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

3 нед. назад

90.4k–166.8k EUR / yearGermanyEuropeOnsite

machine learningpythonartificial intelligence

Research role focused on AI code verification and governance to ensure reliability, security, and maintainability of AI-generated software.

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, explaina

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.

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.