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Harmonic

Startup data for investment due diligence

Research Engineer

AI ResearchConfirmed live in the last 24 hours
Full-timePalo Alto, CA, USA$200k - $450k /yrIn-person

About the Job

Requirements

  • A Bachelor of Science or Master of Science in Computer Science, Mathematics, or a related technical field, or equivalent industry experience.
  • Strong programming skills in Python, with experience in software development and testing.
  • Experience with deep learning frameworks such as PyTorch.
  • A strong understanding of mathematical concepts, including algebra, geometry, and analysis.

Responsibilities

  • Conduct research at the intersection of reinforcement learning and formal methods, with a focus on mathematical theorem proving.
  • Develop and implement reinforcement learning algorithms and models for theorem proving.
  • Collaborate with a multidisciplinary team to integrate reinforcement learning techniques with formal methods.
  • Stay current with developments in reinforcement learning, formal methods, and related fields.

Desired Qualifications

  • A PhD in Computer Science, Mathematics, or a related field.
  • Experience applying artificial intelligence to solve practical problems in formal methods.
  • A track record of research demonstrated by publications, patents, or software contributions.
  • Contributions to open-source projects or development of software tools in the field.
  • A strong background in reinforcement learning, particularly in areas relevant to theorem proving, such as machine learning and natural language processing.
  • Proficiency in formal methods, including experience with theorem-proving systems.

About the Company

Harmonic

Startup data for investment due diligence

Harmonic provides a large, ready-to-query database of startups and professionals. Its data engine curates this information and feeds it directly into a client’s data warehouse or cloud storage, enabling fast, flexible analysis. The service delivers weekly updates and emphasizes breadth, speed, and lower costs compared to pulling data from multiple sources. Its goal is to help investment teams quickly find, assess, and track startup opportunities using a centralized, up-to-date data foundation.

Company size
11-50
Company stage
Series C
Total funding
$295M
Headquarters
Palo Alto, CA
Founded
2023

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