Top Machine Learning Jobs in Paris

The role involves designing post-training environments for machine learning agents, creating evaluation frameworks, building data pipelines, and optimizing training systems for supply chain applications.

Lead developer-facing work on advanced real-time rendering and neural graphics: optimize GPU/CPU performance, develop and tune neural rendering and AI models, collaborate with AAA studios and NVIDIA architecture/driver teams, build demos, publish and present research.

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

The Applied AI Engineer will onboard clients on Mistral AI products, manage complex integrations, and drive technological transformations through collaboration with stakeholders.

As a Research Engineer in ML, you'll optimize large-scale ML systems, collaborate with Research Scientists, enhance models, and implement algorithms in Python.

As a Cloud Machine Learning Evangelist, you will educate the ML community, publish technical content, and drive visibility of integrations with strategic partners.

The Cloud Machine Learning Engineer will develop and integrate ML solutions with cloud platforms using Hugging Face libraries, focusing on performance and developer experience.

As a Senior Machine Learning Engineer, you will design and refine deep learning models for medical applications, lead projects, and collaborate cross-functionally to integrate research into scalable product features.

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.

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.

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

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

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

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 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.

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.