML projects, ensuring the effective application of generative AI technologies to the product suite. Key Responsibilities: Lead the AI CoE team, ensuring alignment with business objectives. Oversee the design, development, and deployment of AI/ML models for financial use cases. Work closely with product managers and business stakeholders to understand requirements and deliver actionable AI solutions. Provide guidance and mentorship to junior team members. Manage project timelines, resources, and risk assessments. Collaborate with Data Engineers, AI/ML Engineers, Full Stack Engineers, and QA Engineers to ensure smooth integration of AI solutions. Stay updated with advancements in AI/ML technologies and best practices. Required Experience: 8-12 years of experience in AI/ML technologies, with at least 3 years in a leadership role. Strong background in AI/ML model development and deployment, particularly in the financial services sector. Proficient in Python, R, and other AI-related programming languages. Experience managing cross-functional teams in an Agile environment. Strong understanding of data science, cloud computing, and AI/ML frameworks (e.g., TensorFlow, PyTorch, etc.). Tech Specifics: Programming Languages: Expert-level proficiency in Python (e.g., NumPy, Pandas) and R for AI/ML development; familiarity with Scala is a plus. AI/ML Frameworks: Hands-on experience with TensorFlow, PyTorch, and Scikit-learn for building and optimizing models; exposure to Hugging Face for NLP/Generative AI tasks. MLOps Tools: Strong command of Docker and Kubernetes for containerization, and Jenkins or GitHub Actions for CI/CD pipelines. Cloud Platforms: Deep expertise in AWS (e.g., SageMaker, Lambda), Azure (e.g., Machine Learning Studio), or GCP (e.g., AI Platform, BigQuery) for scalable model deployment. Big Data Technologies: Working knowledge of Apache Spark or Hadoop for processing large financial datasets. Database Skills: Proficiency in SQL and experience with NoSQL databases like MongoDB or Cassandra for data integration. Generative AI: Practical experience with models like GPT, LLaMA, or BERT for applications such as automated reporting or customer chatbots.

reliability Role Summary: The AI/ML Engineers will be responsible for developing, testing, and deploying machine learning models and AI algorithms that can be integrated into the product suite. The ideal candidate will have expertise in integrating large language models (LLMs) with external knowledge bases, fine-tuning model architectures for specific tasks, and optimizing retrieval strategies to improve the accuracy and relevance of generated content. Key Responsibilities: Implement and optimize AI/ML algorithms for product integration. Collaborate with data scientists to deploy models and integrate them with software products. Design scalable solutions for AI/ML applications. Develop automated pipelines for continuous model training and updates. Work with engineering teams to ensure smooth integration and operation of AI models in production. Monitor and troubleshoot AI/ML models to ensure reliability and performance. Required Experience: 4 - 6 years of hands-on experience in machine learning model development and deployment. Hands-on experience in developing and fine-tuning Generative AI models, specifically focusing on Retrieval-Augmented Generation (RAG) systems. Experience with frameworks such as Hugging Face, OpenAI, or other GenAI platforms, along with proficiency in data preprocessing and model evaluation, is required Proficiency in Python, TensorFlow, Keras, PyTorch, or other AI/ML frameworks. Experience with model deployment and monitoring in production environments. Strong problem-solving skills and experience with cloud computing platforms (AWS, GCP, Azure). Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

Role & responsibilities Develop, implement & fine-tune deep learning AI models for wide range of Computer Vision application including object classification, object detection, segmentation, OCR & NLP Perform data annotation using automation script & preprocessing to prepare high-quality datasets for training our in-house deep learning models. Training of AI models with model inference and evaluate model accuracy & performance metrics using frameworks like PyTorch, Tensorflow Collaborate with software engineers to deploy models in production systems, ensuring scalability, reliability and efficiency. Develop APIs using FastAPI or similar frameworks to enable seamless integration and interaction with deployed models Experience in Deep Learning, Computer Vision, NLP with a focus on object classification, detection, segmentation, OCR & text processing. Pytho , C++, Understanding of deep learning frameworks such as Tensorflow, PyTorc,h or Keras Experience with AI model training,hyperparameters tunin,g and evaluation of large-scale datasets. Data Annotation familiarity & preprocessing techniques to prepare datasets for deep learning models. Version control systems like Git Problem-solving skills, communication skills, collaboration skills, team player AI Model deployment & serving, including the use of APIs and frameworks like FastAPI

Job Description Data Scientist and Machine Learning Exp - 4-12 years Location - Hyderabad and Chennai We are seeking a talented and experienced AI & Generative AI Developer to join our team and help us create groundbreaking generative AI models and applications. In this role, you will work closely with our team of data scientists, machine learning engineers, and researchers to develop, implement, and optimize generative LLM and foundational models for various verticals, such as Banking, Retail, Comms, and more. The ideal candidate will have a strong background in artificial intelligence, machine learning, NLP, and deep learning, with a passion for innovation and a drive to push the boundaries of generative AI technologies. Responsibilities Design, develop, and implement cutting-edge generative AI models using state-of-the-art techniques such as General Adversarial Networks (GANs), variational autoencoders (VAEs), and reinforcement learning. Collaborate with cross-functional teams to define project goals, research requirements, and develop innovative solutions. Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques. Stay up-to-date on the latest advancements in generative AI, deep learning, and related fields, and incorporate new techniques and methods into the team's workflow. Develop and maintain clear and concise documentation of generative AI models, processes, and results. Communicate complex concepts and results to both technical and non-technical stakeholders. Provide support and guidance to other team members, and contribute to a positive, collaborative working environment. Lead the development and deployment of large language models (LLMs) and agentic frameworks such as Autogen or CrewAI. Oversee cloud deployments, containerization, and orchestration of AI models to ensure scalability and reliability. Requirements Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Strong background in artificial intelligence, machine learning, NLP, and deep learning, with a focus on generative models. Technical knowledge and hands-on experience with Azure OpenAI, Google Vertex Gen AI, and AWS LLM foundational models, BERT, Transformers, PaLM, Bard, etc. Proficiency in programming languages such as Python, and experience (3 - 6 years) with various Python packages (like TensorFlow, PyTorch, or Keras, etc.). Demonstrated experience with generative AI techniques, including GANs, VAEs, and reinforcement learning. Strong analytical and problem-solving skills, with the ability to quickly understand and adapt to new concepts and technologies. Excellent communication and collaboration skills, with the ability to work effectively both independently and as part of a team. Familiarity with cloud computing platforms such as AWS, Google Cloud, or Azure. Experience with leading LLMs and agentic frameworks such as Autogen or CrewAI. Experience with cloud deployments, containerization, and orchestration of AI models. Show more Show less

