Top Machine Learning Jobs in France

The role involves implementing MLOps processes, developing scalable pipelines, and enhancing CI/CD for machine learning models while participating in software development practices.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Lead and develop the AI/ML Engineering team for Terabase's software product. Oversee AI/ML initiatives, collaboration across teams, and ensure product quality.

The Senior ML Infrastructure / DevOps Engineer will design, operate, and scale infrastructure for machine learning workloads, automating provisioning and building robust ML pipelines while collaborating with ML teams for production readiness.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

As a Software Engineer - ML, you'll transition research into production systems, implement CI/CD pipelines, and enhance automation workflows.

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.

Design and implement multi-modal perception models for radar sensing, ensuring real-time deployment and producing reliable outputs across conditions.

Lead the development of computer vision models for healthcare robots, optimizing them for edge deployment and managing MLOps pipelines.

Design, build, and productionize LLM-based, retrieval, and multimodal AI systems. Develop RAG and agentic pipelines, deploy and monitor models in cloud-native environments, evaluate performance, and collaborate with engineering and product teams to scale robust AI solutions.

As a Senior Machine Learning Engineer, you will develop and scale customer-facing AI models, ensuring quality integration with business solutions, and mentoring peers.

The role involves conducting R&D in machine learning, particularly in model training and architecture development. Candidates should have a background in deep learning and experience in hands-on experiments with foundational models.

As a Senior Machine Learning Engineer, you will design and deploy ML models, drive technical excellence, mentor team members, and translate business problems into ML solutions.

The role involves developing and maintaining ML models for robotics, enhancing the core library, managing community interactions, and ensuring high performance benchmarks.

As an ML Ops Engineer, you'll design and maintain ML pipelines, ensure monitoring and reliability of ML systems in production, and collaborate with teams across different regions on GCP infrastructure and ML models.

The role involves open-sourcing models and maintaining libraries, optimizing performance, and collaborating with the open-source community. Requires expertise in machine learning and strong programming skills.

As a Senior Machine Learning Engineer at Sonos, you will develop and optimize AI models for voice control systems, ensuring efficient performance across various hardware.

You will optimize ML infrastructure, automate ML pipelines, manage versioning, and collaborate with engineers to ensure model scalability and reliability.

As a Python Developer in the AI & ML team at IDnow, you will design and maintain micro-services for AI-based fraud detection, optimize algorithms, ensure code quality, and collaborate with product owners to meet customer needs.

The intern will assist the applied machine learning engineering team in developing recommender systems, training models, and enhancing the core recommendation platform.

Join the DataLab team to develop operational AI and machine learning solutions, involving data extraction, modeling, and deployment. Collaborate on innovative projects and contribute to knowledge sharing.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

The Senior ML Systems Engineer will build and maintain the training framework for large-scale language models, focusing on distributed training and performance optimization.