onsite
Machine Learning Engineer - LLMs (Research & Innovation)
Machine Learning Engineer - LLMs (Research & Innovation)
As a Machine Learning Engineer specializing in LLMs for Research & Innovation, you will drive the development of advanced AI models to enhance Sonar's products, focusing on applying cutting-edge ML and Deep Learning techniques to the Software Development Lifecycle. You will design, prototype, and implement LLM-based solutions for code analysis and remediation, while collaborating with engineering and product teams to integrate these innovations into the product suite.
About the role
About the Role
Sonar is seeking a highly skilled and innovative Machine Learning Engineer with a strong focus on LLMs (Research & Innovation) to join our team. In this role, you will be at the forefront of applying advanced AI techniques to the Software Development Lifecycle (SDLC), enhancing our products with intelligent solutions for code quality and security.
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.