Role –Senior Gen AI Engineer Location - Chennai - CKC Mode of Interview - In Person Data - 7th June 2025 (Saturday) Job Description: Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data. Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) Work on tasks involving language modeling, text generation, understanding, and contextual comprehension. Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets. Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS. Integrate AI models with our company's data to enhance and augment existing applications. Role & Responsibility Handle data preprocessing, augmentation, and generation of synthetic data. Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) Develop and Maintaining AI Pipelines Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. Ensure the robustness, efficiency, and scalability of AI systems. Stay updated with the latest advancements in AI and machine learning technologies. Skills & Experience Strong foundation in machine learning, deep learning, and computer science. Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). Experience with natural language processing (NLP) and computer vision is a plus. Ability to work independently and as part of a team. Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. Experience in developing and deploying AI models in production environments. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions Should be able to bring new ideas and innovative solutions to our clients

Overview The Gen AI engineer will be part of a team which designs, builds, and operates the AI services of Siemens Healthineers (SHS). The ideal candidate for this role will have experience with AI services. The role will require the candidate to develop and maintain artificial intelligence systems and applications that help businesses and organizations solve complex problems. The role also requires expertise in machine learning, deep learning, natural language processing, computer vision, and other AI technologies. Task and Responsibilities: Generative AI Engineer is responsible for designing, architecting, and development of AI product/service. The main responsibilities include: Designing, developing, and deploying Azure-based AI solutions, including machine learning models, cognitive services, and data analytics solutions. Collaborating with cross-functional teams, such as data scientists, business analysts, and developers, to design and implement AI solutions that meet business requirements. Building and training machine learning models using Azure Machine Learning, and tuning models for optimal performance. Developing and deploying custom AI models using Azure Cognitive Services, such as speech recognition, language understanding, and computer vision. Creating data pipelines to collect, process, and prepare data for analysis and modeling using Azure data services, such as Azure Data Factory and Azure Databricks. Implementing data analytics solutions using Azure Synapse Analytics or other Azure data services. Deploying and managing Azure services and resources using Azure DevOps or other deployment tools. Monitoring and troubleshooting deployed solutions to ensure optimal performance and reliability. Ensuring compliance with security and regulatory requirements related to AI solutions. Staying up-to-date with the latest Azure AI technologies and industry developments, and sharing knowledge and best practices with the team. Qualifications: Overall 5+ years combined experience in IT and recent 3 years as AI engineer. Bachelor's or master's degree in computer science, information technology, or a related field. Experience in designing, developing, and delivering successful AI Services. Experience with cloud computing technologies, such Azure. Relevant industry certifications, such as Microsoft Certified: Azure AI Engineer, Azure Solution Architect etc. is a plus. Excellent written and verbal communication skills to collaborate with cross-functional teams and communicate technical information to non-technical stakeholders. Technical skills Proficiency in programming languages: You should be proficient in programming language such as Python and R. Experience of Azure AI services: You should have experience with Azure AI services such as Azure Machine Learning, Azure Cognitive Services, and Azure Databricks. Data handling and processing: You should be proficient in data handling and processing techniques such as data cleaning, data normalization, and feature extraction. Knowledge of SQL, NoSQL, and big data technologies such as Hadoop and Spark are also beneficial. Experience with Cloud platform: You should have a good understanding of cloud computing concepts and experience working with Azure services such as containers, Kubernetes, Web Apps, Azure Front Door, CDN, Web Application firewalls etc. DevOps and CI/CD: You should be familiar with DevOps practices and CI/CD pipelines. This includes tools such as Azure DevOps & Git. Security and compliance: You should be aware of security and compliance considerations when building and deploying AI models in the cloud. This includes knowledge of Azure security services, compliance frameworks such as HIPAA and GDPR, and best practices for securing data and applications in the cloud. Machine learning algorithms and frameworks: Knowledge of machine learning algorithms and frameworks such as TensorFlow, Keras, PyTorch, and Scikit-learn is a plus.

