CDI
Paris
Télétravail occasionnel
Salaire : non spécifié
> 5 ans
Les compétences que l’on cherche
Amélioration continue
Collaboration et travail d'équipe
Data engineering
Foundation
Pytorch
+4
Votre nouvelle entreprise
100 collaborateurs
Software
Artificial Intelligence / Machine Learning
L'avis de Welcome
AZmed delivers AI-powered radiology software to speed up X-ray detection and create more accurate images. Through its offering, the company helps to enhance patient care pathways by increasing sensitivity on scans and reducing the chance of false negatives. While AI technologies hold immense promise in healthcare, they can encounter scepticism and regulatory hurdles. However, this is something AZmed appears to be tackling well thus far, as it it has already secured both CE marking and FDA clearance for its software. Strong financial support will allow the company to continue developing its technology, aiming to expedite workflows for radiologists. Having established partnerships with prestigious healthcare institutions like the NHS, and expanded into CT imaging, the future looks bright for AZmed.
Vos missions au quotidien
- As a Machine Learning Engineer in the AI team, you will be a bridge between experimental research and robust production systems, directly empowering our AI researchers to build, scale, and deploy cutting-edge technologies. In this supportive yet highly impactful role, your core focus will be to:
- Maintain the overall quality and continuous evolution of both our datasets and our ML models
- Take ownership of the AI team’s codebase, refining architecture, enforcing high standards through rigorous pull request reviews, and actively spreading modern software engineering best practices across the team
- Optimize and operate our Foundation Model pipeline (data preparation, training, validation)
- Drive AI-related feature development and build streamlined pipelines to significantly reduce the time it takes to move models and operating points into production environments
- Success in this role relies on seamless cross-functional collaboration, as you will partner closely with our Ops, MLOps, and Software Engineering teams to ensure smooth infrastructure integration and system reliability
- Ensure quality and continuous improvement of our datasets
- Ensure quality and continuous improvement of our models
- Reduce time to production of AI models and operating points
- Support AI-related feature developments
- Improve and maintain the AI team’s codebase
- Learn and spread dev good practices and guidelines in the team
- Collaborate closely with the Ops, MLOps and Dev teams
Benefits
- Meal vouchers (Swile) and optional BSPCE
- Activities with colleagues: Games, Sports (Basketball session, Urban soccer, …), After works in a bar, karaoke or other activities
- Flexible work: Possibility of working remotely two days per week
- Time-off: 5 weeks of paid holidays and 2 weeks of RTT
- Annual off-sites: Two company holidays each year in amazing locations
- Healthcare: Alan Blue mutuelle
- Classic Perks: Transportation
- Localization: Great office in Paris 2nd arrondissement, next to metro Grands Boulevards
Ce que l’on cherche
- Experience with our ML stack (pytorch, sklearn, skimage)
- Experience in Computer Vision (Classification, Detection and Segmentation)
- Experience in NLP (LLM, pre-processing, word embeddings)
- Experience with our Data Engineering stack (Mongodb, SQL, Spark, Airflow, dvc)
- Master’s degree in statistics, data science, AI (or any related domain)
- Have a strong sense of responsibility and rigor, from PR Reviews to ownership of features
- Being proactive in proposing new features or technologies
- 5+ years of experience as a data engineer or data scientist working on ML applications
- Experience with medical images
- Experience in training or fine-tuning foundation models (pipeline and resource management)
- Experience with image and text alignment, VLM, LLaVA
Nos étapes de recrutement
- Screening interview with our Head Of AI (30 min, remote)
- Technical interview with our Deep Learning Researchers (2 hours, at the office or remote)
- Meet the team and founders (2h30 hours, at the office)