Research Engineer - Post-Training for Agentic Coding

Londonmid

OtherResearch Engineer

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Quick Summary

Overview

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.

Technical Tools

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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:

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.

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.

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.

The ideal candidate will have:

An advanced academic background (Master’s or PhD) in Computer Science, Machine Learning, or a related quantitative field.
Strong 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 AI models, with techniques such as:
- Reinforcement learning from verifiable rewards
- 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.