AI Researcher - Post-Training (f/m/d)

### **Who is Sonar?** Sonar is driving the future of agent-centric software development. As the leader in AI code verification and governance, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable. Integrating seamlessly with Claude Code, Codex, Cursor, GitHub Copilot, Gemini, and Devin, we help over 75% of the Fortune 100 build trusted, reliable, compliant software. Customers who use Sonar are 44% less likely to report an outage due to AI-generated code. We believe code verification is the critical missing link in the Agent-Centric Development Cycle (AC/DC). Industry giants like Nvidia, ServiceNow,, Goldman Sachs, AstraZeneca, and Ford Motor Company count on us to provide independent, explainable, consistent review and governance of their AI-generated code via products like: - SonarQube: The world’s leading AI code review and verification platform. - SonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair. - SonarSweep & Sonar Context Augmentation: Providing the enterprise-grade context and constraints agents need to be truly effective. Our team operates across global hubs in Austin, Bochum, Dubai, Geneva, London, Singapore, Tokyo, and Washington D.C. We move with a mindset we call CODE: - Committed to our customers and community. - Obsessed with quality. - Deliberate in our decisions. - Effective as one team. With over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution. If you’re hungry to have an impact, want to build at a fast pace, and ready to work at the forefront of AI, we want to hear from you. ### **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.