1443 Generative Ai Jobs - Page 30

Responsibilities: * Develop ML models using Python, TensorFlow & PyTorch. * Implement NLP techniques with focus on natural language understanding. * Collaborate with cross-functional teams on CV projects.

Title : ML Engineer Location : Chennai Working mode : Hybrid (3days WFO) Exp:2-10 Years Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

Role - L2 Application Support - AI Platform JOB RESPONSIBILITIES Below are key role and responsibilities for this position: Resolve business /functional issues which couldnt be resolved by L1 team Interact with L1 and keep run-books and Standard support operational procedures(SOP) up-to-date Perform Ad-hoc support tasks and prepare reports for business Troubleshoot all the new incidents/issues for which knowledge base is not available and escalated by L1 team Resolve the incidents/issues and service requests as per agreed SLA Follow the escalation process to escalate to L3 team or next level of support as per escalation metric if unable to resolve the issue within agreed time window Prepare the Incident post-mortem / RCA(Root cause analysis) report of incidents and share it with all the stakeholders within agreed timeline Perform the shift handover activities as per agreed SOPs Participate in problem management, change management, knowledge management, even management etc. Update knowledge base with new learnings, changes in resolution steps etc. in timely manner Ensure SLA/KPI (under control of L2 team like incident response time are met and collect/update data of it in required tools Help shift/team lead to prepare to various operational reports required by internal and external stakeholders Contribute to support reusable assets and internal knowledge sharing sessions Work to build-up skills for L3 support level Work on POC of different solutions, tools etc. POC Coordinate with L1 and L3 engineers (as per case requirement) on various issues, incidents, service requests, user queries, various changes in environment, various events etc. Work on automation of manual activities if possible and share the details of automation opportunities with L3 team Personal Attributes: Systematic problem-solving approach, coupled with effective communication skills and a sense of drive Flexible and proactive/self-motivated working style with strong personal ownership of problem resolution Should be flexible to work in all shifts Ability to prioritize when under pressure Excellent verbal and written communication skills. SKILL REQUIREMENTS Must Skills 6+ years of industry experience in the field of Application / Infrastructure Support and Maintenance Understanding of different Natural Language Processing Concepts Understanding of AI / ML, Deep learning, Generative AI , LLMs and Frameworks like Langchain , Llamaindex Experience with Python, Node JS and React programming languages. Knowledge of SQL and experience with relational databases. Have good understanding of Google Cloud Platform and Google Kubernetes Engine Have understanding of how cloud infrastructure is setup, applications are deployed, various services are setup and used etc. Good understanding of containerization and image management. Experience in working with development teams to containerize applications using Docker and ensure smooth deployment. Familiarity with DevOps and CI/CD pipelines (e.g., Jenkins, Cloud Build, or GitLab CI/CD). Knowledge of tools like Terraform or Ansible to automate infrastructure provisioning and management. Have good exposure of ITIL Processes like Incident Management, Problem Management, and Knowledge Management etc. Excellent communication and documentation skills. Strong problem-solving and analytical skills. Open to work in a 24X7 shift. Have good knowledge of Ticketing Tools like ServiceNow, Jira Servicedesk, Remedy etc. Have good level of production issues troubleshooting and analysis covering : Environment setup understanding Process level debugging & server-side troubleshooting Server configurations Have ability to demonstrate functional and technical architecture knowledge and correlate between the two from past experiences. Note : Only Immediate Joiners are preferred for this role.

Note: Please do not apply if you are not interested for Contract based work. Job Title: Data Scientist Contract Position About the Role: We are looking for a skilled and passionate Data Scientist who brings hands-on expertise in Python programming, Azure ecosystem, and Generative AI (GenAI) to help us design, build, and scale intelligent, AI-powered solutions. The ideal candidate will have deep experience with NLP, Computer Vision (CV), LLMs, FastAPI, vector databases, and modern machine learning pipelines. Key Responsibilities: Design and implement AI/ML models for solving real-world business problems using Python and Azure ML. Develop and deploy RAG-based solutions integrating embedding techniques, chunking, and retrieval strategies. Work on OpenAI/GenAI-based models and fine-tune for specific enterprise use cases. Build and consume REST APIs using FastAPI or Django. Leverage Azure Form Recognizer for intelligent document processing. Implement CI/CD pipelines for model deployment and automation. Work with NoSQL and Vector Databases to store and retrieve high-dimensional data. Collaborate with cross-functional teams to build scalable and robust ML pipelines. Apply Deep Learning and NLP/CV techniques to enhance product features. Primary Skills Required: Strong expertise in Python programming Experience with Azure Services (e.g., Azure ML, Azure Functions, Form Recognizer) Hands-on with FastAPI, Django framework Good understanding of CI/CD pipelines Proficiency in GenAI and OpenAI models Expertise in NLP, Computer Vision, Machine Learning, and Deep Learning Familiarity with NoSQL Databases (e.g., MongoDB, Cosmos DB) Experience with Vector Databases (e.g., FAISS, Pinecone, Qdrant) Knowledge of embedding & chunking techniques Experience in building RAG (Retrieval-Augmented Generation) based solutions Strong grasp of retrieval methods and information retrieval

