Advisor - ML Engineering & Operations
IN: Lilly Bengaluru, India
INR 3700K-5000K (estimate) Senior-level Full Time
Tasks
- Apply software engineering best practices to ML systems
- Architect retrieval-augmented generation systems
- Build production Agentic AI systems
- Define technical contracts and APIs for integrations
- Deploy ML services with Docker and Kubernetes
- Design ML pipelines
- Design and review ML architecture with stakeholders
- Evaluate model performance robustness and explainability
- Implement production ML monitoring
- Implement production guardrails for LLM applications
- Integrate vector databases for semantic search
- Lead LLMOps for prompt versioning and evaluation
- Monitor LLM cost and latency
- Optimize model hyperparameters
- Orchestrate CI/CD pipelines
- Own end to end ML architecture
- Own feature engineering decisions
- Set human in the loop boundaries
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Lambda | AWS SageMaker | Artificial Intelligence | CI/CD | Data Lineage | Docker | GitHub Actions | Kedro | Keras | Kubernetes | LLMOps | Langgraph | Language Models | Large Language Models | MLflow | Machine Learning | Model Monitoring | Model versioning | Pinecone | Prefect | Prompt engineering | PySpark | PyTorch | Python | R | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Vector Database
Education
Roles
AI Engineer | Engineer | ML Engineer | Senior AI Engineer | Senior ML Engineer
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