AI Researcher in EBM

Logical Intelligence • San Francisco, CA

8d

About The Position

At Logical Intelligence, we're revolutionizing software development with AI-powered formal verification. We've developed groundbreaking agents that provide mathematical guarantees of code correctness, ensuring that software behaves exactly as intended while proactively identifying bugs and security vulnerabilities. Our novel foundation model enables scalable, precise reasoning for formally verifiable code across Rust, Golang, and smart contract VMs. We’ve won a well-known formal verification benchmark called PutnamBench, which consists of 672 hard math problems from the William Lowell Putnam Exam, the oldest collegiate mathematics competition in North America. Backed by a world-class team – including ICPC champions, a Fields Medalist and an ACM Turing Award winner – we're building the future where all code is provably correct. Join our team as an AI Research Engineer and help us push the boundaries of what's possible in logical reasoning! We’re looking for a motivated individual to build, maintain, and improve innovative approaches including (but not limited to!) energy-based modeling (EBM). You'll be at the forefront of designing and refining algorithms that go beyond the capabilities of traditional Large Language Models (LLMs), tackling complex reasoning challenges. You'll work closely with a talented team of AI experts, EBM specialists, formal verification engineers, and software developers to create groundbreaking solutions.

Requirements

• M.Sc. or Ph.D. (preferable) focusing on one or more of the following areas: Computer Science, Artificial Intelligence, Mathematics, or a closely related field
• Subject matter expertise and research in one or more of the following areas: Machine Learning, Deep Learning, Reasoning, Energy-based Modeling (preferable)
• Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like PyTorch /TensorFlow/JAX
• Strong communication and teamwork skills
• Experience with explicit and implicit reasoning
• Provable record of Energy-based usage for different problems
• Hands-on with algorithms used to train Energy-based models
• Demonstrated research publications in any of the major conferences (CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI, ACL, etc.)

Nice To Haves

• Multi-node and multi-GPU training
• Mathematical Reasoning – discrete math and logic
• Formal Verification

Responsibilities

• Research new reasoning algorithms and models
• Pre-train and fine-tune the State-of-the-Art LLMs
• Combine Reasoning algorithm and LLMs
• Build effective and efficient ML pipelines
• Collaborate with other teams to understand their pain points and priorities to define milestones of the corresponding roadmaps
• Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution

What This Job Offers

• Job Type: Full-time
• Career Level: Senior