Job description AlgoAnalytics is looking for a Data Scientist who has the passion for AI/ML solution development and cutting-edge work in Gen AI. Minimum 3 years of experience in AI/MI including Deep Learning, and exposure to Gen AI/LLM is required along with tools/techs/libraries like Agentic AI, Dify/Autogen, Langraphetc. Detailed understanding of Cloud technologies and Deployment with good hands-on experience is an added advantage. Key Responsibilities: AI/ML & Gen AI Development: Develop Gen AI/LLM models using OpenAI, Llama, or other open-source/offline models. Utilize Agentic AI frameworks and tools like Dify, Autogen, Langraph to build intelligent systems. Perform prompt engineering, fine-tuning, and dataset-specific model optimization. Implement cutting-edge research from AI/ML and Gen AI domains. Work on cloud-based deployments of AI/ML models for scalability and production readiness. Leadership & Mentoring: Troubleshoot AI/ML, Gen AI, and cloud deployment challenges. Mentor junior team members and contribute to their skill development. Identify team members for mentoring, hiring, and technical initiatives. Ensure smooth project execution, deadline management, and client interactions. Research & Innovation: Explore and implement recent AI/ML research in practical applications. Contribute to research publications, internal knowledge-sharing, and AI innovation. Qualifications: 2-3 years of hands-on experience in Machine Learning, Deep Learning, and Gen AI/LLMs. Bachelors/Masters degree in Computer Science, Engineering, Mathematics, or Statistics (with strong programming knowledge). Skills: Programming: Strong expertise in Python and relevant ML/AI libraries. AI/ML & Gen AI: Deep understanding of Machine Learning, Deep Learning, and Generative AI/LLMs. Agentic AI & Automation: Experience with Dify, Autogen, Langraph, and similar tools. Cloud & Deployment: Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps deployment pipelines. Communication & Leadership: Strong ability to manage teams, meet project deadlines, and collaborate with clients. Note - We would prefer Pune based candidates. Candidates joining immediately will be prefered.

Location: Hyderabad/Bangalore Department: Advanced Analytics & AI Solutions About the Role We are seeking a highly skilled Senior Data Scientist to lead the end-to-end design, enhancement, and deployment of a machine learning solution that predicts the virality of press articles. This role is part of a high-impact digital media analytics project designed to support brand reputation management by forecasting which headlines are likely to gain rapid traction. The ideal candidate brings deep expertise in natural language processing (NLP), deep learning (especially transformer models like BERT), and hands-on experience with Azure AI services. You will drive the evolution of a proof-of-concept Python model into a scalable, production-grade Azure-based solution integrated with downstream generative AI interfaces. Key Responsibilities Lead the development and optimization of a BERT-based pairwise comparison model for predicting press article virality. Incorporate temporal dynamics into modeling strategy to enhance prediction accuracy over time. Design and implement scalable ML pipelines using Azure AI Hub, Foundry, Blob Storage, and Cosmos DB. Collaborate with architecture and platform teams to ensure smooth lift-and-shift deployment of the solution into client environments. Integrate outputs with Azure OpenAI (GPT-4o) to build conversational interfaces via Microsoft Copilot Studio or Power Apps. Evaluate model performance using robust metrics (accuracy, AUC-ROC, ranking correlation). Manage compute budgets (under $1,000/month) through cost-efficient compute planning and Azure monitoring tools. Work closely with stakeholders to translate business requirements into ML model specifications and insights delivery. Stay up-to-date with advances in NLP, ranking models, and Azure ML ecosystem. Required Skills & Experience 610 years of experience in Data Science or Machine Learning, with a strong focus on NLP or content-based recommendation systems. Deep proficiency in Python, with expertise in transformers, PyTorch/TensorFlow, Hugging Face, and data science libraries (pandas, scikit-learn). Hands-on experience with BERT, pairwise learning, and ranking models. Prior exposure to temporal modeling techniques (e.g., sliding windows, time-based feature engineering). Strong experience with the Azure ecosystem, including: Azure AI Hub and Foundry Azure Machine Learning Azure OpenAI Azure Cosmos DB and Blob Storage Azure Monitor and Application Insights Experience designing or integrating generative AI solutions (e.g., GPT-4, Claude, Gemini). Familiarity with CRISP-DM methodology or other structured data science lifecycles. Preferred Qualifications Experience working with media or digital marketing datasets (clickstream, headlines, user interactions). Knowledge of semantic search or vector databases. Understanding of Copilot/Chatbot development on Microsoft platforms. Experience managing data science projects with budget constraints and deployment pipelines. Published research or prototypes in NLP or content virality modeling is a strong plus.

Gen AI Specialist Exp: 10+ Yrs Location: Bengaluru We are seeking a visionary and driven leader to spearhead our organization's transformative journey into the world of Generative AI. This individual will play a pivotal role in building and scaling our Gen AI capabilities, fostering a culture of innovation, and driving tangible productivity gains across all departments. The ideal candidate is a passionate advocate for AI with a proven track record of successfully implementing and scaling AI/ML initiatives within an enterprise setting. Responsibilities: Develop and Implement Gen AI Strategy: Identify key opportunities and use cases for Gen AI across various business functions. Establish and track clear goals, metrics, and KPIs to measure the success of Gen AI initiatives. Workforce Training and Enablement: Design and deliver comprehensive training programs to upskill the workforce on Generative AI concepts, tools, and best practices. Foster a culture of learning and experimentation with Gen AI technologies with Hackathons or ideathons Create resources and support systems to empower employees to leverage Gen AI in their daily work. Build and Manage a Gen AI Repository: Establish a centralized repository of reusable Gen AI components, models, and tools. Develop and enforce standards and guidelines for the development and deployment of Gen AI solutions. Ensure the repository is easily accessible and promotes knowledge sharing across the organization. Drive Productivity and Innovation: Work closely with business units to identify and prioritize high-impact Gen AI use cases. Monitor and analyze the impact of Gen AI on productivity, efficiency, and business outcomes. Stay Ahead of the Curve: Continuously research and evaluate emerging Gen AI technologies, trends, and best practices. Identify and recommend new tools and platforms to enhance the organization's Gen AI capabilities. Represent the organization at industry events and conferences. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. Experience: 10+ years of experience in the technology industry with a focus on AI/ML. Proven track record of successfully leading and implementing AI/ML initiatives in an enterprise environment. Experience with building and managing Gen AI models and solutions. Strong understanding of various Gen AI techniques, including large language models (LLMs), natural language processing (NLP), and computer vision. Skills: Excellent leadership, communication, and interpersonal skills. Strong analytical and problem-solving abilities. Ability to effectively collaborate with cross-functional teams. Passion for driving innovation and staying ahead of technology trends. Desirable Experience: Experience with cloud-based AI platforms (e.g., Google Cloud AI, AWS AI, Azure AI). Familiarity with agile development methodologies. Contributions to the AI community (e.g., publications, open-source projects).

