Lead Machine Learning Engineer
IN - HYDERABAD ORION, India
INR 2250K-2800K (estimate) Senior-level Full Time
Tasks
- Architect production LLM systems
- Build ML training and monitoring pipelines
- Build RAG pipelines
- Build REST and asynchronous APIs
- Containerize and orchestrate AI workloads
- Create prompt versioning and model governance
- Define SRE practices for ML systems
- Deploy vector databases and storage solutions
- Design generative and agentic AI systems
- Develop autonomous AI “Agents”
- Develop high-performance Python backend services
- Develop multi-modal AI systems
- Ensure performance, reliability, and security
- Establish testing and CI CD for ML workloads
- Implement GitOps workflows
- Implement tool use and memory management
- Instrument production observability
- Integrate LLM services with enterprise systems
- Manage GPU cluster inference and autoscaling
Perks/Benefits
- Continuing education program
- Continuous learning resources
- Family-friendly perks
- Financial wellness programs
- Flexible time off
- Health and wellness coverage
- Referral incentive awards
- Retail discounts
- Retirement planning
Skills/Tech-stack
API Security | AWS | Agent Orchestration | Agentic AI | Amazon SageMaker | Async Programming | Autonomous Agents | CI/CD | Chroma | Docker | DynamoDB | Event Streaming | FastAPI | GRPC | Generative AI | GitOps | Google Cloud | Helm | Hugging Face | Hugging Face Transformers | JWT | Kubeflow | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | MLflow | Message Queues | Microservices | Microsoft Azure | Model Governance | Multi-Agent | Multi-Modal | Multi-agent orchestration | Multi-modal AI | OAuth2 | Object storage | Observability | Ollama | OpenSearch | PEFT | Pinecone | PostgreSQL | Python | REST | Redis | Retrieval-Augmented Generation | SOLID | SQS | Testing | VLLM | Vector Databases | Vertex AI
Education
N/A
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