---
title: 'Research Engineer, Training & Inference at Harmonic'
canonical: 'https://feeny.ai/job/research-engineer-training-inference-harmonic-palo-alto-zwfvjpjbhw0b'
type: 'job'
last_seen: '2026-09-10'
---

# Research Engineer, Training & Inference at Harmonic

- **Company:** Harmonic
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-07
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/harmonic/a936691b-d40e-439c-a551-a7e5bebab5d6

## Job description

## About Harmonic

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](https://harmonic.fun/news) to learn more about what we are working on!

## About the Role

We are developing reinforcement learning systems at a scale where standard abstractions frequently fail. Unlike labs that operate primarily through high-level wrappers, we own the entirety of our RL stack. This ownership spans from low-level environment simulators and custom communication primitives to our distributed training loops and inference engines. We are seeking engineers who view existing libraries as a baseline and the hardware speed itself as the true target. You will be responsible for the architecture powering our agents, with a relentless focus on maximizing the throughput of our reinforcement learning and production workflows.

## Key Responsibilities

- Total Stack Ownership: Maintain and optimize our proprietary RL training and serving infrastructure. You have the authority to refactor any layer—from the Python API down to the CUDA kernels—to achieve peak performance for foundation model workloads.
- Optimized Training: maximize the throughput of our reinforcement learning system from data generation to model training with sharded multi-node training and inference algorithms.
- High-Performance Serving: optimize our inference stack for high-throughput reinforcement learning and low-latency LLM production traffic. Tune the inference engine, router, and scheduler, down to custom kernels if need be.
- Compute Optimization: Identify and resolve performance bottlenecks within our distributed clusters, ensuring optimal throughput and memory efficiency for multi-billion parameter models, balancing memory constraints with compute-heavy training cycles.

## Minimum Qualifications

- BS in Computer Science or a related technical field, or equivalent industry experience
- 2+ years of relevant, hands-on industry experience
- Proficiency in Python
- Experience building or maintaining components within ML frameworks (e.g., PyTorch, JAX, or TensorFlow).
- Proficiency in either:
- Understanding of distributed training concepts and collective communication primitives (e.g., NCCL). OR
- Practical experience deploying and profiling models on GPU-accelerated cloud infrastructure.

## Preferred Qualifications

- MS or PhD in Computer Science, Mathematics, or a related field.
- 5+ years of relevant, hands-on industry experience
- Proficiency in C++
- Experience writing or improving kernels (Triton, CuTeDSL, TileLang, CUDA, CUTLASS, ThunderKittens) to resolve low-level bottlenecks.
- Proven success deploying performant inference at scale using open-source or custom inference engines, routers, etc.
- Direct experience scaling models via FSDP, Tensor Parallelism, or related sharding techniques on multi-node GPU clusters.
- Experience designing reinforcement learning systems for high-throughput training and asynchronous data sampling.

## 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.

## About Harmonic

## Company Overview
- **One-liner**: Harmonic is an AI research lab building the world’s most advanced mathematical reasoning engine to achieve verifiable, safe, and superhuman mathematical intelligence.
- **Entity Type**: Private (Series C, $1.45B valuation)
- **Headquarters**: Palo Alto, California, United States
- **Founded**: 2023
- **Founders**: Tudor Achim (CEO) and Vlad Tenev (Executive Chairman)

## Core Business
- **Primary industry**: Artificial intelligence / AI research, with a focus on formal mathematical reasoning and automated theorem proving.
- **Target customers**: B2B, enterprise – safety-critical industries such as aerospace, chip design, industrial systems, and healthcare where software reliability is paramount.
- **Mission**: “To explore the frontiers of human understanding” and build mathematical superintelligence (MSI) – AI with mathematical capabilities superior to humans.

## Products & Services
- **Aristotle**: An automated theorem prover that achieved gold‑medal level performance on the 2025 International Mathematical Olympiad. It advances the state‑of‑the‑art on the MiniF2F benchmark (83% success rate with external computer algebra systems, 63% when restricted to Lean). [harmonic.fun/news/intro-harmonic](https://harmonic.fun/news/intro-harmonic/)
- **Yuclid**: An open‑sourced theorem prover that provides visibility into proof traces (announced alongside Aristotle’s IMO results). [harmonic.fun/news/intro-harmonic](https://harmonic.fun/news/intro-harmonic/)