About the Role We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and implementation of robust and scalable pipelines and backend systems for our Generative AI applications. In this role, you will be responsible for orchestrating the flow of data, integrating AI services, developing RAG pipelines, working with LLMs, and ensuring the smooth operation of the backend infrastructure that powers our Generative AI solutions. You will also be expected to apply modern LLMOps practices, handle schema-constrained generation, optimize cost and latency trade-offs, mitigate hallucinations, and ensure robust safety, personalization, and observability across GenAI systems. Responsibilities Generative AI Pipeline Development Design and implement scalable and modular pipelines for data ingestion, transformation, and orchestration across GenAI workloads. Manage data and model flow across LLMs, embedding services, vector stores, SQL sources, and APIs. Build CI/CD pipelines with integrated prompt regression testing and version control. Use orchestration frameworks like LangChain or LangGraph for tool routing and multi-hop workflows. Monitor system performance using tools like Langfuse or Prometheus. Data and Document Ingestion Develop systems to ingest unstructured (PDF, OCR) and structured (SQL, APIs) data. Apply preprocessing pipelines for text, images, and code. Ensure data integrity, format consistency, and security across sources. AI Service Integration Integrate external and internal LLM APIs (OpenAI, Claude, Mistral, Qwen, etc.). Build internal APIs for smooth backend-AI communication. Optimize performance through fallback routing to classical or smaller models based on latency or cost budgets. Use schema-constrained prompting and output filters to suppress hallucinations and maintain factual accuracy. Retrieval-Augmented Generation (RAG) Pipelines Build hybrid RAG pipelines using vector similarity (FAISS/Qdrant) and structured data (SQL/API). Design custom retrieval strategies for multi-modal or multi-source documents. Apply post-retrieval ranking using DPO or feedback-based techniques. Improve contextual relevance through re-ranking, chunk merging, and scoring logic. LLM Integration and Optimization Manage prompt engineering, model interaction, and tuning workflows. Implement LLMOps best practices: prompt versioning, output validation, caching (KV store), and fallback design. Optimize generation using temperature tuning, token limits, and speculative decoding. Integrate observability and cost-monitoring into LLM workflows. Backend Services Ownership Design and maintain scalable backend services supporting GenAI applications. Implement monitoring, logging, and performance tracing. Build RBAC (Role-Based Access Control) and multi-tenant personalization. Support containerization (Docker, Kubernetes) and autoscaling infrastructure for production. Required Skills and Qualifications Education Bachelors or Masters in Computer Science, Artificial Intelligence, Machine Learning, or related field. Experience 5+ years of experience in AI/ML engineering with end-to-end pipeline development. Hands-on experience building and deploying LLM/RAG systems in production. Strong experience with public cloud platforms (AWS, Azure, or GCP). Technical Skills Proficient in Python and libraries such as Transformers, SentenceTransformers, PyTorch. Deep understanding of GenAI infrastructure, LLM APIs, and toolchains like LangChain/LangGraph. Experience with RESTful API development and version control using Git. Knowledge of vector DBs (Qdrant, FAISS, Weaviate) and similarity-based retrieval. Familiarity with Docker, Kubernetes, and scalable microservice design. Experience with observability tools like Prometheus, Grafana, or Langfuse. Generative AI Specific Skills Knowledge of LLMs, VAEs, Diffusion Models, GANs. Experience building structured + unstructured RAG pipelines. Prompt engineering with safety controls, schema enforcement, and hallucination mitigation. Experience with prompt testing, caching strategies, output filtering, and fallback logic. Familiarity with DPO, RLHF, or other feedback-based fine-tuning methods. Soft Skills Strong analytical, problem-solving, and debugging skills. Excellent collaboration with cross-functional teams: product, QA, and DevOps. Ability to work in fast-paced, agile environments and deliver production-grade solutions. Clear communication and strong documentation practices. Preferred Qualifications Experience with OCR, document parsing, and layout-aware chunking. Hands-on with MLOps and LLMOps tools for Generative AI. Contributions to open-source GenAI or AI infrastructure projects. Knowledge of GenAI governance, ethical deployment, and usage controls. Experience with hallucination suppression frameworks like Guardrails.ai, Rebuff, or Constitutional AI. Shift Time: 2:30 PM to 11:30 PM IST Location-Remote,Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Work Location- Remote Exp-7+ Years Relevant Notice Period- Immediate Lead Data Scientist Relevant Experience: 7+ Years Job Overview: We are seeking a highly skilled and experienced Senior Data Scientist with expertise in Machine Learning (ML), Natural Language Processing (NLP), Generative AI (GenAI), and Deep Learning (DL). Mandatory Skills * 5+ years of work experience in writing code in Python * Experience in using various Python libraries like Pandas, NumPy * Experience in writing good quality code in Python and code refactoring techniques (e.g., IDEs PyCharm, Visual Studio Code; Libraries Pylint, pycodestyle, pydocstyle, Black) * Strong experience on AI assisted coding experience. * AI assisted coding for existing IDE's like vscode. * Experimented multiple AI assisted tools and done research around it. * Deep understanding of data structures, algorithms, and excellent problem-solving skills * Experience in Python, Exploratory Data Analysis (EDA), Feature Engineering, Data Visualisation • Machine Learning libraries like Scikit-learn, XGBoost • Experience in CV, NLP or Time Series. * Experience in building models for ML tasks (Regression, Classification) * Should have Experience into LLM, LLM Fine Tuning, Chatbot, RAG Pipeline Chatbot, LLM Solution, Multi Modal LLM Solution, GPT, Prompt, Prompt Engineering, Tokens, Context Window, Attention Mecanism, Embeddings * Experience of model training and serving on any of the cloud environments (AWS, GCP, Azure) * Experience in distributed training of models on Nvidia GPU’s * Familiarity in Dockerizing the model and create model end points (Rest or gRPC) * Strong working knowledge of source code control tools such as Git, Bitbucket * Prior experience of designing, developing and maintaining Machine Learning solution through its Life Cycle is highly advantageous * Strong drive to learn and master new technologies and techniques * Strong communication and collaboration skills * Good attitude and self-motivated Mandatory Skills- Strong Python coding, Machine Learning, Software Engineering, Deep Learning, Generative AI, LLM, AI Assisted coding tools. Agentic Solutions/Framework Domain-Driven Design (DDD) Testing (Test driven development) Understanding of Hexagonal Architecture and Infrastructure as Code (Terraform)Role & responsibilities Preferred candidate profile