Job Title: Data Scientist – Python Location: Bhopal (Onsite) Experience: 1 to 3 Years Employment Type: Full-time About Us: At Brandsmashers Tech , we’re passionate about leveraging data to transform industries and empower decision-making. We work across domains like e-commerce, healthcare, agriculture, and education, delivering scalable, data-driven solutions. Join us and be part of a team shaping the future with technology and insights. Job Summary: We are looking for a Data Scientist proficient in Python to join our analytics and AI team. The ideal candidate will have hands-on experience with data preprocessing, statistical analysis, machine learning, and data visualization. You’ll play a key role in deriving actionable insights from data and developing intelligent solutions that drive business value. Key Responsibilities: Analyze large datasets to discover trends, patterns, and insights. Develop, test, and deploy machine learning models using Python libraries (e.g., scikit-learn, TensorFlow, PyTorch). Perform data cleaning, transformation, and feature engineering. Design and implement predictive models and algorithms. Visualize data insights using tools like Matplotlib, Seaborn, Plotly, or Power BI. Collaborate with cross-functional teams including engineering, product, and marketing to integrate data science solutions. Communicate findings to stakeholders through presentations and reports. Stay updated with latest advancements in data science and machine learning. Required Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related field. 2+ years of hands-on experience in data science or applied machine learning. Strong proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, and Matplotlib. Experience with ML frameworks like TensorFlow, Keras, or PyTorch. Knowledge of SQL and data querying tools. Experience with model deployment is a plus (e.g., using Flask, FastAPI). Excellent problem-solving skills and analytical mindset. Strong communication and collaboration skills. Preferred Qualifications: Experience with cloud platforms (AWS, GCP, or Azure). Knowledge of big data tools (Spark, Hadoop) is a plus. Understanding of MLOps and automated pipelines. Job Types: Full-time, Permanent Pay: ₹20,000.00 - ₹40,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Weekend availability Ability to commute/relocate: Govindpura, Bhopal, Madhya Pradesh: Reliably commute or planning to relocate before starting work (Preferred) Experience: Python: 3 years (Required) Data Engineer: 2 years (Required) Language: English (Preferred) Work Location: In person Expected Start Date: 22/05/2025

About the Role: We are based in Gurgaon and looking for a Senior Computer Vision Engineer to join our team and help our team to improve and create new technologies. You'll work on projects which makes online assessment more secure and cheating proof. If you're a seasoned computer vision expert with a passion for innovation and a track record of delivering impactful solutions, we would be happy to meet you. Role : Senior Computer Vision Engineer Functional Area : AI Educational Qualification: BTech/MS/MTech/PhD in Computer Science/Computer vision/Signal Processing/Deep Learning or equivalent. Should have worked in an academic or professional setting in the field of computer vision/signal processing. Experience: 2-5 years Location : Gurgaon Key Responsibilities: Develop and optimize advanced computer vision algorithms for image and video analysis tasks. Design, implement and train deep learning models for object detection, face processing, activity recognition and other related tasks. Test and refine models and systems based on real-world data and feedback. Evaluate project requirements, plan and manage the roadmap of a project. Present findings and insights in a clear and concise manner to stakeholders. Collaborate and help to integrate and deploy computer vision systems into broader product architecture. Conduct research to stay updated on emerging computer vision technologies and trends. Automate data preprocessing and annotation processes to streamline workflow efficiency. Maintain comprehensive documentation for algorithms, implementations, and evaluations. Mentor junior engineers and provide strategic guidance on project development. Requirements and skills: Proficiency in Python and knowledge of C++, Java and JS is plus. Solid understanding of neural networks, especially convolutional neural networks (CNNs). Knowledge of RCNN’s and vision transformers. Proficient in understanding, designing and implementing deep learning models using frameworks such as TensorFlow, PyTorch and Keras. Understanding of fundamental image processing techniques like image filtering, edge detection, image segmentation and image augmentation. Experience in evaluating computer vision models using relevant metrics and performance indicators. Familiarity with GPU and related technologies which is utilized for improved computational efficiency such as CUDA, CUDNN, tensorRT etc. Familiarity with Python libraries such as OpenCV, NumPy, Pandas and scikit-learn etc. Basic knowledge of linear algebra, calculus, and statistics. Strong critical thinking, analytical, and problem-solving skills Self-motivated, quick learner and strong team player with ability to work with minimal supervision. Mercer, a business of Marsh McLennan (NYSE: MMC), is a global leader in helping clients realize their investment objectives, shape the future of work and enhance health and retirement outcomes for their people. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit mercer.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person. R_288254 Show more Show less

Additional Locations: India-Maharashtra, Pune Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. About the Role: Data Scientist will work with a small team of data scientists developing and deploying Deep Learning models to interpret biologic signals on ambulatory patients to improve patient outcomes. The team has developed a large volume of diverse and accurate data for training and validation and works closely with experts in this domain. Key Responsibilities: Develop models and infrastructure to interpret biologic signals and other business data Validation and documentation of models for production deployment Support production deployment and monitoring of models Publishing research in support of business needs Developing and documenting intellectual property Lead/Support systems investigations and research activities to define and/or understand how systems interface with biological systems. Prepares standard reports/documentation to communicate status and results. Supports FDA/QSR requirements by assisting in the creation of specifications and qualifications. Influences and defines functional, departmental/divisional procedures through involvement with cross-functional engineering initiatives. Demonstrated cross function teamwork in a technically demanding environment Supports system risk management activities, Use/Design FMEA’s, risk/hazard analysis. Mentors engineers in engineering activities/methodologies and domain knowledge. Qualification & Required Skills: Bachelor’s degree in engineering or equivalent (BE, B Tech, MCA, MSc, M Tech) Minimum 10+ years of industry experience. Minimum 5+ years of experience in Analytics with 3+ years of experience in Python Demonstrated cross function teamwork in a technically demanding environment Experience in regulated product development environment, particularly for medical devices, a plus. Highly accountable and responsible. Self-starting, self-motivated, self-directed, and self-sufficient. Familiar with Agile development methodologies. Excellent Communication, presentation and interpersonal skills with proficiency in English (verbal and written). Preferred Qualifications: ECG / PPG device experience Experience with deep learning toolkits (Tensorflow, PyTorch, Keras, etc) Experience with Azure Cloud technologies (Azure Storage, Azure Service Bus, etc) Experience with containerization technologies (Kubernetes, Docker, Helm, etc) Demonstrated use of source control tools (Git) Experience with regulatory validation processes for software as a medical device Requisition ID: 607048 As a leader in medical science for more than 40 years, we are committed to solving the challenges that matter most – united by a deep caring for human life. Our mission to advance science for life is about transforming lives through innovative medical solutions that improve patient lives, create value for our customers, and support our employees and the communities in which we operate. Now more than ever, we have a responsibility to apply those values to everything we do – as a global business and as a global corporate citizen. So, choosing a career with Boston Scientific (NYSE: BSX) isn’t just business, it’s personal. And if you’re a natural problem-solver with the imagination, determination, and spirit to make a meaningful difference to people worldwide, we encourage you to apply and look forward to connecting with you!

