Principal Machine Learning Engineer
INR 2500K-3500K (estimate) Senior-level Full Time
Tasks
- Advise AI strategy and build vs buy decisions
- Architect production scale LLM systems
- Build RAG pipelines
- Build asynchronous APIs
- Build restful APIs
- Build reusable AI libraries
- Define SRE practices for ML systems
- Define transformation KPIs
- Deploy vector database backed retrieval
- Design autonomous AI agents
- Develop multi-modal AI systems
- Develop responsible AI policies
- Drive platform standardization for AI self service
- Embed AI workloads into CI CD pipelines
- Ensure performance, reliability, and security
- Establish model governance
- Implement ML pipelines
- Implement prompt versioning
- Implement rigorous testing
- Instrument observability for model quality and performance
- Integrate LLM services with enterprise systems
- Lead code reviews
- Manage GPU cluster inference scaling
- Manage distributed high throughput model serving
- Operationalize agent workflows
- Set up training through monitoring
Perks/Benefits
- Continuing education program
- Continuous learning resources
- Family-friendly perks
- Financial wellness programs
- Generous time off
- Health care coverage
- Retail discounts
- Retirement planning
Skills/Tech-stack
API Security | Agentic AI | Amazon Bedrock | Auto Scaling | Automated testing | Azure OpenAI | CI/CD | Chroma | Cluster management | Docker | DynamoDB | FastAPI | GPU Cluster Management | GRPC | Generative AI | GitOps | Helm | JWT | Kafka | Kubeflow | Kubernetes | LLMOps | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Microservices | Model Governance | Multimodal AI | OAuth2 | Object storage | Observability | OpenSearch | Pinecone | PostgreSQL | Prompt engineering | Python | REST | Redis | Retrieval-Augmented Generation | SOLID | SQS | SageMaker | Vector Databases | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Engineering | Master of Science | PhD
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