As a Machine Learning Engineer specializing in LLMs and code analysis, you will drive innovation by applying advanced AI techniques to enhance the Software Development Lifecycle. Your responsibilities include developing novel ML models, building LLM-powered features for code analysis and remediation, and managing data pipelines to support these initiatives.
About the role
About the Role
SonarSource is looking for a passionate and innovative Machine Learning Engineer with a strong background in Large Language Models (LLMs) and code analysis. In this role, you will be at the forefront of applying cutting-edge AI techniques to enhance the Software Development Lifecycle (SDLC).
Responsibilities
Spearhead Research & Innovation: Stay on the cutting edge of ML, Deep Learning, and LLMs, specifically their application to the Software Development Lifecycle (SDLC), and identify novel opportunities to enhance our products.
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.
Build LLM-Powered Features: Develop and implement advanced LLM-based solutions, including Retrieval-Augmented Generation (RAG) for contextual code analysis, fine-tuning models on proprietary codebases, and exploring agentic systems for automated code remediation.
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 ML 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.