Oracle Database Performance Specialist - ( AI/ML Engineer) About Oracle - Customer Success Services Oracle is the only provider of fully integrated technology solutions that span both infrastructure and applications. Today's businesses, however, need more than just the best technology solutions. They need a strategic partner to support sustained business growth. Oracle Customer Success Services (CSS) was created to help ensure customer's ongoing success with our technology. CSS is completely integrated with Oracle's product development teams to help maximize the value of customer's cloud investment. Job Responsibilities: As CSS AI Engineer, Work directly with customers and have a solid understanding of the application development and support processes. you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications . Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency. Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments. Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring. Build robust, reusable, and scalable Python code for AI model development and deployment. Work on the integration and deployment of generative AI models and systems for innovative applications. Troubleshoot, optimize and maintain production-level AI models and services. Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies. Mandatory Skills: Bachelor's or Master's degree in Computer Science, Engineering or related field. Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps. Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar. Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP). Hands-on experience deploying and managing AI models in production using Docker and Kubernetes. Knowledge of cloud platforms (OCI, AWS, Azure, GCP) and how they relate to containerized AI deployments. Experience with CI/CD pipelines and version control (Git). Strong understanding of generative AI models such as GANs, VAEs or transformers. Familiarity with monitoring, logging, and debugging AI/ML systems in production environments. Excellent communication and teamwork skills, with the ability to collaborate with diverse teams. If you have the above skills, take up the below list of self-test questions to know if you qualify to apply. Self-Test Questions: Is supervised learning used when the data is labelled Answer : Yes, Supervised learning requires a labelled dataset, where each training example has a corresponding output label. Can overfitting occur when a model is too complex Answer : Yes, Overfitting happens when a model is excessively complex, capturing noise in the training data rather than generalizing to new data. Is decision tree a type of supervised learning algorithm Answer : Yes, A decision tree is a supervised learning algorithm used for both classification and regression tasks. Can gradient descent be used for optimization in neural networks Answer : Yes, Gradient descent is commonly used to optimize the weights in neural networks by minimizing the loss function. Is normalization used to scale features between 0 and 1 Answer: Yes, Normalization scales the data to a specific range, often between 0 and 1, to improve the performance of machine learning algorithms. Oracle Database Performance Specialist - ( AI/ML Engineer) About Oracle - Customer Success Services Oracle is the only provider of fully integrated technology solutions that span both infrastructure and applications. Today's businesses, however, need more than just the best technology solutions. They need a strategic partner to support sustained business growth. Oracle Customer Success Services (CSS) was created to help ensure customer's ongoing success with our technology. CSS is completely integrated with Oracle's product development teams to help maximize the value of customer's cloud investment. Job Responsibilities: As CSS AI Engineer, Work directly with customers and have a solid understanding of the application development and support processes. you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications . Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency. Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments. Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring. Build robust, reusable, and scalable Python code for AI model development and deployment. Work on the integration and deployment of generative AI models and systems for innovative applications. Troubleshoot, optimize and maintain production-level AI models and services. Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies. Mandatory Skills: Bachelor's or Master's degree in Computer Science, Engineering or related field. Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps. Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar. Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP). Hands-on experience deploying and managing AI models in production using Docker and Kubernetes. Knowledge of cloud platforms (OCI, AWS, Azure, GCP) and how they relate to containerized AI deployments. Experience with CI/CD pipelines and version control (Git). Strong understanding of generative AI models such as GANs, VAEs or transformers. Familiarity with monitoring, logging, and debugging AI/ML systems in production environments. Excellent communication and teamwork skills, with the ability to collaborate with diverse teams. If you have the above skills, take up the below list of self-test questions to know if you qualify to apply. Self-Test Questions: Is supervised learning used when the data is labelled Answer : Yes, Supervised learning requires a labelled dataset, where each training example has a corresponding output label. Can overfitting occur when a model is too complex Answer : Yes, Overfitting happens when a model is excessively complex, capturing noise in the training data rather than generalizing to new data. Is decision tree a type of supervised learning algorithm Answer : Yes, A decision tree is a supervised learning algorithm used for both classification and regression tasks. Can gradient descent be used for optimization in neural networks Answer : Yes, Gradient descent is commonly used to optimize the weights in neural networks by minimizing the loss function. Is normalization used to scale features between 0 and 1 Answer: Yes, Normalization scales the data to a specific range, often between 0 and 1, to improve the performance of machine learning algorithms. Career Level - IC3

