Research Engineer, Distributed Training

About Us

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.

Key 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.

Minimum Qualifications

• 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).

Preferred Qualifications

• MS or PhD in Computer Science, Mathematics, or related technical fields

• Knowledge of reinforcement learning techniques

• Contributions to open-source AI projects

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