AI Research Scientist/Engineer

Position description

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.

What you will do

• 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.

Experience and qualifications

• 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.