Oracle Database Performance Specialist - ( AI/ML Engineer) About Oracle -Customer Success Services Oracle is the only provider of fully integrated technology solutions that span both infrastructure and applications. Today's businesses, however, need more than just the best technology solutions. They need a strategic partner to support sustained business growth. Oracle Customer Success Services (CSS) was created to help ensure customer's ongoing success with our technology. CSS is completely integrated with Oracle's product development teams to help maximize the value of customer's cloud investment. Job Responsibilities: As CSS AI Engineer, Work directly with customers and have a solid understanding of the application development and support processes. you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications. Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency. Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments. Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring. Build robust, reusable, and scalable Python code for AI model development and deployment. Work on the integration and deployment of generative AI models and systems for innovative applications. Troubleshoot, optimize and maintain production-level AI models and services. Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies. Mandatory Skills: Bachelor's or Master's degree in Computer Science, Engineering or related field. Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps. Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar. Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP). Hands-on experience deploying and managing AI models in production using Docker and Kubernetes. Knowledge of cloud platforms (OCI, AWS, Azure, GCP) and how they relate to containerized AI deployments. Experience with CI/CD pipelines and version control (Git). Strong understanding of generative AI models such as GANs, VAEs or transformers. Familiarity with monitoring, logging, and debugging AI/ML systems in production environments. Excellent communication and teamwork skills, with the ability to collaborate with diverse teams. If you have the above skills, take up the below list of self-test questions to know if you qualify to apply. Self-Test Questions: Is supervised learning used when the data is labelled Answer : Yes, Supervised learning requires a labelled dataset, where each training example has a corresponding output label. Can overfitting occur when a model is too complex Answer : Yes, Overfitting happens when a model is excessively complex, capturing noise in the training data rather than generalizing to new data. Is decision tree a type of supervised learning algorithm Answer : Yes, A decision tree is a supervised learning algorithm used for both classification and regression tasks. Can gradient descent be used for optimization in neural networks Answer : Yes, Gradient descent is commonly used to optimize the weights in neural networks by minimizing the loss function. Is normalization used to scale features between 0 and 1 Answer: Yes, Normalization scales the data to a specific range, often between 0 and 1, to improve the performance of machine learning algorithms. Oracle Database Performance Specialist - ( AI/ML Engineer) About Oracle -Customer Success Services Oracle is the only provider of fully integrated technology solutions that span both infrastructure and applications. Today's businesses, however, need more than just the best technology solutions. They need a strategic partner to support sustained business growth. Oracle Customer Success Services (CSS) was created to help ensure customer's ongoing success with our technology. CSS is completely integrated with Oracle's product development teams to help maximize the value of customer's cloud investment. Job Responsibilities: As CSS AI Engineer, Work directly with customers and have a solid understanding of the application development and support processes. you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications. Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency. Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments. Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring. Build robust, reusable, and scalable Python code for AI model development and deployment. Work on the integration and deployment of generative AI models and systems for innovative applications. Troubleshoot, optimize and maintain production-level AI models and services. Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies. Mandatory Skills: Bachelor's or Master's degree in Computer Science, Engineering or related field. Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps. Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar. Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP). Hands-on experience deploying and managing AI models in production using Docker and Kubernetes. Knowledge of cloud platforms (OCI, AWS, Azure, GCP) and how they relate to containerized AI deployments. Experience with CI/CD pipelines and version control (Git). Strong understanding of generative AI models such as GANs, VAEs or transformers. Familiarity with monitoring, logging, and debugging AI/ML systems in production environments. Excellent communication and teamwork skills, with the ability to collaborate with diverse teams. If you have the above skills, take up the below list of self-test questions to know if you qualify to apply. Self-Test Questions: Is supervised learning used when the data is labelled Answer : Yes, Supervised learning requires a labelled dataset, where each training example has a corresponding output label. Can overfitting occur when a model is too complex Answer : Yes, Overfitting happens when a model is excessively complex, capturing noise in the training data rather than generalizing to new data. Is decision tree a type of supervised learning algorithm Answer : Yes, A decision tree is a supervised learning algorithm used for both classification and regression tasks. Can gradient descent be used for optimization in neural networks Answer : Yes, Gradient descent is commonly used to optimize the weights in neural networks by minimizing the loss function. Is normalization used to scale features between 0 and 1 Answer: Yes, Normalization scales the data to a specific range, often between 0 and 1, to improve the performance of machine learning algorithms. Career Level - IC3

What youll be doing We are looking for data engineers who can work with world class team members to help drive telecom business to its full potential. We are building data products / assets for telecom wireless and wireline business which includes consumer analytics, telecom network performance and service assurance analytics etc. We are working on cutting edge technologies like digital twin to build these analytical platforms and provide data support for varied AI ML implementations. As a data engineer you will be collaborating with business product owners, coaches, industry renowned data scientists and system architects to develop strategic data solutions from sources which includes batch, file and data streams As a Data Engineer with ETL/ELT expertise for our growing data platform & analytics teams, you will understand and enable the required data sets from different sources both structured and unstructured data into our data warehouse and data lake with real-time streaming and/or batch processing to generate insights and perform analytics for business teams within Company. Understanding the business requirements and converting them to the technical design. Working on Data Ingestion, Preparation and Transformation. Developing data streaming applications. Debugging the production failures and identifying the solution. Working on ETL/ELT development. Understanding devops process and contributing for devops pipelines What were looking for... You’re curious about new technologies and the game-changing possibilities it creates. You like to stay up-to-date with the latest trends and apply your technical expertise to solving business problems. You’ll need to have: Bachelor’s degree or four or more years of work experience. Experience with Data Warehouse concepts and Data Management life cycle. Experience in GCP cloud platform - (BigQuery/Cloud Composer/Data Proc(or Hadoop+Spark))/Cloud Function). Experience in any programming language preferably Python. Proficiency in graph data modeling, including experience with graph data models and graph query language. Exposure in working on GenAI use cases. Experience in troubleshooting the data issues. Experience in writing complex SQL and performance tuning. Experience in DevOps Experience in GraphDB , Core Java Experience in real time streaming and lambda architecture. Role & responsibilities Preferred candidate profile

