Lead ML Operations Engineer
INR 4000K-5000K (estimate) Senior-level Full Time
Tasks
- Build microservices for AI systems
- Collaborate with cross-functional teams
- Define CI/CD pipelines for ML
- Deploy applications using Streamlit and React
- Design end to end solution development
- Develop agentic AI workflows
- Ensure production reliability and observability
- Establish containerization standards
- Implement multi-agent architectures
- Implement security governance and responsible AI
- Integrate models and LLMs
- Lead AI ML and GenAI architecture
- Manage model lifecycle and versioning
- Monitor drift and system performance
- Own data ingestion pipelines
- Present architecture trade offs to stakeholders
- Translate requirements into production solutions
Perks/Benefits
- N/A
Skills/Tech-stack
API Gateway | AWS | AWS Fargate | AWS IAM | AWS Lambda | AWS Secrets | AWS Secrets Manager | AWS Step Functions | Agent Orchestration | Agent systems | Amazon API | Amazon API Gateway | Amazon Bedrock | Amazon CloudWatch | Amazon EC2 | Amazon ECR | Amazon ECS | Amazon EventBridge | Amazon S3 | Amazon SNS | Amazon SQS | Amazon SageMaker | CI/CD | Docker | Drift Detection | Encryption | Evaluation Frameworks | External stages | FastAPI | Flask | GenAIOps | Human-in-the-loop | Java | Kubernetes | Logging | MLOps | Microservices | Model Drift | Model Drift Detection | Model Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Prompt engineering | Python | RAG | REST APIs | React | Retrieval-Augmented Generation | SQL | Scala | Secrets Manager | Snowflake | Snowflake Cortex | Snowflake SQL | Snowflake Tasks | Snowflake stored procedures | Snowpark Python | Step Functions | Stored Procedures | Streamlit | The Loop
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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