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Research Engineer

HarmonicPalo Alto
On-site FullTime

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Qualifications

Minimum QualificationsBachelor's or Master's degree in Computer Science, Mathematics, or a related technical field, or equivalent practical experience. Proficient programming skills in Python, along with solid experience in software development and testing. Familiarity with deep learning frameworks, particularly PyTorch. Strong grasp of mathematical principles, including algebra, geometry, and analysis. Preferred QualificationsPhD in Computer Science, Mathematics, or a related discipline. Proven experience applying AI methodologies to resolve practical challenges in formal methods. Demonstrated excellence in research shown through publications, patents, or software projects. Active contributions to open-source initiatives or development of software tools in relevant fields. Robust background in reinforcement learning, especially in contexts related to theorem proving (e.g., machine learning and natural language processing). Expertise in formal methods, including expressive logics and proof assistants.

About the job

About Harmonic

Harmonic is an innovative startup on a mission to develop the world's most sophisticated mathematical reasoning engine. Recently, we achieved Gold Medal-level performance at the prestigious 2025 International Math Olympiad (IMO). With support from some of the most influential investors globally, we are strategically expanding our elite technical team to drive groundbreaking advancements in mathematics.

Role Overview

We are looking for a passionate and talented Research Engineer to become a vital member of our Reinforcement Learning & Formal Methods team. In this role, you will focus on enhancing mathematical theorem proving through state-of-the-art reinforcement learning techniques. The ideal candidate will be instrumental in crafting innovative algorithms and models that unify reinforcement learning with formal methods to tackle challenging problems in theorem proving and beyond.

Key Responsibilities

  • Engage in high-impact research at the convergence of reinforcement learning and formal methods, emphasizing mathematical theorem proving.
  • Design and execute pioneering reinforcement learning algorithms and models tailored for theorem proving applications.
  • Collaborate with a multidisciplinary team to effectively merge reinforcement learning techniques with formal methodologies.
  • Stay informed on the latest advancements in reinforcement learning, formal methods, and associated disciplines.

About Harmonic

Harmonic is not just a startup; we're a visionary hub committed to revolutionizing mathematical reasoning through advanced technology. Our recent accolades, including achieving Gold Medal-level performance at the 2025 International Math Olympiad, showcase our dedication to excellence. With the backing of leading investors, we are expanding our team of top-tier talent to push the boundaries of what's possible in mathematics and artificial intelligence.

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