Harmonic (harmonic.fun) Logo

Harmonic (harmonic.fun)

Software Engineer, ML Systems

Reposted 21 Days Ago
In-Office
Palo Alto, CA, USA
2-3 Annually
Junior
In-Office
Palo Alto, CA, USA
2-3 Annually
Junior
The Machine Learning Engineer will develop production-grade ML pipelines, optimize research code, and implement cloud infrastructure for ML workloads at Harmonic.
The summary above was generated by AI
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.
Following our Gold Medal-level performance on the 2025 International Math Olympiad (IMO) and the successful resolution of long-standing open problems, we are proving that AI can master the most rigorous domains of human thought. Backed by some of the world’s most prominent investors, we are intentionally scaling an elite technical team.
Visit our company blog to learn more about what we are working on!

About the Role

We are looking for a pragmatic, Software Engineer to own the productionization of our research pipelines. This is an implementation-heavy role designed for an engineer who can take a nascent research idea and build the robust, scalable machinery required to prove it at scale within our cloud infrastructure.

Key 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.

Minimum Qualifications
  • 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.

Preferred Qualifications
  • 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).

What We Offer
  • 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

Equal Opportunity Statement

Harmonic is committed to diversity and inclusivity in the workplace. We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.

HQ

Harmonic (harmonic.fun) Palo Alto, California, USA Office

Palo Alto, CA, United States

Similar Jobs

13 Days Ago
In-Office or Remote
7 Locations
150K-300K Annually
Entry level
150K-300K Annually
Entry level
Angel or VC Firm • Financial Services
Design and build machine-learning-driven robotic systems that operate in the real world, support portfolio company growth, influence product and technical direction, and advance company and career outcomes.
3 Days Ago
Hybrid
Los Altos, CA, USA
234K-319K Annually
Senior level
234K-319K Annually
Senior level
Artificial Intelligence • Software
Drive the quality strategy for Modular's engineering organization by implementing quality systems for AI infrastructure. Collaborate with teams, monitor quality processes, and enhance product excellence.
Top Skills: JaxPyTorchTensorFlow
15 Days Ago
In-Office
San Francisco, CA, USA
180K-250K Annually
Mid level
180K-250K Annually
Mid level
Cloud • Digital Media • Information Technology
Design and implement model serving architectures, develop monitoring tools, and optimize performance for generative media models working with Applied ML teams.
Top Skills: NsightPyTorchTensorrtTransformerengineTriton

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account