Machine Learning & Operations Engineer
United States - Remote
R
USD 160K-240K (estimate) Senior-level Full Time
Tasks
- Build distributed experimentation infrastructure
- Collaborate with ML researchers to productize algorithms
- Deploy monitor and maintain production ML models
- Design ML training pipelines
- Develop ML CI CD workflows
- Establish MLOps best practices model registry artifact management observability
- Implement experiment tracking hyperparameter tuning automation and reproducibility systems
- Improve system reliability, performance, and security
- Optimize GPU compute utilization
- Orchestrate data ingestion preprocessing validation and model versioning
Perks/Benefits
- 401k match
- Disability insurance
- Employer paid dental
- Employer paid vision
- Employer-paid life insurance
- Employer-paid medical
- Remote-first work
Skills/Tech-stack
AWS | Airflow | Argo | Azure | CI/CD | Data Validation | Distributed Training | Docker | Experiment tracking | GCP | GPU workload management | GitHub Actions | GitLab CI | Hyperparameter Tuning | Infrastructure as Code | Jenkins | Kubeflow | Kubernetes | ML Model Deployment | MLflow | Model Deployment | Model Registry | Observability | Prefect | Pulumi | PyTorch | Python | TensorFlow | Terraform | Weights and Biases | Workload management | “as-code”
Education
N/A
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