Company Overview KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us. Group/Division The Information Technology (IT) group at KLA is involved in every aspect of the global business. IT’s mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence. Job Description/Preferred Qualifications We are seeking for a Data Scientist/ML Engineer with experience in NLP, statistics, and Conversational AI. The ideal candidate is adept at using Statistical Modelling, Machine learning algorithms and Conversational AI. Strong experience using variety of data mining/ Machine Learning methods, using/coding algorithms and running simulations. The right candidate will have a passion for discovering solutions hidden in large data sets and working with business partners to improve business outcomes. Responsibilities for Data Scientist/ML Engineer: Building end-to-end ML systems (Including traditional ML models and Conversational AI) and deploying them to operate at scale. Research and devise innovative statistical models/ML models for data analysis Develop and maintain RAG (Retrieval-Augmented Generation) applications. Implement changes to algorithms to improve AI performance and retrieval techniques. Use predictive modeling to increase and optimize customer service experience and supply chain optimization. Identify patterns in data using statistical modeling, develop custom data models and algorithms to apply to data sets. Work with business partners throughout the organization to find opportunities for using company data to drive solutions. Working with project managers to establish objectives for AI systems. Minimum Qualifications Skills and Qualifications: Bachelor’s degree (or equivalent) in computer science, statistics, applied mathematics, or related discipline Experience solving problems with Conversational AI in a production environment for a High-tech Manufacturing Industry 4+ years of experience in Python and ML packages (NumPy, Keras, Seaborn, Scikit-learn). Excellent understanding of machine learning techniques and algorithms such as, Regression models, kNN, SVM,NB, Decision Trees. Expertise/Familiarity with one or more deep learning frameworks such as TensorFlow, PyTorch. We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees. KLA is proud to be an equal opportunity employer Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched KLA’s Careers website for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to talent.acquisition@kla.com to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information. Show more Show less

Your Team Responsibilities AI and Data Engineering Team ResponsibilitiesDevelopment of Scalable and Efficient AI-Driven Solutions Create AI solutions that address complex business challenges. Ensure solutions are scalable to handle large data volumes and efficient in performance. Development and Maintenance of Derived Data Platforms Build and sustain platforms that generate and manage derived data. Integrate data from various sources, maintain data accuracy, and ensure reliability. Development of Data Science-Based Solutions for Quality Check of Data Points Ensure the accuracy and reliability of data through advanced data science techniques. Implement metrics, detect anomalies, and validate data points to maintain high data quality. Your Key Responsibilities2. Development and Maintenance of Derived Data Platforms3. Development of Data Science-Based Solutions for Quality Check of Data Points Development of Scalable and Efficient AI-Driven Solutions Create AI/ML solutions that address complex business challenges. Understand business use cases and identify where AI can add value. Design, train, and validate machine learning models tailored to specific business needs. Leverage LLMs to build solutions solving business problems Ensure solutions can handle large volumes of data and scale with business growth. Optimize models and algorithms for performance and resource utilization. Build and sustain platforms that generate and manage derived data for MSCI. Development of new calculations to be added to exisitng derived data platform. Regularly update and maintain the platforms to ensure data accuracy and reliability. Implement checks to maintain high data quality. Ensure the accuracy and reliability of data through advanced data science techniques. Define and implement metrics to assess data quality. Develop models to detect anomalies and inconsistencies in data. Create automated processes to validate data points against predefined standards. Continuously refine quality check methods based on feedback and new insights. Your Skills And Experience That Will Help You Excel Artificial Intelligence (AI) and Machine Learning (ML) Understanding of machine learning algorithms, deep learning, neural networks, and reinforcement learning. Understanding and experience on Generative AI. Proficiency in working with large language models like GPT, BERT, and their variants. Experience in fine-tuning and deploying these models for various applications. Familiarity with frameworks like TensorFlow, PyTorch, and Keras. Programming Languages Python: Proficiency in Python for data manipulation, model development, and automation. Experience with libraries such as NumPy, pandas, scikit-learn, and matplotlib. Java: Strong skills in Java for building scalable and efficient applications. Knowledge of Java frameworks like Spring. Oracle: Expertise in Oracle databases, including SQL and PL/SQL. Experience in database design, optimization, and management. About MSCI What we offer you Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing. Flexible working arrangements, advanced technology, and collaborative workspaces. A culture of high performance and innovation where we experiment with new ideas and take responsibility for achieving results. A global network of talented colleagues, who inspire, support, and share their expertise to innovate and deliver for our clients. Global Orientation program to kickstart your journey, followed by access to our Learning@MSCI platform, LinkedIn Learning Pro and tailored learning opportunities for ongoing skills development. Multi-directional career paths that offer professional growth and development through new challenges, internal mobility and expanded roles. We actively nurture an environment that builds a sense of inclusion belonging and connection, including eight Employee Resource Groups. All Abilities, Asian Support Network, Black Leadership Network, Climate Action Network, Hola! MSCI, Pride & Allies, Women in Tech, and Women’s Leadership Forum. At MSCI we are passionate about what we do, and we are inspired by our purpose – to power better investment decisions. You’ll be part of an industry-leading network of creative, curious, and entrepreneurial pioneers. This is a space where you can challenge yourself, set new standards and perform beyond expectations for yourself, our clients, and our industry. MSCI is a leading provider of critical decision support tools and services for the global investment community. With over 50 years of expertise in research, data, and technology, we power better investment decisions by enabling clients to understand and analyze key drivers of risk and return and confidently build more effective portfolios. We create industry-leading research-enhanced solutions that clients use to gain insight into and improve transparency across the investment process. MSCI Inc. is an equal opportunity employer. It is the policy of the firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, gender, gender identity, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy (including unlawful discrimination on the basis of a legally protected parental leave), veteran status, or any other characteristic protected by law. MSCI is also committed to working with and providing reasonable accommodations to individuals with disabilities. If you are an individual with a disability and would like to request a reasonable accommodation for any part of the application process, please email Disability.Assistance@msci.com and indicate the specifics of the assistance needed. Please note, this e-mail is intended only for individuals who are requesting a reasonable workplace accommodation; it is not intended for other inquiries. To all recruitment agencies MSCI does not accept unsolicited CVs/Resumes. Please do not forward CVs/Resumes to any MSCI employee, location, or website. MSCI is not responsible for any fees related to unsolicited CVs/Resumes. Note on recruitment scams We are aware of recruitment scams where fraudsters impersonating MSCI personnel may try and elicit personal information from job seekers. Read our full note on careers.msci.com Show more Show less

