Job Summary

We're looking for a hands-on technical leader to design, build, and productionize AI/ML and GenAI solutions that improve healthcare operations and patient outcomes. You will own end-to-end delivery-from problem framing and data pipelines to models, MLOps/LLMOps, and ongoing monitoring-while mentoring a small team and partnering with product, data engineering, and clinical/operations stakeholders.

Primary Responsibilities

- Lead architecture and delivery of ML/GenAI solutions (classification, forecasting, NLP, deep learning, LLM apps) at production scale

- Build robust data/feature pipelines over large clinical/claims datasets; write effective, well-tested Python (pandas/NumPy) and SQL

- Develop and deploy LLM capabilities: prompt design, fine-tuning, RAG pipelines, vector indexing, and evaluation with guardrails

- Establish MLOps/LLMOps best practices: CI/CD, model registry, experiment tracking, monitoring, drift detection, A/B testing

- Ensure data privacy and compliance (HIPAA/PHI handling, access controls, auditability) and champion model governance and Responsible AI

- Translate business problems into technical roadmaps; communicate trade-offs and results to executives and non-technical partners

- Mentor engineers and set engineering standards (code reviews, documentation, reliability, observability)

Required Qualifications

- Bachelors in Computer Science, Engineering, Math, or related field required; MS/PhD preferred or equivalent experience





- 10+ years of qualified experience in software/ML engineering, including 3+ years leading projects or teams

- Hands-on GenAI experience: LLMs, embeddings, RAG, fine-tuning, evaluation; familiarity with Hugging Face and LangChain/LlamaIndex

- Solid data engineering skills: SQL;

experience with Spark/Dask and workflow orchestration (Airflow/Prefect)

- Solid foundation in statistics and ML (hypothesis testing, experimental design, feature engineering, supervised/unsupervised methods)

- Deep learning expertise (PyTorch or TensorFlow) and modern NLP (transformers)

- Expert Python and pandas stack; ability to write vectorized, high-performance code; solid testing practices (pytest) and Git

- Cloud proficiency (AWS/Azure/GCP) and containerization/orchestration (Docker/Kubernetes); CI/CD and IaC (Terraform) exposure

- Proven excellent communication and stakeholder management skills

Preferred Qualifications

- Healthcare domain experience: claims, EHR/HL7/FHIR, coding (ICD/CPT), risk adjustment, quality measures, de-identification

- Experience with Big data platforms (Databricks, Snowflake, BigQuery) and streaming (Kafka); lakehouse patterns

- Experience with MLOps stack: MLflow/SageMaker/Azure ML/Vertex; model monitoring/observability

- Vector databases (FAISS, Pinecone, pgvector), knowledge graphs (Neo4j), and ontologies (UMLS/SNOMED)

- Security/compliance frameworks (SOC 2, HITRUST) experience

- Experience with additional languages for performance or integration (Scala/Java/Go)

📌 Senior AI/ML Engineer- Optimisation & Operations Research (Hyderabad)
🏢 Optum
📍 Hyderabad