Research Engineer

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 Lean4 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 ...

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We are seeking a highly motivated and skilled Research Engineer to join our Reinforcement Learning & Formal Methods team. The successful candidate will play a key role in advancing verifiable reasoning by developing new algorithms, models, and RL techniques.
Conduct high-quality research in the intersection of RL and formal methods, with a focus on mathematical theorem proving.
Develop and implement novel RL algorithms and models for theorem proving.
Collaborate with a multidisciplinary team to integrate RL techniques with formal methods.
Stay abreast of the latest developments in RL, formal methods, and related fields.

BS or MS in Computer Science, Mathematics a related technical field, or equivalent industry experience
Strong programming skills in Python, with experience in software development and testing.
Experience in deep learning frameworks such as PyTorch
Strong understanding of mathematical concepts, including algebra, geometry, and analysis.
PhD in Computer Science, Mathematics, or a related field.
Experience in applying AI to solve practical problems in formal methods.
Proven track record of high-quality research demonstrated by publications, patents, or software contributions.
Contributions to open-source projects or development of software tools in the field.
Strong background in RL, particularly in areas relevant to theorem proving (e.g., machine learning, natural language processing).
Proficiency in formal methods, including experience with theorem proving systems.