Postdoc: Keystone Project (Machine-Verified LLM Inference) — EPFL

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Mission

The Keystone project seeks to advance knowledge in the following domains: • Formal verification and interactive theorem proving (Rocq, Lean) • Secure and high-performance computer systems, including ML infrastructure

We seek outstanding candidates working in formal methods and/or computer systems with interests in one or more of the following areas: machine-checked verification of systems software, GPU kernel semantics and verification, and AI-assisted proof engineering.

The position is part of an ARIA-funded collaboration between EPFL and Imperial College London whose goal is to build a formally-verified ML inference engine, demonstrating that AI can help make verified systems competitive with unverified systems in terms of development effort, features, and performance.

Main duties and responsibilities

• Conducting research related to the Keystone project, including contributing to the design and construction of a machine-verified LLM inference engine. The precise focus will be discussed with the successful candidate depending on their background, expertise and affinities. Possible directions include: • Formalizing GPU kernel semantics (e.g., PTX/Triton) in a proof assistant and verifying high-performance inference kernels (numerical accuracy, memory safety, data race freedom, functional correctness) • Implementing and verifying the inference coordination layer (batching, KV-cache management, scheduling) in Rocq/Lean, with extraction to executable code • Developing agentic AI workflows for specification autoformalization, proof generation, and proof repair • Build a strong network in the fields of formal verification, systems, and ML infrastructure, including close collaboration with the Imperial College London team (regular visits to London are expected) • Contribute to open-source releases of specifications, proofs, and verified artefacts • Engage with the ARIA programme, including red/blue team exercises and sprint reviews

Profile

• PhD (or nearing completion of) in computer science or a closely related field • Background in formal verification, programming languages, systems, or ML • Research experience in one or more of: interactive theorem proving (Rocq, Lean, HOL, Isabelle, or similar), GPU programming or semantics, compilers, concurrency, or ML systems (e.g., vLLM, SGLang, or similar inference engines) • Strong computational and analytical skills, including solid software engineering ability across multiple languages (e.g., Python, C++, OCaml, functional languages) • Experience using or evaluating LLM-based tools for code or proof generation is a plus • Publication record (relative to your career stage) in internationally leading journals and conferences • Independent, creative, and solution-oriented • Excellent written and oral communication skills in English • Strong motivation to explore new research domains at the intersection of AI and formal methods • Good team spirit and enthusiasm for working in a distributed, multi-institution team

We offer

• A stimulating and international working environment • Excellent working conditions • Opportunity to perform state-of-the-art research in one of the most dynamic scientific institutions in Europe, within a high-profile ARIA-funded project • Opportunity to interact with internationally renowned experts at EPFL and Imperial College London, and with a strong team of postdoctoral researchers and PhD students • Generous access to frontier AI models and high-performance compute for proof-assistant workloads • Funded travel for collaboration between Lausanne and London, and for conferences

Informations

Only applications submitted through the online platform are considered. You are asked to supply: • A brief cover letter (pdf, up to 2 pages).

And in one PDF

• A CV with a publication list. • A research statement (pdf, up to 3 pages). • Contact details for 3 referees.

For any further information, please contact: Nate Foster (n

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