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. Basics of Statistics Experience in ML models Linear Regression, Logistic regression, Random forest etc Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Experience in Azure platform Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications . Bachelor%27s or Master%27s degree in Data Science, Computer Science, Statistics, or a related field. . Experience in data science, machine learning, AI applications, and generative AI modelling. . Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. . Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. . Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. . Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. . Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills . Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. . Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance . Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Senior Manager - Senior Data Scientist (NLP & Generative AI) Location: PAN India / Remote Employment Type: Full-time About the Role We are seeking a highly experienced Senior data scientist with 8+ years of expertise in machine learning, focusing on NLP, Generative AI, and advanced LLM ecosystems. This role demands leadership in designing and deploying scalable AI systems leveraging the latest advancements such as Google ADK, Agent Engine, and Gemini LLM. You will spearhead building real-time inference pipelines and agentic AI solutions that power complex, multi-user applications with cutting-edge technology. Key Responsibilities Lead the architecture, development, and deployment of scalable machine learning and AI systems centered on real-time LLM inference for concurrent users. Design, implement, and manage agentic AI frameworks leveraging Google Adk, Langgraph or custom-built agents. Integrate foundation models (GPT, LLaMA, Claude, Gemini) and fine-tune them for domain-specific intelligent applications. Build robust MLOps pipelines for end-to-end lifecycle management of models-training, testing, deployment, and monitoring. Collaborate with DevOps teams to deploy scalable serving infrastructures using containerization (Docker), orchestration (Kubernetes), and cloud platforms. Drive innovation by adopting new AI capabilities and tools, such as Google Gemini, to enhance AI model performance and interaction quality. Partner cross-functionally to understand traffic patterns and design AI systems that handle real-world scale and complexity. Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related fields. 7+ years in ML engineering, applied AI, or senior data scientist roles. Strong programming expertise in Python and frameworks including PyTorch, TensorFlow, Hugging Face Transformers. Deep experience with NLP, Transformer models, and generative AI techniques. Practical knowledge of LLM inference scaling with tools like vLLM, Groq, Triton Inference Server, and Google ADK. Hands-on experience deploying AI models to concurrent users with high throughput and low latency. Skilled in cloud environments (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG). Experience with agentic AI using Adk, LangChain, Langgraph and Agent Engine Preferred Qualifications Experience with Google Gemini and other advanced LLM innovations. Contributions to open-source AI/ML projects or participation in applied AI research. Knowledge of hardware acceleration and GPU/TPU-based inference optimization. Exposure to event-driven architectures or streaming pipelines (Kafka, Redis).

