ML Operations Engineer
Tasks
- Build CI CD pipelines for ML artifacts
- Build RAG-architectures
- Build and maintain LLM fine tuning pipelines
- Collaborate on ML AI feature development
- Design ML deployment infrastructure
- Implement model tracking and versioning
- Improve platform reliability and cost efficiency
- Manage experiment tracking
- Manage project priorities and deadlines
- Migrate training and inference workloads
- Operate GPU cluster architecture
- Optimize inference for generative AI
- Partner with Data Science and AI teams
- Set up monitoring and observability for ML systems
Perks/Benefits
- 401k match
- Dental insurance
- Flexible PTO
- Health and wellness allowance
- Internet stipend
- Medical insurance
- Paid Holidays
- Parental leave
- Professional development reimbursement
- Remote-friendly culture
- Vision insurance
- WiFi reimbursement
- Work from home stipend
Skills/Tech-stack
Airflow | Apache Spark | Argo Workflows | CI/CD | CUDA | CUDNN | Docker | Grafana | Jupyter | Kubernetes | Linux | MLflow | Machine Learning | Model Serving | Model registries | NVIDIA GPU | Prometheus | Python | RAG | Vector Databases
Education
Roles
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