MLOps Lead
Tasks
- Build automated training pipelines
- Build data pipelines
- Build feature stores
- Collaborate with research teams
- Define MLOps roadmap
- Deploy and scale machine learning models
- Design scalable machine learning infrastructure
- Detect model drift and operational issues
- Implement CI/CD workflows
- Lead MLOps team
- Optimize model serving architecture
- Set up monitoring, logging, alerting
Perks/Benefits
- Continuous learning culture
- Healthcare coverage
- International collaboration
- Paid parental leave
- Relocation assistance
- Remote work
- Technical ownership
Skills/Tech-stack
AWS | Azure | Databricks | Datadog | FastAPI | GCP | GitOps | Grafana | Helm | Inference Server | KServe | Kubernetes | MLflow | Machine Learning | OpenAPI | OpenTelemetry | Prometheus | PyTorch | Python | Snowflake | TensorFlow | TensorFlow Serving | Terraform | Torchserve | Triton Inference | Triton Inference Server | Weights and Biases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Engineer | Lead | Learning Engineer | MLOps Lead | Machine Learning Engineer
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