Senior AI/ML Engineer- Optimisation & Operations Research

Optum; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Optum is seeking 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.

You will lead architecture, build production-grade data pipelines, deploy LLM capabilities, establish

Qualifications

• Bachelor's degree in CS/Engineering/Math or related field.

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 efficient, 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)

Skills

GenAI experience

LLMs

Embeddings

RAG pipelines

Hugging Face

LangChain

LlamaIndex

Python (pandas)

SQL

PyTorch/TensorFlow

NLP transformers

CI/CD

Docker

Kubernetes

Terraform

Databricks

Education

Bachelors in Computer Science/Engineering/Math

MS/PhD preferred or equivalent experience

Tools

Spark

Dask

Airflow

Prefect

SQL

Docker

Kubernetes

Terraform

Databricks

Snowflake

BigQuery

MLflow

Job description

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 efficient, 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 professional 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)