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Manager- Data Science Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Our Team As consumer preference for digital payments continues to grow, ensuring a seamless and secure consumer experience is top of mind. Optimization Solutions team focuses on tracking of digital performance across all products and regions, understanding the factors influencing performance and the broader industry landscape. This includes delivering data-driven insights and business recommendations, engaging directly with key external stakeholders on implementing optimization solutions (new and existing), and partnering across the organization to drive alignment and ensure action is taken. Are you excited about Data Assets and the value they bring to an organization? Are you an evangelist for data-driven decision-making? Are you motivated to be part of a team that builds large-scale Analytical Capabilities supporting end users across 6 continents? Do you want to be the go-to resource for data science & analytics in the company? The Role Work closely with global optimization solutions team to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support data insights and analytical needs across products, markets, and services The candidate for this position will focus on Building solutions using Machine Learning and creating actionable insights to support product optimization and sales enablement. Prototype new algorithms, experiment, evaluate and deliver actionable insights. Drive the evolution of products with an impact focused on data science and engineering. Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Perform data ingestion, aggregation, and processing on high volume and high dimensionality data to drive and enable data unification and produce relevant insights. Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations. Apply knowledge of metrics, measurements, and benchmarking to complex and demanding solutions. Role Ensure that all AI solutions follow industry standards for data management and privacy, covering aspects like data collection, use, storage, access, retention, output, reporting, and quality at Mastercard. Take a practical approach to AI, simplifying complex technical requirements to align with stakeholders' needs. Collaborate with global stakeholders to gather necessary information and define business problems. Think creatively to link AI methodologies with real business challenges. Identify common use case patterns to promote scalable AI through reusable models and a microservice approach. Build AI/ML solutions using the latest advancements from industry and academia. Use both open and proprietary technologies to address business problems. Work effectively across teams and geographies, leveraging broader team expertise to achieve AI goals. Partner with technical teams to deploy solutions in production environments. Foster a culture of learning and continuous improvement in AI capabilities. All About You 8+ years in Data Science, with a focus on AI strategy, execution, and solution development from the ground up. A passion for AI, demonstrated through participation in competitions such as Kaggle. Preferred experience or familiarity with cybersecurity, fraud, and risk solutions, including: Deep learning algorithms, open-source tools, and statistical environments (Python, R, SQL). Big data platforms like Hadoop, Hive, Spark, and GPU clusters for deep learning. Classical machine learning techniques such as Logistic Regression, Decision Trees, K-Means, PCA, and Time Series models (ARIMA/ARMA). Deep learning techniques including Random Forest, GBM, Neural Networks (CNNs, LSTMs), and optimization techniques (Adam, Adagrad, etc.). Frameworks like TensorFlow, Keras, PyTorch, and XGBoost for production systems. Experience or exposure to collaboration tools like Confluence, Bitbucket, ALM, etc. Knowledge of the payments industry and experience with SAFe (Scaled Agile Framework) is a plus. Effectiveness Ability to manage assumptions and validate them with key stakeholders under tight deadlines, while keeping development on track. Strong problem-solving skills, with the ability to break down complex issues and apply the right AI techniques to solve them. Deep attention to detail, ensuring high confidence in developed solutions. Strong understanding of technical system architecture and interdependencies, anticipating challenges and proactively solving them. Core Capabilities Excellent written and verbal communication skills. Strong project management experience. Background in Computer Science. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-245889 Show more Show less

Job Title: Python FullStack Developer Experience: 5+ years Location: Hyderabad (Hybrid)/Remote Required Skillset: Proven experience as a Full Stack Developer with a strong portfolio of web applications. Proficiency in Python programming language and its web frameworks such as Django or Flask. Solid understanding of front-end technologies, including HTML, CSS, JavaScript, and modern frameworks/libraries (e.g., React.js, Angular, Vue.js). Experience in implementing data storage solutions using SQL (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Redis). Knowledge of REST APIs and strong experience in building and consuming APIs. Experience on version control systems (e.g., Git), CI/CD pipelines, and DevOps practices. Experience in deploying applications on cloud platforms (e.g., AWS, Azure, Google Cloud). Experience in Azure AD authentication, and other Azure services. Experience in test-driven development using testing frameworks/tools (e.g., Pytest, Jest). Strong problem-solving skills, attention to detail, and ability to work in a fast-paced environment. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams. Experience working in projects Agile/Scrum methodologies. Preferred Skillset (Not Mandatory, but good to have): Experience working in Azure Cloud platform (e.g., Azure Data Factory, Azure Data Bricks, Azure SQL, Azure Data Lake etc.). Experience of working in the Data Science domain using Python libraries like Scikit-learn, NumPy, Pandas, TensorFlow, Keras etc. Knowledge on Big data technologies such as Hadoop, Spark. Experience with at least one visualization tool like Power BI, Tableau. Show more Show less

