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Harmonic

Software Engineer, ML Systems

Palo AltoOnsite · United States
FullTime · Engineering
POSTED 7 MAYVERIFIED 10H AGO
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Role
186 days opentrue age
Posted 7 May
Pay
$200k–$300kno pay posted
Market p25–p75
$200k–$300k
SF Bay Area · n=461 · 365d to 6 Nov
CompanyHarmonic →
9open roles
Opened · 30d
+0
Closed · 30d
−0
2d of snapshots · 30d window
Market
3,256open · ML / AI
Opened · 7d
+2427% of open
All ml / ai
6,613open
All tracked boards · live 10 Nov · n=3,256
Visa
3H-1B LCAs · FY26
Median wage
$150k
UK licensed sponsor
✓Worker (A rating)
LCAs FY26 · n=3 · to 2026-05-26
PythonAWSGCPAzureKubernetesDockerAirflow

About Harmonic

At Harmonic, we believe the future of AI depends on proof. Most AI makes its best guess. Aristotle uses formal methods and reinforcement learning to check its own reasoning and results.

AI agents can write software in seconds, but edge cases and silent bugs still get through. We're building the verification engine to find them before code ships. With support for C and Verilog, Aristotle is built for the hardware and software where failure is expensive.

Backed by some of the world’s most prominent investors, we are intentionally scaling an elite technical team.

Try Aristotle for yourself here!

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.

Source · HarmonicFirst seen 2 NovOriginal ↗