Software Engineer, ML Systems

About the Company

At Harmonic, we are building a mathematical reasoning engine that operates with absolute precision. While most AI makes maximum-likelihood guesses, Harmonic's Aristotle uses Lean 4 and reinforcement learning to verify its reasoning and results.

Responsibilities

• Build and manage end-to-end ML pipelines (ETL and automated evaluation)
• Identify and refactor inefficient research code to ensure scalability
• Establish best practices for versioning, experiment tracking, and CI/CD for ML models
• Manage deployment and scaling of workloads on Kubernetes
• Implement tooling and telemetry for agent behavior and training health observability

Requirements

• BS in Computer Science or a related technical field
• 2+ years of relevant industry experience
• Expert-level Python skills
• Disciplined approach to software engineering including testing and modular design
• Experience building and managing end-to-end ML pipelines

Preferred Qualifications

• Full-stack ML experience from data engineering to model debugging
• Experience refactoring research-grade code into production packages
• Ability to design complex data-loading and evaluation systems for non-deterministic models
• Experience with workflow orchestration tools like Kubeflow, Airflow, or Metaflow
• Experience managing large-scale experiments on AWS, GCP, or Azure
• Hands-on experience with Docker and Kubernetes

Benefits

• Unlimited PTO
• 401(k) matching
• 100% employer-paid health, vision, and dental benefits for employees
• Health Savings Account (HSA) available