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Principal Consultant, Sr . Tech Lead/Architect - Gen AI,AI &ML! In this role, you will be dealing with designing and architecting scalable Gen AI, machine learning solutions, developing models, and ensuring their successful deployment. This role requires collaboration with data scientists, ML engineers, and stakeholders to create impactful Gen AI/AI-driven solutions Responsibilities Design and Implement AI Solutions : Architect and develop AI-driven solutions, focusing on generative AI technologies. Cloud Integration : Integrate AI capabilities into cloud platforms, ensuring scalability, security, and compliance. Collaboration : Work closely with stakeholders, including developers, analysts, and business leaders, to understand requirements and deliver solutions. Thought Leadership : Provide guidance and mentorship on AI and cloud technologies, staying updated with the latest advancements. MLOps : Automate machine learning pipelines, including training, testing, deployment, monitoring, and scaling of AI models. Data Analysis : Conduct ongoing data analysis to build or fine- tune AI models for optimal performance. Security and Compliance: Ensure compliance with data privacy and security standards. Stay updated on industry best practices for ML security. Hands-on experience with Large Language Models (LLMs) from OpenAI, GPT-4, etc., with a demonstrated ability to implement solutions utilizing these models. Familiarity with generative models, prompt engineering, and fine-tuning techniques to develop innovative AI solutions. Designing, developing, and implementing solutions tailored to meet client needs. Understanding business requirements and translating them into technical solutions using GEN AI Collaborate with service line teams to design, implement and manage Gen-AI solution Collaborating with stakeholders to align solutions with project goals. Conducting thorough testing to ensure functionality and usability Managing expectations and addressing issues during implementation Analysing, planning, and executing project tasks efficiently for successful delivery. Works closely with service line teams to design, implement, and manage Generative AI solutions Strong understanding of AWS, with a focus on Bedrock models, and expertise in AI/ML, and Cognitive Services Experience working in Agile development environments Qualifications we seek in you! Minimum Qualifications Bachelor&rsquos degree in computer science, Engineering, or a related field. Strong programming skills in Python, R, or Java. Experience with database management systems, such as SQL and NoSQL. Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies, such as Docker and Kubernetes. Proficiency in machine learning frameworks, such as TensorFlow, PyTorch , or Keras , and experience with generative AI techniques, such as GANs, VAEs, and transformers. Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Preferred Qualifications/ Skills Relevant architecture certifications, such as AWS Certified Solutions Architect, AWS Certified Machine Learning - Specialty, Google Cloud Professional Cloud Architect, Google Cloud Professional Machine Learning Engineer or Microsoft Certified: Azure Solutions Architect Expert, Microsoft Certified: Azure Machine Learning Experience with big data technologies (Hadoop, Spark). Knowledge of DevOps practices and CI/CD tools. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Lead Assistant Manager - Data Scientist (NLP & Generative AI) Location: PAN India / Remote Employment Type: Full-time About the Role We are looking for a motivated Data Scientist with 5+ years of experience in machine learning and data science, focusing on NLP and Generative AI. You will contribute to the design, development, and deployment of AI solutions centered on Large Language Models (LLMs) and agentic AI technologies, including Google ADK, Agent Engine, and Gemini. This role involves working closely with senior leadership to build scalable, real-time inference systems and intelligent applications. Key Responsibilities Lead the architecture, development, and deployment of scalable machine learning and AI systems centered on real-time LLM inference for concurrent users. Design, implement, and manage agentic AI frameworks leveraging Google Adk, Langgraph or custom-built agents. Integrate foundation models (GPT, LLaMA, Claude, Gemini) and fine-tune them for domain-specific intelligent applications. Build robust MLOps pipelines for end-to-end lifecycle management of models-training, testing, deployment, and monitoring. Collaborate with DevOps teams to deploy scalable serving infrastructures using containerization (Docker), orchestration (Kubernetes), and cloud platforms. Drive innovation by adopting new AI capabilities and tools, such as Google Gemini, to enhance AI model performance and interaction quality. Partner cross-functionally to understand traffic patterns and design AI systems that handle real-world scale and complexity. Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related fields. 5+ years in ML engineering, applied AI, or data scientist roles. Strong programming expertise in Python and frameworks including PyTorch, TensorFlow, Hugging Face Transformers. Deep experience with NLP, Transformer models, and generative AI techniques. Hands-on experience deploying AI models to concurrent users with high throughput and low latency. Skilled in cloud environments (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG). Experience with agentic AI using Adk, LangChain, Langgraph and Agent Engine Preferred Qualifications Experience with Google Gemini and other advanced LLM innovations. Contributions to open-source AI/ML projects or participation in applied AI research. Knowledge of hardware acceleration and GPU/TPU-based inference optimization.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant - Data Analyst We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Analyze data sets: Examine large data sets to identify trends, patterns, and anomalies that can inform business strategies. Create reports and dashboards: Develop comprehensive reports and interactive dashboards to present findings to stakeholders. Collaborate with teams: Work closely with cross-functional teams, including marketing, finance, and operations, to understand data needs and deliver solutions. Ensure data accuracy: Validate data sources and ensure the accuracy and integrity of data used for analysis. Support decision-making: Provide insights and recommendations based on data analysis to support business decision-making processes. Experience in GenAI project Qualifications we seek in you: Minimum Qualifications . Bachelor%27s or Master%27s degree in Data Science , Computer Science, Statistics, or a related field. . Experience in data science, machine learning, AI applications, and generative AI modelling. . Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. . Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. . Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. . Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills . Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. . Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance . Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Principal Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Collaborate with cross-functional teams to identify , analyze , and interpret complex datasets to develop actionable insights and drive data-driven decision-making. Basics of Statistics Experience in ML models Linear Regression, Logistic regression, Random forest etc Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Experience in Azure platform Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications . Bachelor%27s or Master%27s degree in Data Science , Computer Science, Statistics, or a related field. . Experience in data science, machine learning, AI applications, and generative AI modelling. . Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. . Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. . Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. . Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. . Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills . Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. . Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance . Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Principal Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. Basics of Statistics Experience in ML models Linear Regression, Logistic regression, Random forest etc Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Experience in Azure platform Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications . Bachelor%27s or Master%27s degree in Data Science, Computer Science, Statistics, or a related field. . Experience in data science, machine learning, AI applications, and generative AI modelling. . Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. . Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. . Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. . Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. . Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills . Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. . Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance . Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Collaborate with cross-functional teams to identify , analyze , and interpret complex datasets to develop actionable insights and drive data-driven decision-making. Basics of Statistics Experience in ML models Linear Regression, Logistic regression, Random forest etc Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Experience in Azure platform Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications . Bachelor%27s or Master%27s degree in Data Science , Computer Science, Statistics, or a related field. . Experience in data science, machine learning, AI applications, and generative AI modelling. . Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. . Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. . Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. . Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. . Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills . Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. . Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance . Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Key Responsibilities: Generative AI Systems Design : Architect scalable, high-performance applications powered by Generative AI models (e.g., LLMs, diffusion models), with a focus on real-world usability and business integration. Prompt Engineering & RAG Pipelines : Design and implement optimized prompt strategies and Retrieval-Augmented Generation (RAG) workflows using LangChain and similar frameworks. Agentic AI & Autonomous Workflows : Develop and manage intelligent agents capable of multi-step reasoning, planning, and decision-making using frameworks like LangChain Agents or custom implementations. Vector Store Integration : Design and integrate vector databases for semantic search and document retrieval in GenAI workflows. End-to-End AI Application Development : Build and deploy AI-driven applications from scratch using Python and modern ML/AI toolkits. Ensure clean integration with APIs, databases, and frontend services. Microservices & API Development : Create modular, maintainable backend services using microservices architecture. Ensure RESTful APIs for smooth communication. CI/CD & DevOps : Develop and maintain CI/CD pipelines for model and app deployment. Ensure reproducibility, automated testing, and smooth rollout using tools like GitHub Actions, GitLab CI/CD, or Jenkins. Database Management : Use PostgreSQL and NoSQL databases effectively in storing structured and unstructured data, with focus on performance, indexing, and scaling. Performance Optimization : Continuously monitor, benchmark, and optimize applications for performance, scalability, and cost-efficiency across cloud and on-prem environments. Collaboration & Mentorship : Work closely with product managers, AI researchers, and junior developers. Lead by example and provide technical mentorship in AI system design and production-readiness. Required Qualifications: Technical Expertise : Strong proficiency in Python (mandatory) and experience with AI/ML libraries like FastAI , Hugging Face Transformers, and OpenAI APIs. Experience implementing LangChain workflows, prompt chaining, agents, tools, and memory systems. Hands-on experience building RAG systems using vector DBs like FAISS, Pinecone, Weaviate , or Chroma . Solid understanding of Generative AI technologies (LLMs, image/video generation, embeddings). Working knowledge of Agentic AI concepts for building autonomous tools and applications. Backend & Architecture : Strong skills in system design , API development, and microservices-based backend architecture. Experience with PostgreSQL and NoSQL databases (e.g., MongoDB, DynamoDB). Cloud & DevOps : Familiarity with CI/CD pipelines , containerization (Docker), and cloud deployments (AWS/GCP/Azure). Git-based version control and collaborative development workflows. Communication & Leadership : Ability to translate AI research into production-ready applications. Strong collaboration skills and experience leading engineering efforts or mentoring peers. Preferred (Nice to Have): Experience working with LLMOps tools Exposure to data labeling, fine-tuning , or custom LLM training . Familiarity with streaming architectures or real-time AI inference . Location- Pune, Baner Client Office Work Mode- Hybrid ( 3 days a week) Payments Domain is Mandatory

