Research Engineer for Machine Learning

As a Research Engineer on the NERPHYS project, the work will focus on designing, implementing, and scaling the core computational and data infrastructure:

• Data Strategy & Infrastructure: Define and deploy automated data collection, synthetic rendering, and validation pipelines tailored for fine-tuning dynamic generative and physical models.
• Model Fine-Tuning & Integration: Implement GPU-accelerated training workflows based on physically-based rendering to fine-tune diffusion models and integrate them with implicit/explicit neural scene representations (3DGS/NeRFs) and physical solvers.
• Systems & Tooling: Build robust, reusable software abstractions and benchmarking frameworks to support the research team in running reproducible dynamic simulation experiments.

• Education: Master’s degree in Computer Science, specializing in Computer Graphics, and Machine Learning for visual computing. Computer Vision education is a plus.
• Core Skills: Proficiency in Python, PyTorch, C++, and CUDA for high-performance deep learning and graphics workflows.
• Graphics & Physics Expertise: Background in computer graphics (rendering, rasterization, ray tracing, path tracing, mitsuba3).
• Advanced Machine Learning skills: Experience with training/fine tuning large models, in particular diffusion models and transformers, automated data generation pipelines, multi-GPU scaling
• Experience with use of AI agentic coding frameworks for task automation., The ideal candidate will be familiar with the main concepts of computer graphics and real-time/interactive rendering, and will have experience with development of advanced machine learning systems involving training and fine-tuning of diffusion/flow matching models and transformers, as well as general experience with moderately large software system development. The ability to work and interact well with a team of motivated researchers is essential. The specific background requirements are listed below.

• Subsidized meals
• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Contribution to mutual insurance (subject to conditions)

The Inria center at Université Côte d’Azur includes 42 research teams and 9 support services. The center’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d’Azur, CNRS, INRAE, INSERM …), but also with the regional economic players.

With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d’Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels., This position is in the context of our ongoing ERC Advanced Grant NERPHYS (for more information see https://www.inria.fr/en/erc-grants-george-drettakis-ai-physics-3d and https://project.inria.fr/nerphys/)

The are seeking to hire a highly motivated candidate who will be part of this exciting project, involving software engineering work on novel research projects, while working alongside the GRAPHDECO group that is continuing the advancement of new research ideas in this project.

This position is a great opportunity to be part of a world-class team of researchers working on exciting and timely projects. The successful candidate will acquire top-notch first-hand knowledge and experience in radiance field rendering which is in extremely high demand today, providing excellent skills for career enhancement.