Thiruvananthapuram Office, AEDGE AICC India Pvt Ltd About the Company Armada is an edge computing startup that provides computing infrastructure to remote areas where connectivity and cloud infrastructure is limited, as well as areas where data needs to be processed locally for real-time analytics and AI at the edge. We’re looking to bring on the most brilliant minds to help further our mission of bridging the digital divide with advanced technology infrastructure that can be rapidly deployed anywhere . About the Role We are seeking a highly motivated Senior Data Engineer to join our Data Platform team for our Edge Computing AI Platform. As a Data Engineer in our Data Platform team, you will be responsible for helping us shape the future of data ingestion, processing, and analysis, while maintaining and improving existing data systems. If you are a highly motivated individual with a passion for cutting-edge AI, cloud, edge, and infrastructure technology and are ready to take on the challenge of defining and delivering a new computing and AI platform, we would love to hear from you. Location. This role is office-based at our Trivandrum, Kerala office. What You'll Do (Key Responsibilities) Build new tools and services that support other teams’ data workflows, ingestion, processing, and distribution. Design, discuss, propose, and implement to our existing data tooling and services. Collaborate with a diverse group of people, giving and receiving feedback for growth. Execute on big opportunities and contribute to building a company culture rising to the top of the AI and Edge Computing industry. Required Qualifications 6+ years of experience in software development. Experience with data modeling, ETL/ELT processes, streaming data pipelines. Familiarity with data warehousing technologies like Databricks/Snowflake/BigQuery/Redshift and data processing platforms like Spark; working with data warehousing file formats like Avro and Parquet. Strong understanding of Storage (Object Stores, Data Virtualization) and Compute (Spark on K8S, Databricks, AWS EMR and the like) architectures used by data stack solutions and platforms. Experience with scheduler tooling like Airflow. Experience with version control systems like Git and working using a standardized git flow. Strong analytical and problem-solving skills, with the ability to work independently and collaboratively in a team environment. Professional experience developing data-heavy platforms and/or APIs. A strong understanding of distributed systems and how architectural decisions affect performance and maintainability. Bachelor’s degree in computer science, Electrical Engineering, or related field. Preferred Qualifications Experience analyzing ML algorithms that could be used to solve a given problem and ranking them by their success probability. Proficiency with a deep learning framework such as TensorFlow or Keras. Understanding of MLOps practices and practical experience with platforms like Kubeflow / Sagemaker. Compensation & Benefits For India-based candidates: We offer a competitive base salary along with equity options, providing an opportunity to share in the success and growth of Armada. #LI-JV1 #LI-Onsite You're a Great Fit if You're A go-getter with a growth mindset. You're intellectually curious, have strong business acumen, and actively seek opportunities to build relevant skills and knowledge A detail-oriented problem-solver. You can independently gather information, solve problems efficiently, and deliver results with a "get-it-done" attitude Thrive in a fast-paced environment. You're energized by an entrepreneurial spirit, capable of working quickly, and excited to contribute to a growing company A collaborative team player. You focus on business success and are motivated by team accomplishment vs personal agenda Highly organized and results-driven. Strong prioritization skills and a dedicated work ethic are essential for you Equal Opportunity Statement At Armada, we are committed to fostering a work environment where everyone is given equal opportunities to thrive. As an equal opportunity employer, we strictly prohibit discrimination or harassment based on race, color, gender, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law. This policy applies to all employment decisions, including hiring, promotions, and compensation. Our hiring is guided by qualifications, merit, and the business needs at the time.

Role Description Who we are: At UST, we help the world’s best organizations grow and succeed through transformation. Bringing together the right talent, tools, and ideas, we work with our client to co-create lasting change. Together, with over 26,000 employees in 25 countries, we build for boundless impact—touching billions of lives in the process. Visit us at . You Are We are looking for experienced candidate with around one or two year experience in an artificial intelligence engineer to join the revolution, using deep learning, neuro-linguistic programming (NLP), chatbots and generative models to help us improve various business outcomes and drive innovation. The engineer will join a multidisciplinary team helping to shape our AI strategy and showcasing the potential for AI through early-stage solutions. Therefore, it’s essential that you are skilled at problem solving, solution design, and high-quality coding. The Opportunity Engage in research activities to explore the latest advancements in generative AI techniques and algorithms. Stay updated with current literature and emerging trends in the field. Develop AI/ML applications according to requirements. Select appropriate datasets and data representation methods. Run machine learning tests and experiments. Perform statistical analysis and fine-tuning using test results. Train and retrain systems when necessary. Extend existing AI/ML libraries and frameworks What You Need Bachelor’s in computer science or related field. 1 or 2 year experience in n applying AI/ML preferably using TensorFlow or PyTorch Framework Understanding of data structures, data modeling and software architecture Strong understanding of machine learning fundamentals including deep learning, neural networks, and generative models. Ability to write robust code in Python. Familiarity with machine learning frameworks (Keras, deep learning, TensorFlow, PyTorch, NLP Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), or Transformer-based models.) Strong programming skills in at least one of the following: Python, C++ will be added advantage. Outstanding analytical and problem-solving skills Experience with continuous integration practices ,ML model validation metrics and developing tools in windows environment will be an added advantage. What We Believe We’re proud to embrace the same values that have shaped UST since the beginning. Since day one, we’ve been building enduring relationships and a culture of integrity. And today, it's those same values that are inspiring us to encourage innovation from everyone, to champion diversity and inclusion and to place people at the center of everything we do. Humility We will listen, learn, be empathetic and help selflessly in our interactions with everyone. Humanity Through business, we will better the lives of those less fortunate than ourselves. Integrity We honor our commitments and act with responsibility in all our relationships Equal Employment Opportunity Statement UST is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion or sexual orientation. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. UST reserves the right to periodically redefine your roles and responsibilities based on the requirements of the organization and/or your performance. To support and promote the values of UST. Comply with all Company policies and procedures Skills Nlp,Artificial Intelligence,Machine Learning,Python Show more Show less

