AI Researcher - Post-Training
Angaben zum Job
| Firma | SonarSource |
| Kategorie | IT, Forschung / Wissenschaft | Pensum | 100% |
| Lohn (geschätzt) | CHF 88'000 – 112'000 / Jahr |
| Einsatzort | Genf |
Job-Inhalt
Position description
At Sonar, we are seeking an ambitious senior researcher to join our cross-disciplinary team, innovating and developing the next generation of solutions to build enterprise-grade coding agents and models. You will harness Sonar’s deep experience in static analysis, and combine it with your experience and leading techniques in large language model post-training. If you are interested in being hands-on with state-of-the-art research, building practical solutions that deliver high-impact for customers, and working within a team of innovative researchers and engineers, this role is for you.
What you will do
Outcome Driven Development: Work in a team developing and implementing advanced products that enable customers to post-train models to power their agentic coding practices. These agents need to generate high-quality code that meets their enterprise standards and software development best practices.
Translate Prototypes to Products: Collaborate closely with researchers, research engineers, MLOps and engineers within the team to design hypotheses and experiments, iterate proofs-of-concept quickly and develop successful prototypes into cutting-edge products.
Subject Matter Expert: You will contribute and discuss ideas within our cross-disciplinary team, driving towards the next generation of coding model post-training for enterprises.
Spearhead Research & Innovation: Stay up-to-date with the latest LLM and agentic developments; you are driven by learning and teaching others. You will need to explain complex technical details and concepts to both technical and non-technical audiences.
Experience and qualifications
The ideal candidate will have:
An advanced academic background (Master’s or PhD) in Computer Science, Machine Learning, or a related quantitative field.
4+ years industry experience in machine learning, with a solid understanding of modern software engineering practices and tools.
Fluency with Python including core ML frameworks, experience with Rust or any of SonarQube’s flagship languages (C#, C++, JS/TS, Java) is a plus.
Expertise in post-training of large language models, including:
Policy optimization algorithms (e.g. GRPO, PPO)
Verifier-based RL frameworks (RLVR)
Supervised fine-tuning (SFT)
Data-centric AI methods, including synthetic data and curation
Parameter-efficient fine-tuning (PEFT)
Preference and Safety Alignment
Experience of driving research projects, delivering valuable findings and prototypes, and then converting them into products.
Excellent communication skills in English and a talent for explaining complex scientific topics clearly and concisely.