Job Summary

Returnship Hiring - Women Professionals

We are seeking an AI/ML professional with strong experience in Data Science, Generative AI, and MLOps to build end-to-end machine learning solutions—from data exploration and model development to production deployment and monitoring. The ideal candidate will design robust ML pipelines, implement GenAI solutions, and operationalize models at scale with best-in-class governance and security.

Key Responsibilities

AI/ML & Data Science

• Translate business problems into ML use cases and define measurable outcomes.
• Perform data exploration, feature engineering, model training, and evaluation (classification, regression, time-series, NLP, CV).
• Build scalable pipelines for training and inference using Python/SQL and Spark.
• Conduct A/B testing, bias/fairness checks, and explainability (SHAP/LIME).

Generative AI (GenAI)

• Design and implement solutions using LLMs (e.g., OpenAI, Azure OpenAI, Cohere), embeddings, and vector databases.
• Build RAG pipelines (retrieval augmented generation), prompt engineering, and evaluation frameworks.
• Fine-tune or instruct-tune models; manage hallucination, toxicity, and guardrails.
• Integrate GenAI into products/workflows (chatbots, content generation, code assistants).

MLOps

• Operationalize ML/GenAI models with CI/CD, model versioning, and automated deployments.
• Set up model monitoring (performance drift, data drift), observability, and alerting.
• Implement governance: model registry, lineage, access controls, compliance.
• Optimize cost/performance; manage scaling and reliability in production.

Required Skills & Qualifications

• Programming: Python (NumPy, Pandas, scikit-learn), PyTorch/TensorFlow; SQL.
• ML/GenAI: LLMs, embeddings, vector DBs (FAISS, Milvus, pgvector), RAG, prompt engineering.
• Data: Spark, Databricks, data lake/warehouse concepts; ETL/ELT.
• MLOps Tooling: MLflow, Kubeflow, Airflow, Docker, Kubernetes; CI/CD (Azure DevOps/GitHub Actions).
• Cloud: Azure (Data Factory, Synapse, Databricks, Azure ML, Azure OpenAI); experience with AWS/GCP is a plus.
• Analytics/Math: Statistics, probability, optimization, experimental design.
• Security & Governance: Role-based access, secrets management, PII handling, compliance.

The Cognizant community:
We are a high caliber team who appreciate and support one another. Our people uphold an energetic, collaborative and inclusive workplace where everyone can thrive.

• Cognizant is a global community with more than 300,000 associates around the world.
• We don’t just dream of a better way – we make it happen.
• We take care of our people, clients, company, communities and climate by doing what’s right.
• We foster an innovative environment where you can build the career path that’s right for you.

About us:
Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World’s Best Employers 2025) is consistently listed among the most admired companies in the world. Learn how Cognizant helps clients lead with digital at www.cognizant.com

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.

Disclaimer: 
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.