Research Engineer for Machine Learning for and by Rendering

Research Engineer for Machine Learning for and by Rendering Download job offer in PDF format Contract type : Fixed-term contract Renewable contract : Yes Level of qualifications required : Graduate degree or equivalent Other valued qualifications : PhD, Master Fonction : Temporary scientific engineer Level of experience : Recently graduated About the research centre or Inria department 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. Context 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. The engineer will work on projects of the Ph.D. students and postdocs of the group. Context Generative models have proven highly effective at providing powerful structural and physical priors for complex computer graphics and vision tasks. Recent breakthroughs leverage these generative priors to tackle inverse problems, such as intrinsic image decomposition [1], radiance field relighting [2], and physical dynamic reconstruction. Most state-of-the-art approaches build on large video or multi-view diffusion models pre-trained on massive datasets. While fine-tuning these models preserves generalization while adapting them to domain-specific physics and rendering constraints, doing so reliably requires robust data pipelines, dynamic simulation grounding, and large-scale data collection strategies. Within the ERC Advanced Grant NERPHYS (NEural Representations for PHYSical simulation), the engineer will help build solutions that aim to bridge neural representations (e.g., 3D Gaussian Splatting, NeRFs) with physics-based simulation and generative priors to achieve interactive, physically plausible 3D scene editing and simulation. Assignment Approach & Engineering Scope 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. Key References • [1] Liang, Ruofan, et al. "Diffusionrenderer: Neural inverse and forward rendering with video diffusion models." IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025. • [2] Poirier‐Ginter, Yohan, et al. "A Diffusion Approach to Radiance Field Relighting using Multi‐Illumination Synthesis." Computer Graphics Forum, Vol. 43, No. 4, 2024. • [3] ERC Grant NERPHYS: NEural Representations for PHYSical simulation (Inria GraphDeco). Skills We are searching for recent graduates, but also for candidates with a few years experience. Requirements • 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. Benefits package • 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) Remuneration From 2692 € gross monthly (according to degree and experience) Apply for this position Share • Facebook • Linkedin • Twitter • Email General Information • Theme/Domain : Interaction and visualization Software engineering (BAP E) • Town/city : Sophia Antipolis • Inria Center : Centre Inria d'Université Côte d'Azur • Starting date : 2026-12-01 • Duration of contract : 1 year • Deadline to apply : 2026-09-27 Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed. Instruction to apply Applications must be submitted online on the Inria website. Collecting applications by other channels is not guaranteed. Defence Security : This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. Recruitment Policy : As part of its diversity policy, all Inria positions are accessible to people with disabilities. Contacts • Inria Team : GRAPHDECO • Recruiter : Drettakis George / George.Drettakis@inria.fr The keys to success 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. About Inria Inria, the French national institute for research in digital science and technology, supports the French government in national research and innovation strategies in the digital field, acting as Digital Programs Agency. Inria leads over 300 research and innovation projects with its 3,500 scientists, engineers, and support staff, in partnership with universities and the digital ecosystem (businesses, entrepreneurs, and public stakeholders). Together, we explore strategic fields such as artificial intelligence, cybersecurity, quantum computing, cloud technologies, digital transformation in healthcare, digital twins, and digital technologies for defence. We develop practical solutions such as software, tech startups, partnerships with national companies, and cutting-edge training programmes. Our goal is to drive scientific, technological, and industrial excellence to ensure France’s digital sovereignty.