Staff Software Engineer(MLOps)
Tasks
- Build automated testing for ML pipelines
- Define AI infrastructure roadmap
- Design unified MLOps platform
- Develop ML observability and incident response
- Implement CI/CD for ML
- Implement scalable model deployment and inference
- Lead MLOps architecture and standards
- Lead feature store and automated retraining workflows
- Manage infrastructure as code
- Mentor engineers and drive technical rigor
- Perform root cause analysis for ML system failures
Perks/Benefits
Skills/Tech-stack
AWS Athena | AWS DynamoDB | AWS Glue | AWS SageMaker | Apache Airflow | Apache Flink | CI/CD | CPU GPU Resource Management | Cause analysis | Distributed Systems | Feature Store | GPU resource management | Generative AI | Git | GitHub Actions | High Performance | High-Performance Computing | Incident Response | Inference Optimization | Java | Kotlin | LLMOps | Langchain | Langgraph | MLOps | MLflow | Machine Learning | Microservices | Model Deployment | Object-Oriented | Object-oriented programming | Observability | Performance Computing | Prefect | PySpark | Python | Ray | Resource Management | Root Cause Analysis | Root cause | Scala | Shell Scripting | System design | Task Orchestration | Terraform | Test automation | Test-Driven | Test-Driven Development | Vector Database
Education
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