MLOps Lead
Tasks
- Build automated training pipelines
- Build feature stores
- Collaborate with research teams
- Create data pipelines
- Define MLOps roadmap
- Deploy and manage model serving
- Design machine learning infrastructure
- Drive platform engineering standards
- Establish observability strategies
- Implement CI/CD workflows
- Implement monitoring, logging, alerting
- Lead MLOps team
- Orchestrate machine learning workflows
- Support low latency inference
Perks/Benefits
- Fully remote work
- Healthcare coverage
- Inclusive culture
- International collaboration
- Paid parental leave
- Relocation assistance
- Technical ownership
Skills/Tech-stack
AWS | Bash | Cloud platform | Databricks | Datadog | FastAPI | GitOps | Go | Google Cloud | Google Cloud Platform | Grafana | Helm | Inference Server | KServe | Kubernetes | MLflow | Microsoft Azure | OpenTelemetry | Prometheus | PyTorch | Python | Snowflake | TensorFlow | TensorFlow Serving | Terraform | Torchserve | Triton Inference | Triton Inference Server | Weights & Biases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Engineer | Lead | Learning Engineer | ML Engineer | MLOps Lead | Machine Learning Engineer
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