About us We are a global technology company, driving energy innovation for a balanced planet.​ Together, we create amazing technology that unlocks access to energy for the benefit of all.​ Our inclusive culture is the key to our success. We collaborate with our internal community of colleagues, alumni, and our valued external partners to support each other and achieve our goals. We aim to raise the bar high. We look for people who are committed to innovation and success and act with integrity to become and be a part of one of the most diverse group of experts in our industry, anywhere around the globe. Global in outlook, local in practice – and with a united, shared passion for discovering solutions, we hire talented, driven people and support them to succeed, personally and professionally. Job Description Job Title: Data Scientist Location: PuTC, Pune Job Summary: We are looking for data scientists to join the PuTC Data Science team. The Data Scientists will be responsible for designing and executing undirected research and tackling open-ended data problems related to oil and gas domain using advanced techniques in AI (Artificial Intelligence), ML (Machine learning), DL (deep learning) etc. The data scientists will be working with very complex and large data sets. The individual will be responsible for collaborating with various cross functional teams and providing periodic updates through presentations and prototype demonstrations. The role will require working on multiple projects simultaneously. Responsibilities Assimilate next-generation technologies for data-driven solutions in oil and gas domain Generate innovative ideas, establish new research directions, and shape and execute on research projects Apply engineering knowledge in developing data-driven algorithms and prototypes for classification, regression, anomaly detection, failure prediction, and optimization Collaborate with business and engineering teams to implement robust and scalable industrial software solutions Contribute to technical discussions and undertake reviews of different projects as an expert Communicate ideas, plans, and results effectively to different stake holders Participate in technical forums and other appropriate events and conferences Qualifications and Requirements M.S/MTech/PhD in computer science, mathematics, physics, applied sciences, engineering or similar disciplines with demonstrated capability in field of algorithm development using General AI, Generative AI with 3-5 years of experience, Deep understanding of Generative AI, deep learning algorithms and their applications to text analytics/NLP, computer vision etc Strong background in retrieval augmented generation (RAG), agentic frameworks, etc. would be preferred. Strong background in linear algebra, statistics, and probability Strong background in Python programming Hand-on experience in developing deep learning models using TensorFlow, Keras, Pytorch, etc. will be a plus Experience in patents or publications at top-tier peer-reviewed conferences or journals SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law. Show more Show less

Position Title: Data Scientist Company Overview: Capgemini Engineering is a global leader in engineering services, bringing together a worldwide team of engineers, scientists, and architects to assist the most innovative companies in unleashing their potential. Position Overview: We are seeking a skilled Data Scientist with expertise in Cognite Data Fusion, data modelling, Unified Namespace (UNS), ontologies, and the identification of data products and datasets. The ideal candidate will have a strong background in developing and implementing data science projects, analyzing large and complex data sets, and driving data-driven decision-making across the organization Key Responsibilities: Solution Development: Design, implement, and deploy scalable data solutions utilizing Cognite Data Fusion, focusing on data modeling, UNS, and ontologies to address industry-specific challenges.​ Data Analysis: Analyze large and complex data sets to identify trends, insights, and opportunities, supporting solution development and business strategies.​ Collaboration: Collaborate with cross-functional teams to understand data needs and translate them into data science solutions, ensuring seamless integration and operationalization of digital solutions across various domains. Client Engagement: Engage with clients to understand their business objectives, lead discovery workshops, and provide expert guidance on data-driven strategies and potential challenges.​ Visualization: Develop dashboards and visualizations using tools such as Power BI, Grafana, or web development frameworks like Plotly Dash and Streamlit to effectively communicate data insights.​ Mentorship: Provide guidance and mentorship to junior team members, promoting best practices in data science and software development.​ Qualifications: Educational Background: Master’s or PhD degree in a quantitative field.​ Experience: Minimum of 2 years of experience in data science, with a strong background in developing analytical solutions within domains such as pharma, oil and gas, manufacturing, or power & utilities.​ Technical Skills: Proficiency in Python and its data ecosystem (pandas, numpy), machine learning libraries (scikit-learn, keras), and experience with SQL.​ Visualization Tools: Experience with data visualization tools like Power BI, Grafana, Tableau, or web development frameworks such as Plotly Dash and Streamlit.​ Software Practices: Strong understanding of software development practices, including version control (e.g., Git), automated testing, and documentation.​ Cloud Platforms: Experience with cloud services such as GCP, Azure, or AWS is advantageous.​ Domain Knowledge: Familiarity with industrial data management concepts, including Unified Namespace (UNS), ontologies, and data product identification.​ Communication Skills: Excellent communication and collaboration skills, with the ability to work with cross-functional teams and stakeholders.​ Leadership: Demonstrated ability to lead projects and mentor junior team members.​ Preferred Qualifications: Industry Expertise: Experience serving as a domain expert on internal or customer projects within relevant industries.​ Cloud Deployment: Experience deploying models and solutions in production environments using cloud infrastructure.​ Continuous Learning: Willingness to stay updated with the latest developments in data science and related technologies.​ Show more Show less