## Market Standing
- **Valuation/Market Cap**: $1.45 billion (Series C, November 2025) [linkedin.com/company/harmonicmath](https://www.linkedin.com/company/harmonicmath)
- **Key Metric**: Total funding of $295M (Series A $75M, Series B $100M, Series C $120M). Revenue is not publicly available.
- **Notable Investors/Partners**: Sequoia Capital (lead Series A), Kleiner Perkins (lead Series B), Ribbit Capital (lead Series C), Index Ventures. [harmonic.fun/news/intro-harmonic](https://harmonic.fun/news/intro-harmonic/)
- **Growth Signals**: 41.9% year‑over‑year headcount growth (37 employees); three funding rounds in 14 months; first research model (Aristotle) achieving state‑of‑the‑art results. [linkedin.com/company/harmonicmath](https://www.linkedin.com/company/harmonicmath)

## Competitive Advantages
- **Formal mathematical reasoning**: Models produce outputs that are guaranteed correct through verifiable, interpretable proof traces – fundamentally safer than current LLM‑based systems.
- **Full‑stack RL ownership**: The team owns the entire reinforcement learning stack – from low‑level environment simulators and custom communication primitives to distributed training loops and inference engines. [harmonic.fun/careers](https://harmonic.fun/careers/)
- **Founding team depth**: Co‑founders with deep AI and scale‑up experience (Tudor Achim co‑founded Helm.ai; Vlad Tenev co‑founded Robinhood), attracting top talent from Anthropic, Meta, and top research universities. [linkedin.com/company/harmonicmath](https://www.linkedin.com/company/harmonicmath)
- **Open ecosystem**: Open‑sourcing tools like Yuclid to build community and accelerate adoption of formal methods.

## Strategic Focus
- **Scale Mathematical Superintelligence (MSI)**: Continue advancing Aristotle’s capabilities and integrate MSI into real‑world safety‑critical applications.
- **Expand research and engineering team**: 8 active job postings across research, infrastructure, product, and machine learning systems. [harmonic.fun/careers](https://harmonic.fun/careers/)
- **Bridge research and production**: Build robust, scalable infrastructure to turn research ideas into deployable systems. [harmonic.fun/careers](https://harmonic.fun/careers/)

## Why Work Here
- **Mission‑driven work**: Contribute to AI safety and fundamental science – building AI that can be trusted because its reasoning is provably correct.
- **Cutting‑edge technical challenges**: Work on low‑level RL systems, formal theorem proving, and distributed training at scale. The team operates like a commercial research lab with high ownership. [harmonic.fun/careers](https://harmonic.fun/careers/)
- **Strong talent density**: Team includes researchers and engineers from Meta, Anthropic, Perimeter Institute, UC Berkeley, Stanford – a fast‑growing, high‑caliber group. [linkedin.com/company/harmonicmath](https://www.linkedin.com/company/harmonicmath)
- **Location & flexibility**: Based in Palo Alto, CA (headquarters) with a second office in the UK. Job postings list “Palo Alto” as location – likely primarily in‑office. [harmonic.fun/careers](https://harmonic.fun/careers/)
- **Growth trajectory**: Rapidly scaling startup ($295M raised, 41.9% headcount growth) offering early‑employee impact and career growth.

## Sources
1. [harmonic.fun/about](https://www.harmonic.fun/about/)
2. [harmonic.fun/careers](https://harmonic.fun/careers/)
3. [linkedin.com/company/harmonicmath](https://www.linkedin.com/company/harmonicmath)
4. [harmonic.fun/news/intro-harmonic](https://harmonic.fun/news/intro-harmonic/)

## Other roles at Harmonic

- [Research Engineer, Formal Methods](https://feeny.ai/job/research-engineer-formal-methods-harmonic-palo-alto-kwng36gryxtz) — Palo Alto, CA
- [Formal Verification Engineer](https://feeny.ai/job/formal-verification-engineer-harmonic-palo-alto-nwvhgknaq1k5) — Palo Alto, CA
- [Software Engineer, Product](https://feeny.ai/job/software-engineer-product-harmonic-palo-alto-1yff5aezv40e) — Palo Alto, CA
- [Software Engineer, ML Systems](https://feeny.ai/job/software-engineer-ml-systems-harmonic-palo-alto-0y91cwhwtxhx) — Palo Alto, CA
- [Software Engineer, Infrastructure](https://feeny.ai/job/software-engineer-infrastructure-harmonic-london-cbrqy6dv7t0p) — London, United Kingdom
- [General Opportunity](https://feeny.ai/job/general-opportunity-harmonic-palo-alto-m52jhh18j8ps) — Palo Alto, CA
- [Research Engineer, Technical Lead](https://feeny.ai/job/research-engineer-technical-lead-harmonic-palo-alto-31amhf03p5wm) — Palo Alto, CA
- [Research Engineer](https://feeny.ai/job/research-engineer-harmonic-palo-alto-ze9en6jgv6fs) — Palo Alto, CA
- [Software Engineer](https://feeny.ai/job/software-engineer-harmonic-palo-alto-qvysrbna92cr) — Palo Alto, CA