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Research Engineer (f/m/d)
SonarSourceBochum
Zur OriginalanzeigeDie Bewerbung läuft direkt beim Arbeitgeber.
Warum dieser Job gelistet ist
KI ist Gegenstand der Rolle (Kernbegriffe in Titel/Anforderungen). Prüfverfahren ansehen
Aufgaben
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 Agentic Workflows: Design, prototype, and validate intelligent agentic systems and automated workflows that facilitate writing clean code, identifying root causes of system issues, and remediating complex bugs and vulnerabilities. - 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 product 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 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
Anforderungen
Advanced academic background in Computer Science, Machine Learning, or a related quantitative field. - Strong software engineering experience (minimum 2+ years in industry) with proficiency in Python and major modern programming languages. - Practical experience with modern agentic frameworks, software automation tools, and LLM architectures. - Experience of driving research projects from initial ideation to a demonstrable prototype with a high degree of autonomy. - Hands-on experience integrating third-party tools, program analysis frameworks, or open-source libraries into functional prototypes. - Proven experience in data handling: constructing high-quality datasets, defining objective success metrics, and building robust benchmarks for new solutions. - 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. Plus: - Background in static analysis: abstract syntax trees (ASTs), code security, bug detection, etc. - Familiarity with LLM techniques such as model fine-tuning, semantic search engines, etc. - Experience with large-scale data processing frameworks and cloud infrastructure (e.g. AWS).
Additional comments This role is based in Bochum. We are unable to consider candidates unwilling to be in Bochum, but we are willing to relocate the right candidate.
Zur Position
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 and verification engines. You will be at the forefront of applying cutting-edge AI, advanced agentic workflow and static analysis techniques to complex source code. Your work will directly shape our core products—ensuring both AI-generated and developer-written code meets rigorous enterprise quality and security standards.
If you are driven to turn state-of-the-art research into practical, high-impact solutions, this is the role for you.
Interesse an dieser Position?
Die vollständige Anzeige und das Bewerbungsformular liegen beim Arbeitgeber.
Zur OriginalanzeigeWorum es hier geht
Modelle bauen, trainieren und verbessern: von klassischem Machine Learning über Computer Vision bis zum Feinschliff großer Sprachmodelle.