Position: Machine Learning Intern (Full-Time) Company: Lead India Location: Remote Stipend: ₹25,000/month Duration: 1–3 months (Full-Time Internship) About Lead India: Lead India is a technology-driven company leveraging AI and data to create intelligent, real-world solutions. We provide aspiring developers and analysts with remote opportunities to gain hands-on experience in machine learning and artificial intelligence. Role Overview: We are looking for a Machine Learning Intern to join our data science team. This internship is a great fit for individuals with a solid foundation in ML concepts and Python, and a passion for building intelligent systems using real-world data. Key Responsibilities: Assist in building, training, and evaluating machine learning models Conduct data preprocessing and feature engineering Experiment with model tuning and validation techniques Work with libraries like scikit-learn, TensorFlow, or PyTorch Analyze performance metrics and help improve accuracy Document workflows, results, and present findings to the team Skills We're Looking For: Proficiency in Python and libraries such as pandas, NumPy, scikit-learn Understanding of supervised and unsupervised learning techniques Experience with basic data preprocessing and visualization Familiarity with TensorFlow, Keras, or PyTorch is a plus Analytical thinking, curiosity, and a willingness to learn What You’ll Gain: ₹25,000/month stipend Experience on real-world machine learning projects Mentorship from experienced ML professionals Fully remote and flexible working environment Opportunity for a Pre-Placement Offer (PPO) based on performance Show more Show less

Position Title: AWS AI Engineer Job Timings: 8am-5pm CST (Central Time, US) Location: Remote, India About Cloudelligent Cloudelligent is Cloud-native consultancy and AWS Advanced consulting partner! We specialize in providing bespoke cloud solutions to the SMB & enterprise segments as well as the public sector (Non-Profit Organizations). Being a next-gen cloud service provider, Cloudelligent helps small businesses & medium/large enterprises to break free from hardware lifecycle and capital expenditures, allowing them to make the most out of their cloud investment. We have an international footprint with a diverse team of domain experts, and we are customer obsessed. Job Objective As an AI Engineer at Cloudelligent, you will drive the development of innovative artificial intelligence solutions. This role emphasizes the implementation, optimization, and deployment of AI models while collaborating with cross-functional teams to enhance our products and services. The ideal candidate will possess a strong foundation in both machine learning and deep learning. Responsibilities: Implement and fine-tune pre-trained AI models tailored to meet specific industry needs. Utilize cloud-based AI services, particularly AWS Bedrock, Amazon SageMaker, Amazon Rekognition, and OpenAI, to streamline development and deployment processes. Leverage AWS data services, including Amazon Athena, Amazon Redshift, OpenSearch, Kendra and AWS Glue, for efficient data processing and analysis. Optimize AI models for performance, accuracy, and efficiency, ensuring they meet real-world requirements. Apply techniques to reduce AI hallucination and enhance model reliability. Utilize Retrieval-Augmented Generation (RAG) techniques to improve AI response quality. Work with vector databases, specifically PostgreSQL with pgvector, for efficient similarity search and information retrieval in AI applications. Collaborate with cross-functional teams to seamlessly integrate AI capabilities into our products and services. Engage in prompt engineering to enhance model interaction and output quality. Stay updated on the latest trends and advancements in AI technologies, contributing to the adoption of new tools and techniques. Requirements: Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field. 4+ years of hands-on experience in AI/ML development. Strong programming skills, particularly in Python, and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or Keras. Experience with cloud-based AI services, especially AWS Bedrock, Amazon SageMaker, and Azure OpenAI. Familiarity with AWS data services, including Amazon Athena, Amazon Redshift, and AWS Glue. Knowledge of Agentic Behavior in AI, with experience in deploying models using CrewAI, LangGraph, and Langchain. Familiarity with vector databases and similarity search techniques. Solid understanding of various AI/ML algorithms and architectures, including but not limited to CNNs, RNNs, and transformers. Experience in data preprocessing, feature engineering, and model evaluation. Excellent problem-solving and communication skills. Good to Have: Experience with machine learning frameworks and libraries like TensorFlow, PyTorch, or Scikit-learn. Knowledge of big data technologies such as Apache Spark or Hadoop. Familiarity with data visualization tools and techniques. Highly Desirable: Relevant certifications (e.g., AWS Certified Machine Learning – Specialty). Show more Show less

Job Title - Data Engineer Sr.Analyst ACS SONG Management Level: Level 10 Sr. Analyst Location: Kochi, Coimbatore, Trivandrum Must have skills: Python/Scala, Pyspark/Pytorch Good to have skills: Redshift Job Summary You’ll capture user requirements and translate them into business and digitally enabled solutions across a range of industries. Your responsibilities will include: Roles And Responsibilities Designing, developing, optimizing, and maintaining data pipelines that adhere to ETL principles and business goals Solving complex data problems to deliver insights that helps our business to achieve their goals. Source data (structured→ unstructured) from various touchpoints, format and organize them into an analyzable format. Creating data products for analytics team members to improve productivity Calling of AI services like vision, translation etc. to generate an outcome that can be used in further steps along the pipeline. Fostering a culture of sharing, re-use, design and operational efficiency of data and analytical solutions Preparing data to create a unified database and build tracking solutions ensuring data quality Create Production grade analytical assets deployed using the guiding principles of CI/CD. Professional And Technical Skills Expert in Python, Scala, Pyspark, Pytorch, Javascript (any 2 at least) Extensive experience in data analysis (Big data- Apache Spark environments), data libraries (e.g. Pandas, SciPy, Tensorflow, Keras etc.), and SQL. 2-3 years of hands-on experience working on these technologies. Experience in one of the many BI tools such as Tableau, Power BI, Looker. Good working knowledge of key concepts in data analytics, such as dimensional modeling, ETL, reporting/dashboarding, data governance, dealing with structured and unstructured data, and corresponding infrastructure needs. Worked extensively in Microsoft Azure (ADF, Function Apps, ADLS, Azure SQL), AWS (Lambda,Glue,S3), Databricks analytical platforms/tools, Snowflake Cloud Datawarehouse. Additional Information Experience working in cloud Data warehouses like Redshift or Synapse Certification in any one of the following or equivalent AWS- AWS certified data Analytics- Speciality Azure- Microsoft certified Azure Data Scientist Associate Snowflake- Snowpro core- Data Engineer Databricks Data Engineering About Our Company | Accenture (do not remove the hyperlink) Experience: 3.5 -5 years of experience is required Educational Qualification: Graduation (Accurate educational details should capture) Show more Show less