Senior MLOps Platform Engineer
Tasks
- Architect data pipelines to data lake
- Build automated testing canary releases and rollbacks
- Build self service model and endpoint tooling
- Create observability and monitoring stacks
- Design unify MLOps platform
- Develop CI CD pipelines for model packaging
- Ensure reproducibility security and compliance
- Implement and operate Kubernetes and AWS services
- Implement security IAM network policies and secret management
- Manage inference latency throughput and resource utilization metrics
- Mentor junior engineers and maintain internal knowledge bases
- Optimize inference performance with scaling and quantization
- Plan disaster recovery for hybrid infrastructure
Perks/Benefits
- Flexible time off
- Healthcare
- Learning resources
- Retirement benefits
- Robust learning and development opportunities
- Wellness
Skills/Tech-stack
AWS EKS | Airflow | Amazon S3 | Amazon SageMaker | Argo CD | CI/CD | CloudWatch | Direct Connect | Distributed Systems | Docker | ELK | Flink | Flux | GPU scaling | GitHub Actions | GitLab CI | GitOps | Go | Grafana | Helm | IAM | Java | Kafka | Kubernetes | Kubernetes Operators | MLOps | Model Quantization | OpenTelemetry | Prometheus | Python | Rust | S3 | Spark | Step Functions | VPN
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
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