onsite
Machine Learning Engineer - SDLC
Machine Learning Engineer - SDLC
The Machine Learning Engineer - SDLC will spearhead research and innovation in applying ML, Deep Learning, and LLMs to the Software Development Lifecycle. This role involves developing advanced AI models to identify and resolve bugs, building LLM-powered features like RAG, and engineering data pipelines to support model training.
About the role
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.
Skills
MLDeep LearningLlmsRetrieval Augmented GenerationRag