AI/Machine Learning Engineer

Level of qualifications required : Graduate degree or equivalent Other valued qualifications : Young doctorates Fonction : Support functions Level of experience : Recently graduated About the research centre or Inria department The Inria University of Lille centre, created in 2008, employs 360 people including 305 scientists in 15 research teams. Recognised for its strong involvement in the socio-economic development of the Hauts-De-France region, theInria University of Lille centre pursues a close relationship with large companies and SMEs. By promoting synergies between researchers and industrialists, Inria participates in the transfer of skills and expertise in digital technologies and provides access to the best European and international research for the benefit of innovation and companies, particularly in the region.For more than 10 years, theInria University of Lille centre has been located at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on Avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT) Context Within the framework ofNeuroKnowAI, a deep-tech startup projectstemmed fromresearch. This project is currently in the Inria Startup Studio acceleration program. NeuroknowAI is a privacy-first intelligent document processing platform with domain knowledge across industries. The objective is to develop and integrate AI models and document processing pipelinesmore specifically dedicated to intelligent multi-industry document processing (insurance, healthcare, legal, finance, media, HR, marketing, real estate) with a privacy-first architecture. No regular travel is foreseen for this post. Work is primarily on-site (some remote days are available). Assignment Assignments:With the help of theNeuroKnowAI technical team, the recruited person will design, develop, and optimize machine learning models for intelligent document processing, including Transformer models, Named Entity Recognition (NER), and differential privacy algorithms. Collaboration:The recruited person will be in connection with the R&D team that develops NeuroDoc, NeuroShield, and NeuroGuard products for ensuring ML model integration into production infrastructure. Responsibilities:The person recruited is responsible for designing and implementing industry-specific ML models and will take initiatives for improving the performance, accuracy, and efficiency of document processing pipelines. Steering/Management:The person recruited will be responsible for documenting technical developments and contributing to ML architectural decisions. Main activities Main activities:1. Develop and train Transformer models for multi-modal document processing (OCR, speech-to-text, text analysis)2. Design industry-specific NER models (healthcare, legal, finance, insurance, etc.)3. Implement differential privacy algorithms for NeuroShield4. Optimize ML pipelines for high-performance processing (multi-GPU, mixed precision computation)5. Integrate models into semantic search infrastructure Complementary activities:1. Write technical documentation and performance reports2. Test, modify, and validate models before production deployment3. Present work progress to partners and the team Skills Technical skills and level required: Python: Expert PyTorch or TensorFlow: Advanced Hugging Face Transformers: Advanced NLP and document processing: Advanced OCR and multi-modal processing: Intermediate to Advanced GPU optimization (CUDA, mixed precision): Intermediate MLOps (Docker, CI/CD, model deployment): Intermediate Git and version control: Advanced Languages: English: Fluent (technical documentation, team communication) French: Appreciated but not mandatory Relational skills: Ability to communicate complex technical concepts clearly Team spirit and collaboration Autonomy and initiative Adaptability in a fast-evolving environment Other values appreciated: Experience with differential privacy techniques Knowledge of data protection regulations (GDPR, HIPAA) Experience in industry-specific document processing (healthcare, legal, finance) Open-source contributions or scientific publications Benefits package 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 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 Please provide your resume and cover letter 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. We are looking for someone passionate about artificial intelligence and natural language processing, comfortable in a dynamic startup environment where innovation and autonomy are valued. Required profile Master's in Data Science with a minimum of 2 years of experience in Machine Learning, ORPhD in Machine Learning with a minimum of 1 year of experience Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face) Experience with Transformer models and NLP Knowledge of document processing techniques (OCR, entity extraction) Experience with GPU optimization and high-performance computing is a plus Awareness of data privacy concerns appreciated The ideal candidate Enjoys solving complex problems and turning research concepts into concrete solutions Is curious and stays up-to-date with the latest ML/NLP advances Has a startup mindset, adapts to quickly changing environments effortlessly Appreciate teamwork while being capable of leading projects independently Has attention to detail and code quality Is mindful of privacy and data protection challenges Essential qualities to fulfill this assignment are feeling at ease in an environment of scientific dynamics, and a desire to learn and experiment. About Inria Inria is the French national research institute dedicated to digital science and technology. It employs 2,600 people. Its 200 agile project teams, generally run jointly with academic partners, include more than 3,500 scientists and engineers working to meet the challenges of digital technology, often at the interface with other disciplines. The Institute also employs numerous talents in over forty different professions. 900 research support staff contribute to the preparation and development of scientific and entrepreneurial projects that have a worldwide impact. #J-18808-Ljbffr