Profluent is seeking a Software Engineer, MLOps to support ML infrastructure and build tooling/workflows for ML focused workloads, to revolutionize biomedicine by designing and validating novel, functional proteins using deep generative models.
Requirements
- Familiarity with K8s, Terraform, and Docker
- Worked with production backend systems (database, services, etc)
- Experienced with the challenges of working with large scale ML models
- Experience with transitioning research ideas into production
- Familiarity with ML frameworks such as PyTorch, MLFlow
- 2+ years of industry experience working with cloud infrastructure (GCP, AWS, Neo-Clouds, …)
Responsibilities
- Build and manage cloud infrastructure (e.g K8s, Terraform)
- Develop tooling around ML workloads (e.g Skypilot, Kubeflow, Loki, Grafana)
- Support our Progen3 model API offering
- Standardize common data and ML workflows into robust pipelines (e.g Airflow, Kubeflow Pipelines)
- Optimize workloads and reduce costs for compute and storage
- Ensure security best practices are followed (e.g least privilege principle, token management)
- Enhance our CI/CD pipelines to catch regressions (e.g Github Actions)
Other
- BS in Computer Science or a related field
- Legal authorization to work in the United States is required
- Commitment to physical and mental well-being
- Generous paid time off (PTO) policy
- Health insurance (health/dental/vision)
