Software Engineer: Keystone Project (Machine-Verified LLM Inference)

École polytechnique fédérale de Lausanne, EPFL; Lausanne; Vor Ort; CHF 110.000 - 150.000; Vollzeit

Benefits dieser Stelle

Frontier AI models access

Travel for collaboration

Professional development

Excellent working conditions

Zusammenfassung

EPFL seeks a software engineer to help turn verified research prototypes into a production-grade, high-performance LLM inference engine. The role involves designing core components, runtime glue, GPU kernels, and driver interfaces, with collaboration across EPFL and Imperial College London.

You'll organize the engineering infrastructure, run differential testing against reference engines, and contribute to agentic AI pipelines, proofs, and open-source artefacts.

Qualifikationen

• Higher degree in computer science or equivalent; experience in research or industry.
• Strong knowledge of systems programming and performance optimization.
• Experience with one or more of: GPU programming, ML inference serving, formal methods.

Aufgaben

• Design and implement core components of the verified LLM inference engine.
• Collaborate with EPFL and Imperial College London teams.
• Maintain CI and performance benchmarking tooling.
• Develop AI pipelines for specification autoformalization and proof repair.
• Produce documentation and reproducible artefacts.
• Address failures and regressions across the stack.
• Assess security and trusted computing base; contribute to ARIA exercises.
• Contribute to open-source releases and communities.

Kenntnisse

Systems programming

Performance engineering

GPU programming

ML inference serving

Formal verification concepts

Build systems/CI

English communication

Ausbildung

Master's degree in Computer Science

Tools

Python

C/C++

Rust

OCaml

Jobbeschreibung

EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries.

Software Engineer: Keystone Project (Machine-Verified LLM Inference)

Mission

The Keystone project, an ARIA-funded collaboration between EPFL and Imperial College London, aims 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. Its missions include the design and implementation of verified inference components, the formalization of GPU kernel semantics, the development of AI-assisted proof engineering workflows, and the open-source release of specifications, proofs, and verified artefacts.

We seek an excellent software engineer to play a central role in turning verified research prototypes into a production-grade, high-performance inference engine. Prior experience with formal verification is welcome but not required: a strong systems engineer with the motivation to learn proof-assistant technology will thrive in this role.

Main duties and responsibilities

Bring technical expertise in systems programming and performance engineering to support the project’s research; collaborate with the research teams at EPFL and Imperial College London

Design, implement, and maintain core components of the verified LLM inference engine, including the runtime and glue code connecting extracted verified code, GPU kernels, and drivers

Organize and manage the project’s engineering infrastructure: differential testing against reference engines (vLLM, SGLang), continuous integration for code and proofs, and performance benchmarking

Develop and maintain agentic AI pipelines for specification autoformalization, proof generation, and proof repair

Write documentation, procedures, and recommendations to ensure reproducibility of the project’s artefacts

Diagnose, prevent, and repair failures and regressions across the software stack

Analyze the security level and trusted computing base of the components we develop, and contribute to red/blue team exercises within the ARIA programme

Contribute to open-source releases and engage with their user communities

Profile

Higher degree in computer science or education deemed equivalent; experience in the field

Excellent technical knowledge of systems programming, and strong programming ability in several of: Python, C/C++, Rust, OCaml, or other functional languages

Knowledge of one or more of the following, with strong motivation to grow in the others:

GPU programming (CUDA, Triton, PTX) or high-performance computing

ML inference or serving systems (vLLM, SGLang, PyTorch internals, or similar)

Interactive theorem proving (Rocq, Lean, HOL, Isabelle, or similar) or other formal methods

Experience maintaining development tooling: build systems, continuous integration, and test infrastructure

Experience using LLM-based development tools or building agentic workflows is a plus

Mastery of English indispensable (oral and written); French is an asset but not required

Sense of priorities, integrity, and autonomy in your work

Team spirit and aptitude for conducting technical investigations and implementations; excellent ability to communicate with varied audiences, from proof engineers to systems researchers

Strong sense of service and spirit of initiative

We offer

The possibility to join a dynamic and stimulating team on a high-profile ARIA-funded project

A multicultural and academic working environment of high quality

Opportunities for continuing education and professional development

Excellent working conditions

Generous access to frontier AI models and high-performance compute

Funded travel for collaboration between Lausanne and London, and for conferences

Informations

For any further information, please contact: Nate Foster ([e-mail]).

Contract Start Date : 01.12.2026, or to be determined

Activity Rate: 100.00

Contract Type: CDD

Duration: 1 year, renewable (project duration permitting)