Sonarsource7mo ago

Machine Learning Scientist (AI for Code)

Genève · GenevaEmployee / Full-Timemid

Data ScienceMachine Learning ScientistData & AI

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Overview

Who is Sonar? Sonar is driving the future of agent-centric software development. As the leader in AI code review and verification,

Technical Tools

Data ScienceMachine Learning ScientistData & AI

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, Mastercard, NASA, Deutsche Bank, 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 innovative Research Engineer to join our Data & Agentic team and pioneer the next generation of our code analysis engine. You will be at the forefront of applying cutting-edge AI, Large Language Model (LLM) and agentic techniques to the complex domain of source code. Your work will directly shape our products, pushing the boundaries of static analysis to help millions of developers write better, more secure code. If you are driven to solve real-world problems by turning state-of-the-art research into practical, high-impact solutions, this is the role for you.

Create & Innovate: Actively participate in the conceptualization phase. Brainstorm novel ways to improve our products and provide immediate, practical feedback to steer exploratory research toward paths that are both impactful and engineering-feasible.

Develop Advanced AI Models: Design, prototype, and validate novel ML models that identify and resolve complex bugs, vulnerabilities, and code smells, going beyond the capabilities of traditional static analysis.

Develop Pragmatic Prototypes: Build hands-on prototypes that prove the viability and scalability of research concepts. Proactively identify engineering bottlenecks or scalability limits and propose effective mitigations early in the research phase.

Evaluate & Benchmark: Drive the rigorous evaluation of new AI-powered features. Construct high-quality datasets, define relevant success metrics, and implement comprehensive benchmarks leveraging Sonar’s existing IP alongside third-party and open-source AI tools.

Engineer Data Pipelines: Build and manage robust data pipelines to gather, process, and version massive code-centric datasets required for training and evaluating specialized models at scale.

Translate Prototypes to Products: Collaborate closely with engineering and product teams to integrate successful AI prototypes into Sonar's cutting-edge products, ensuring they meet the needs of our global user base.

Communicate and Evangelize: Clearly articulate and document complex technical concepts and research findings to both technical and non-technical stakeholders.

Strong industry experience in AI and a solid understanding of modern software engineering practices and tools, with minimum 2 years experience in industry.

Exceptional programming skills in Python (other programming languages such as Java is a strong plus), and the ability to write clean, well-documented code for product integration.

Practical experience working with modern AI/ML frameworks, LLMs, and integrating third-party or open-source AI tools into functional prototypes.

Proven experience in data handling: constructing high-quality datasets, defining objective success metrics, and building robust benchmarks for AI solutions.

Experience with modern LLM architectures and techniques, such as:

Fine-tuning strategies (e.g., LoRA, QLoRA) and advanced prompt engineering.

Building and optimizing Retrieval-Augmented Generation (RAG) pipelines.

Working with vector databases and semantic search.

Experience with large-scale data processing frameworks and cloud infrastructure (e.g. AWS).

Experience of driving research projects from initial ideation to a demonstrable prototype with a high degree of autonomy.

The ability to fast context-switch and maintain momentum across multiple concurrent, fast-moving research topics.

Excellent communication skills in English, with a talent for translating complex research findings into clear, actionable artifacts for product engineering squads.