Software Engineer, ML Systems

Summary

Harmonic is building a mathematical reasoning engine that operates with absolute precision, utilizing Lean 4 and reinforcement learning. They are seeking a pragmatic Software Engineer to own the productionization of research pipelines, focusing on building scalable machinery within their cloud infrastructure.

Responsibilities

• Pipeline Engineering: Build and manage end-to-end ML pipelines (ETL and automated evaluation) that are the bedrock of our RL research
• Bottleneck Resolution: Identify and refactor inefficient research code. You act as the primary engineer ensuring that a promising idea reaches its full potential through scalable code
• Standardization: Establish best practices for versioning, experiment tracking, and CI/CD for ML models to ensure reliability
• Cloud Infrastructure & Observability: Manage the deployment and scaling of workloads on Kubernetes. Implement the tooling and telemetry that allows the team to understand agent behavior and training health at a glance

Skills

• BS in Computer Science, a related technical field, or equivalent industry experience
• 2+ years of relevant industry experience
• Expert-level Python skills and a disciplined approach to software engineering (testing, versioning, and modular design)
• Experience building and managing end-to-end ML pipelines in a production or research-intensive environment
• Full-stack ML experience: Comfortable moving from data engineering to model debugging
• Experience refactoring research-grade code into high-quality, scalable production packages
• Proven ability to design and implement complex data-loading and evaluation systems for non-deterministic models
• Experience with workflow orchestration tools (e.g., Kubeflow, Airflow, or Metaflow)
• Experience managing large-scale experiments on cloud providers (AWS, GCP, or Azure)
• Proven track record collaborating directly with researchers to translate algorithmic requirements into engineering roadmaps
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes)

Qualifications

Must Haves

• BS in Computer Science, a related technical field, or equivalent industry experience
• 2+ years of relevant industry experience
• Expert-level Python skills and a disciplined approach to software engineering (testing, versioning, and modular design)
• Experience building and managing end-to-end ML pipelines in a production or research-intensive environment

Nice to Haves

• Full-stack ML experience: Comfortable moving from data engineering to model debugging
• Experience refactoring research-grade code into high-quality, scalable production packages
• Proven ability to design and implement complex data-loading and evaluation systems for non-deterministic models
• Experience with workflow orchestration tools (e.g., Kubeflow, Airflow, or Metaflow)
• Experience managing large-scale experiments on cloud providers (AWS, GCP, or Azure)
• Proven track record collaborating directly with researchers to translate algorithmic requirements into engineering roadmaps
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes)

Benefits

• Unlimited PTO
• 401(k) matching
• 100% employer-paid health, vision, and dental benefits for employees and 50% coverage for dependents. Harmonic offers varied health coverage options to select what is best for you and your family.
• Health Savings Account (HSA) available for qualifying health plans