Job Title : AI/ML Lead - AI Build Plan and Investment Location : Hyderabad Experience : 10-12 years Job Description : We are seeking a highly skilled and experienced AI/ML Lead to spearhead the development and execution of our AI build plan and investment strategy. The ideal candidate will possess a deep understanding of AI/ML technologies, strong leadership abilities, and a proven track record of delivering successful AI initiatives. Responsibilities : AI Build Plan Development : - Conduct in-depth analysis of business requirements and identify AI/ML opportunities to drive growth and efficiency. - Develop a comprehensive AI build plan outlining strategic objectives, technology roadmap, and resource allocation. - Prioritize AI initiatives based on business impact, feasibility, and ROI. - Collaborate with cross-functional teams to align AI strategy with overall business goals. AI Investment Strategy : - Define AI investment criteria and evaluate potential AI projects for funding. - Develop financial models to assess the ROI of AI initiatives and justify investments. - Manage AI budget allocation and track spending against the approved plan. AI Team Leadership : - Build and lead a high-performing AI team of data scientists, machine learning engineers, and other AI professionals. - Provide technical guidance and mentorship to team members. - Foster a culture of innovation and experimentation within the AI team. AI Model Development and Deployment : - Oversee the development and deployment of AI models across various business domains. - Ensure the quality, accuracy, and scalability of AI models. - Monitor model performance and implement necessary improvements. Technology Evaluation and Adoption : - Stay up-to-date with the latest advancements in AI/ML technologies. - Evaluate new AI tools and platforms to identify potential benefits for the organization. - Drive the adoption of AI technologies across the enterprise. Required Qualifications : - Strong proficiency in Python, C++, and deep learning frameworks (Keras, TensorFlow, PyTorch, etc.) - Extensive experience in machine learning algorithms (CNNs, RNNs, LSTMs, Seq2seq) and neural network architectures. - Proven ability to create and optimize AI models for various use cases. - Deep understanding of performance and accuracy metrics for different AI models. - Experience with AI model optimization for CPUs and GPUs. - Knowledge of machine learning accelerators and related software. - Excellent communication and interpersonal skills. - Strong analytical and problem-solving abilities. - Experience with open-source tools for AI model optimization (TF/ONNX/PyTorch). - Exposure to GenAI technologies and their potential applications. Preferred Qualifications : - Experience in leading AI projects from inception to deployment. - Knowledge of cloud platforms (AWS, Azure, GCP). - Experience with big data technologies and tools. - A Master's or Ph.D. degree in computer science, statistics, or a related field.

He/She will be responsible for building innovative products with the latest in AI technology to solve real-world problems. Need solid foundation in ML AI & 1 Yr in Gen AI Expert inPython,LLM Models (RAG) model fine-tuning &agentic AI systems Required Candidate profile Expert inPythonwith strong understanding LLMs Experience buildingRAG pipelines& integrating vector search systems. Expert inmodel fine-tuningusing LoRA, PEFT, or Hugging Face Transformers. Perks and benefits Best Salary + Company Benefits

Job Title: Senior Data Scientist IT/OT, SAP & Classical ML Experience: 7+ Years Location: Jaipur / Noida / Pune Employment Type: Full-time About the Role: We are seeking an experienced Senior Data Scientist with a strong background in IT/OT systems, SAP integration, and classical machine learning techniques. The ideal candidate will bring deep technical expertise combined with a consulting mindset and excellent communication skills. This role involves working closely with clients to understand complex business challenges and delivering actionable AI/ML-driven solutions across diverse enterprise environments. Key Responsibilities: Develop and implement classical machine learning models tailored for IT/OT and SAP data environments. Collaborate with clients and cross-functional teams to analyze requirements and translate them into scalable data science solutions. Integrate data from SAP and other enterprise systems to build comprehensive predictive and prescriptive analytics. Conduct exploratory data analysis, feature engineering, model training, validation, and deployment. Present findings, insights, and recommendations clearly to both technical and non-technical stakeholders. Support digital transformation initiatives leveraging data-driven decision-making in IT and OT operations. Stay updated on industry trends, emerging technologies, and best practices in data science and enterprise IT/OT systems. Required Qualifications: 7+ years of professional experience in Data Science, focusing on classical ML techniques. Proven experience working with IT/OT systems and integrating SAP data into analytic workflows. Strong proficiency in Python/R and ML frameworks such as scikit-learn, TensorFlow, or PyTorch. Demonstrated consulting experience with client-facing engagements and solution delivery. Excellent communication and presentation skills to convey complex concepts effectively. Bachelors or Master’s degree in Computer Science, Engineering, Data Science, or related fields. Preferred Qualifications: Hands-on experience with SAP modules and data structures. Knowledge of IoT and industrial OT systems. Experience with cloud platforms (AWS, Azure, GCP) and MLOps. Familiarity with data visualization tools like Power BI or Tableau. What We Offer: Exciting opportunity to work on digital transformation projects in leading enterprises. Collaborative work culture across Jaipur, Noida, and Pune offices. Competitive salary and benefits package. Continuous learning and professional growth opportunities. If this sounds like you, we'd love to connect! Apply now to chaity.mukherjee@celebaltech.com to be part of our innovative team.

Data Scientist Gen AI & Agentic AI Experience: 2+ Years Location: Jaipur (WFO) Employment Type: Full-time About the Role: We are looking for a highly motivated Data Scientist with experience in Generative AI , Agentic AI , and a strong consulting mindset. This is a client-facing role that blends deep technical expertise with the ability to understand and solve business problems through cutting-edge AI technologies. Youll be part of a forward-thinking team working on impactful projects in AI transformation across industries. Key Responsibilities: Design, develop, and deploy AI/ML solutions with a focus on Generative AI (e.g., LLMs, prompt engineering) and Agentic AI frameworks . Collaborate with clients and internal stakeholders to understand business needs and translate them into AI solutions. Prototype and implement intelligent agent-based systems for automation, decision-making, and conversational interfaces. Build proof-of-concepts (POCs), MVPs, and production-ready solutions in real-world business environments. Work on data preparation, model fine-tuning, and evaluation of large language models (LLMs). Present insights, solutions, and progress to clients in a clear and consultative manner. Stay current with AI trends and contribute to internal knowledge-sharing and innovation. Required Qualifications: 2+ years of experience in Data Science, with hands-on exposure to Generative AI and LLMs (e.g., OpenAI, Cohere, Hugging Face). Experience with Agentic AI concepts or frameworks like LangChain, AutoGen, CrewAI, or similar. Strong Python programming skills and familiarity with ML/DL frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Consulting or client-facing experience with the ability to translate business needs into technical requirements. Good understanding of NLP, prompt engineering, and conversational AI workflows. Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or related fields. Preferred Qualifications: Experience in building AI solutions for enterprise clients. Familiarity with MLOps and deploying models to production. Prior experience with cloud platforms (AWS, Azure, or GCP). Knowledge of vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG) techniques. What We Offer: Exciting projects at the intersection of AI, automation, and enterprise transformation. A collaborative and fast-paced environment focused on innovation. Opportunities for continuous learning and professional growth. Flexible working model with Jaipur as the base location. If this sounds like you, we'd love to connect! Apply now to chaity.mukherjee@celebaltech.com to be part of our innovative team.