Data Scientist – ML / GenAI / LLM

Cognizant; Saint Francis (AR); On-site; USD 150,000 - 155,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Paid Holidays

PTO

401(k) Plan

Disability Insurance

Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant is seeking an experienced Data Scientist to design and build production-scale ML and GenAI/LLM solutions. The role covers problem framing, model development, evaluation, deployment, and optimization across the ML lifecycle.

Responsibilities include building ML pipelines, applying prompt engineering, RAG, fine-tuning, and evaluating LLMs, plus collaboration with engineering, product, and data teams. Strong Python and cloud experience preferred.

Qualifications

• 10+ years of experience in data science or ML engineering.
• Strong Python programming and production-grade ML development.
• Experience building GenAI/LLM applications and tools.

Responsibilities

• Design and implement ML/DS solutions for complex business problems.
• Develop GenAI/LLM applications including conversational AI and summarization.
• Work with pre-trained LLMs, prompt engineering, and RAG techniques.
• Build data/ML pipelines for training, inference and deployment.
• Collaborate with cross-functional teams to translate requirements.

Skills

Python programming

Data Science

Machine Learning

GenAI/LLM

Prompt engineering

RAG

MLOps

Model deployment

Experimentation

Cloud platforms

Tools

PyTorch

TensorFlow

scikit-learn

Hugging Face

LangChain

LlamaIndex

Vector databases

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