6 months ago
Palo Alto, CA, USAMid Level
H1B sponsor
Responsibilities
- Build and manage end-to-end ML pipelines for ETL and automated evaluation.
- Identify bottlenecks and refactor inefficient research code into scalable production systems.
- Establish best practices for model versioning, experiment tracking, and software reliability.
- Deploy and scale workloads on Kubernetes.
- Implement tooling and telemetry for monitoring agent behavior and training health.
- Collaborate with researchers to translate algorithmic requirements into engineering roadmaps.
Requirements
- Bachelor’s degree in Computer Science or 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.
- Preferred experience across data engineering and model debugging.
- Preferred experience refactoring research code into scalable production packages and designing data-loading and evaluation systems for non-deterministic models.
- Preferred experience with Kubeflow, Airflow, or Metaflow.
- Preferred experience with AWS, GCP, or Azure, plus Docker and Kubernetes.
- Preferred experience collaborating directly with researchers.
Benefits
- Unlimited paid time off.
- 401(k) matching.
- Employer-paid health, vision, and dental benefits for employees, with 50% dependent coverage.
- Health Savings Account available for qualifying health plans.
Tech Stack
Categories
Data EngineeringML Engineering
About Harmonic
We are forging the worlds most advanced mathematical reasoning engine