Research Engineer, Distributed Training

Harmonic•Palo Alto, CA

About The Position

Harmonic is a startup building the world’s most advanced mathematical reasoning engine, recently achieving Gold Medal-level performance on the 2025 International Math Olympiad (IMO). Backed by some of the world's most prominent investors, we are intentionally scaling our elite technical team. We are seeking a highly motivated and skilled Research Engineer with expertise in model training, to focus on reasoning in formal and informal settings. The successful candidate will play a key role in scaling our reinforcement learning systems beyond human-level capabilities.

Requirements

BS in Computer Science, related technical fields, or equivalent industry experience
2+ years of experience focused on training large language models
Knowledge of cutting-edge models, and experience building evaluations for model capability
Expertise in Python and PyTorch
Experience with distributed training, parallel computing, and GPU acceleration
Strong experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM or Kubernetes).

Nice To Haves

MS or PhD in Computer Science, Mathematics, or related technical fields
Knowledge of reinforcement learning techniques
Contributions to open-source AI projects

Responsibilities

Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimization.
Optimize and scale our training infrastructure to improve efficiency and reliability in a reinforcement learning setting.

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

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