4 months ago
Palo Alto, CA, USAMid Level
H1B Sponsor
Responsibilities
- Build and manage end-to-end ML pipelines, including ETL and automated evaluation, for reinforcement-learning research.
- Identify bottlenecks and refactor inefficient research code into scalable, robust implementations.
- Establish best practices for model versioning, experiment tracking, and software reliability.
- Deploy and scale workloads on Kubernetes.
- Implement tooling and telemetry to monitor agent behavior and training health.
- Translate research ideas and algorithmic requirements into production engineering systems.
Requirements
- Bachelor’s degree in Computer Science, a related technical field, or equivalent industry experience.
- At least 2 years of relevant industry experience.
- Expert-level Python skills and disciplined software engineering practices including testing, versioning, and modular design.
- Experience building and managing end-to-end ML pipelines in a production or research-intensive environment.
- Experience across data engineering and model debugging is preferred.
- Experience refactoring research-grade code into scalable production packages is preferred.
- Experience designing complex data-loading and evaluation systems for non-deterministic models is preferred.
- Experience with Kubeflow, Airflow, or Metaflow is preferred.
- Experience managing large-scale experiments on AWS, GCP, or Azure is preferred.
- Experience collaborating with researchers to translate algorithmic requirements into engineering roadmaps is preferred.
- Hands-on Docker and Kubernetes experience is preferred.
Benefits
- Unlimited PTO
- 401(k) matching
- 100% employer-paid health, vision, and dental benefits for employees
- 50% coverage for dependents
- Health Savings Account available for qualifying health plans
Tech Stack
Categories
About Harmonic
We are forging the worlds most advanced mathematical reasoning engine