Our team has an immediate permanent opening for a Research Engineer.
Responsibilities :
- Conduct advanced research to explore and apply state-of-the-art LLM and AI techniques to improve software engineering processes, including requirements analysis, system design, modelling, and automated software testing.
- Develop novel frameworks and methodologies for integrating LLMs into software engineering workflows. This includes applying prompt engineering, retrieval-augmented generation (RAG), self-consistency methods, reflection techniques, search and planning algorithms, and evaluation metrics to enhance system performance and decision-making.
- Design and implementation of techniques that combine symbolic reasoning with generative AI models, aiming to bridge the gap between data-driven and logic-based approaches to problem-solving in software systems.
- Collaborate with cross-functional teams of researchers, engineers, and product experts to integrate AI-driven solutions into real-world software systems engineering challenges.
Communicate research findings through academic publications and industry reports.
Stay at the forefront of LLM advancements and related AI technologies, identifying opportunities for innovation and contributing to the development of next-generation software systems engineering tools and techniques.
LI-TL1
What you’ll bring to the team :
- A Ph.D. in Software Engineering, Requirements Engineering, Artificial Intelligence, Natural Language Processing (NLP), or closely related fields, with a focus on the application of Large Language Models and AI techniques.
- Research & development experience in the application of AI / LLMs in the software engineering domain, with a solid understanding of both theoretical foundations and practical implementations;
Strong programming skills and experience in LLM development tools.
- Proven ability to address complex challenges in AI / LLM applications, particularly in integrating AI-driven insights into software engineering tasks such as requirement specification, system design, and quality assurance.
- Demonstrated ability to work effectively in interdisciplinary teams, with strong communication skills to convey complex technical concepts to non-expert stakeholders and present findings at conferences or workshops.
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