Research Engineer - Post-Training for Agentic Coding
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Who is Sonar?
Sonar is driving the future of agent-centric software development. As the leader in AI code review and verification, 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, Booking.com, 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:
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SonarQube: The world’s leading AI code review and verification platform.
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SonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair.
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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:
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Committed to our customers and community.
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Obsessed with quality.
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Deliberate in our decisions.
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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 research engineer 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.
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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.
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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.
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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.
The ideal candidate will have:
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An advanced academic background (Master’s or PhD) in Computer Science, Machine Learning, or a related quantitative field.
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Strong industry experience in machine learning, with a solid understanding of modern software engineering practices and tools.
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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.
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Expertise in post-training of AI models, with techniques such as:
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Reinforcement learning from verifiable rewards
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GRPO and related techniques
Offline or semi-online reinforcement learning
Parameter efficient fine-tuning
Supervised fine-tuning
Safety Alignment
Experience with large-scale data processing frameworks and cloud infrastructure (e.g. AWS, Microsoft Foundry, Databricks).
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.