Job description

Job Title: Data Scientist – ML / GenAI / LLM Job Summary We are looking for an experienced Data Scientist with strong expertise in Data Science, Machine Learning, Machine Learning Engineering (MLE), Generative AI, and Large Language Models (LLMs) . The ideal candidate will have a strong foundation in building production-grade machine learning solutions and hands-on experience developing GenAI/LLM-based applications. This role requires someone who can work across the ML lifecycle, from problem formulation and model development to evaluation, deployment, optimization, and productionization. **Must have 10+ years of experience** Key Responsibilities • Design, develop, and implement advanced Machine Learning and Data Science solutions for complex business problems. • Build, train, evaluate, and optimize ML models using structured and unstructured data. • Develop Generative AI and LLM-based applications , including conversational AI, knowledge assistants, summarization, information extraction, and other enterprise AI use cases. • Work with pre-trained LLMs and apply techniques such as prompt engineering, RAG, fine-tuning, and model evaluation. • Design and implement Retrieval-Augmented Generation (RAG) solutions leveraging enterprise data sources. • Build robust data and ML pipelines to support model training, inference, and production deployment. • Apply strong MLE principles to ensure models and AI applications are scalable, reliable, maintainable, and production-ready. • Develop solutions using Python and commonly used ML/AI frameworks and libraries. • Experiment with different models, architectures, prompts, retrieval strategies, and evaluation techniques to improve solution quality. • Implement appropriate LLM evaluation and monitoring approaches for accuracy, relevance, reliability, and performance. • Collaborate with engineering, product, data, and business teams to translate business requirements into AI/ML solutions. • Stay current with evolving developments in Generative AI, LLMs, Machine Learning, and MLOps . Required Skills • Strong hands-on experience in Data Science and Machine Learning . • Strong programming skills in Python . • Experience developing and productionizing ML models and ML pipelines . • Strong understanding of Machine Learning Engineering (MLE) concepts. • Hands-on experience with Generative AI and Large Language Models (LLMs) . • Experience with prompt engineering, RAG, embeddings, vector search/vector databases, and LLM evaluation . • Understanding of transformer architectures, NLP, and foundation models . • Experience with ML/AI frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face , or similar technologies. • Experience integrating LLMs/foundation models into enterprise applications. • Working knowledge of MLOps , model deployment, monitoring, versioning, and CI/CD concepts. • Experience working with cloud-based data and AI platforms such as AWS, Azure, or GCP . • Strong understanding of statistics, experimentation, feature engineering, model selection, and model evaluation. Preferred Skills • Experience with LLM orchestration/frameworks such as LangChain, LlamaIndex , or similar tools. • Experience with vector databases and semantic search solutions. • Knowledge of AI agents / Agentic AI and tool-calling architectures. • Experience building enterprise-grade GenAI applications. • Familiarity with LLM guardrails, responsible AI, security, and governance considerations. • Experience optimizing GenAI solutions for latency, scalability, reliability, and cost . Salary and Other Compensation: The annual salary for this position is between $150-155Kdepending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans. Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: · Medical/Dental/Vision/Life Insurance · Paid holidays plus Paid Time Off · 401(k) plan and contributions · Long-term/Short-term Disability · Paid Parental Leave · Employee Stock Purchase Plan Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable la Additional employment information Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law. Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview. Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws. Applicants for US based positions must be currently authorized to work for any employer in the United States. The company is unable to provide employment-based immigration sponsorship for US based positions. If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email CareersNA2@cognizant.com for roles based in the Americas or CareersIndia2@cognizant.com for roles based in India. About Cognizant: Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.

Requirements

Must-haves

Job Title: Data Scientist – ML / GenAI / LLM
This role requires someone who can work across the ML lifecycle, from problem formulation and model development to evaluation, deployment, optimization, and productionization.
Must have 10+ years of experience**
Design, develop, and implement advanced Machine Learning and Data Science solutions for complex business problems.
Build, train, evaluate, and optimize ML models using structured and unstructured data.
Develop Generative AI and LLM-based applications , including conversational AI, knowledge assistants, summarization, information extraction, and other enterprise AI use cases.
Work with pre-trained LLMs and apply techniques such as prompt engineering, RAG, fine-tuning, and model evaluation.
Design and implement Retrieval-Augmented Generation (RAG) solutions leveraging enterprise data sources.
Build robust data and ML pipelines to support model training, inference, and production deployment.
Apply strong MLE principles to ensure models and AI applications are scalable, reliable, maintainable, and production-ready.
Develop solutions using Python and commonly used ML/AI frameworks and libraries.
Experiment with different models, architectures, prompts, retrieval strategies, and evaluation techniques to improve solution quality.
Implement appropriate LLM evaluation and monitoring approaches for accuracy, relevance, reliability, and performance.
Collaborate with engineering, product, data, and business teams to translate business requirements into AI/ML solutions.
Stay current with evolving developments in Generative AI, LLMs, Machine Learning, and MLOps .
Strong hands-on experience in Data Science and Machine Learning .
Strong programming skills in Python .
Experience developing and productionizing ML models and ML pipelines .

Nice-to-haves

Experience with LLM orchestration/frameworks such as LangChain, LlamaIndex , or similar tools.
Experience with vector databases and semantic search solutions.
Knowledge of AI agents / Agentic AI and tool-calling architectures.
Experience building enterprise-grade GenAI applications.
Familiarity with LLM guardrails, responsible AI, security, and governance considerations.
Experience optimizing GenAI solutions for latency, scalability, reliability, and cost .

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlllmmachine learningaipythonci/cdawsazuregcp

Platform: cognizant
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave