Top Machine Learning Jobs in France

The Trading Risk Analyst supports sales and trading, manages trade processes, analyzes P&L, and collaborates with teams on technology and operational workflows.

Lead product development for Datadog APM features, focusing on distributed tracing, performance analysis, and AI-driven troubleshooting. Work with engineers, designers, and customers to validate problems, deliver prototypes to production, define go-to-market, and measure adoption and impact.

The Senior AI Engineer will develop AI tools to enhance developer productivity at Datadog, focusing on LLM-based systems, prompts, and integration with existing products, while collaborating with various teams and users.

The Strategic Sales Executive will sell Identity Governance Administration solutions to multinational organizations, engaging with senior decision-makers and navigating lengthy sales cycles.

As a Senior Applied Scientist, you will design machine learning solutions, develop scalable features, and analyze data within the Datadog app, collaborating with engineering and product teams.

As an AI Researcher at Datadog, you'll conduct cutting-edge research in AI, focusing on foundation models and AI agents for observability and reliability, collaborating with cross-functional teams, and contributing to scientific publications.

Lead product strategy and roadmap for AI and data security features—AI discovery, posture management, and data protection. Collaborate with engineering, design, security research, and GTM teams to define, build, and launch capabilities. Engage customers to validate solutions and drive adoption while translating security research into actionable product features.

The Junior Sales Engineer coordinates with Account Representatives, designs technical solutions, delivers training, supports clients, and creates prototypes while ensuring successful implementations.

Lead design and delivery of web modules and microservices for a cloud-native genomics SaaS platform. Implement full-stack features (React/Next.js front end, Java back end), optimize databases, integrate ML components (RAG pipelines, LLM evaluation), and improve SDLC using CI/CD, observability, and DevOps practices while mentoring engineers and collaborating cross-functionally.

Lead global adoption of Pernod Ricard's Matrix MMM platform to optimize marketing investments, advise senior leaders on A&P decisions, drive media effectiveness, shape product roadmap with Data Science and Engineering, lead change management, and build global marketing performance capabilities and governance frameworks to accelerate ROI.

Support identification and implementation of AI-driven business use cases, collaborate with cross-functional teams, analyze impact using data, and provide training on AI tools to improve processes across sales and marketing.

As an AI Solutions Architect, you will design scalable AI architectures, assess technical feasibility, optimize solutions for performance and reliability, and provide technical leadership across teams to ensure successful AI deployments.

The role involves delivering technical solutions, integrating AI/ML models, developing software, and mentoring junior engineers while ensuring customer satisfaction through engagement and solution design.

As a Machine Learning Engineer at Doctrine, you will develop NLP models and conversational agents to streamline legal information access and enhance product features.

The IT/OT Data Engineer is responsible for data collection, architecture development, building data pipelines, and collaborating with data scientists to improve data reliability and efficiency.

Design, build, and deploy AI-driven automation and GenAI solutions for large-scale distributed and cloud environments. Develop ML/LLM models, data pipelines, feature engineering, and model evaluation. Integrate solutions via APIs and orchestration tools, collaborate with global stakeholders, and apply AI to improve network operations, reliability, and customer experience.

Lead product development for Firco Continuity, defining roadmap and AI-driven features to improve screening accuracy, reduce false positives, and automate alert processing. Collaborate with engineering, data science, compliance, and UX; translate regulatory requirements into product specs; ensure scalability, monitor performance, and drive launches and continuous improvements while contributing to positioning, pricing, and lifecycle strategy.

Lead development and deployment of ML/DL image-analysis models to optimize orthodontic manufacturing and quality. Integrate models into production pipelines, refactor C++ to Python, build C# UI, work with PLC hardware, validate training results, and transfer technology across product groups.

Own the Subscriptions roadmap end-to-end: research, prioritize, coordinate cross-product dependencies, drive features through delivery, and enable sales and documentation to maximize retention and revenue.

Work with AAA developers to optimize GPU/system performance for path-traced and neural rendering, develop and tune neural rendering algorithms and AI models, profile and optimize low-level performance, collaborate with architecture and driver teams, and create demos, papers, and presentations for conferences.

As an AI Product Manager, you will lead AI product development, collaborate with teams, conduct market research, and ensure alignment with user needs.

You will leverage your technical expertise and sales leadership to drive revenue growth, build partnerships, and represent technology to engineering companies, focusing on capturing new business opportunities in Europe.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.