Lead Machine Learning Engineer
INR 2520K-3380K (estimate) Senior-level Full Time
Tasks
- Architect cloud-native AI infrastructure
- Architect production LLM systems
- Build multi-agent orchestration
- Build vector database and model serving
- Define SRE practices for ML systems
- Deploy generative AI and RAG pipelines
- Design Agentic AI systems
- Design RESTful and asynchronous APIs
- Develop Python backend APIs
- Embed AI workloads into CI CD pipelines
- Establish prompt versioning and model governance
- Implement ML training and monitoring pipelines
- Implement containerization and Helm deployments
- Implement testing and CI CD for ML workloads
- Instrument observability for performance and quality
- Integrate LLM services with enterprise systems
- Manage GPU cluster and scaling
Perks/Benefits
- Continuing education program
- Continuous learning resources
- Employee discounts
- Family-friendly perks
- Flexible time off
- Health insurance
- Referral incentive awards
- Retirement planning
Skills/Tech-stack
API Development | AWS | Agent systems | Agentic AI | Asynchronous programming | Azure | CI/CD | Chroma | Cluster management | Distributed Systems | Docker | Event Streaming | GCP | GPU Cluster | GPU Cluster Management | GRPC | Generative AI | GitOps | Helm | JWT | Kubeflow | LLM orchestration | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | MLOps | MLflow | Machine Learning | Message Queues | Microservices | Multi-Agent | Multi-Agent Systems | OAuth2 | OpenSearch | PEFT | Pinecone | PostgreSQL | Python | RAG | REST | Redis | SageMaker | Transformers | VLLM | Vector Databases | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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