AI/Machine Learning Engineer (F/M)

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 pipelines more 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 NeuroShield 4. 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 reports 2. Test, modify, and validate models before production deployment 3. 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, OR PhD 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.

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