Top Machine Learning Jobs in France

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Lead end-to-end ML product roadmaps and initiatives (e.g., Attachment Matcher, Transaction Categorizer). Collaborate with data scientists, engineers, and stakeholders to define, deliver, and monitor ML solutions that drive measurable business value for SMEs across Qonto's platform.

Develop RF signal-processing algorithms for detecting, characterizing, classifying, and identifying emitters across radar, radio, and electronic-warfare systems. Build machine-learning analytics, electronic order-of-battle capabilities, cross-module data-fusion pipelines, and real-time implementations. Prototype in Python or MATLAB, collaborate with software and FPGA engineers, and validate performance using simulated and real-world datasets in laboratory and field environments.

Design and implement resilient navigation and PNT solutions for autonomous platforms operating in contested and GNSS-denied environments. Develop anti-jam and anti-spoof capabilities, multi-sensor fusion, estimation and filtering algorithms, and real-time implementations. Lead integration, prototyping, field validation, architecture reviews, requirements traceability, and technical coordination across hardware, software, EW, GNC, and machine learning teams.

Leads Royal Canin’s Predictive Research team, developing long-term strategies and predictive science portfolios across biological, nutritional, industrial, and clinical R&D data. Provides hands-on guidance in biostatistics, machine learning, data engineering, and cloud analytics; manages multidisciplinary staff, budgets, vendors, governance, infrastructure, intellectual property, and scientific publications. Builds partnerships across Mars, academic institutions, CROs, and biotechnology providers to generate insights supporting pet health, nutrition innovation, and product development.

Designs and deploys enterprise AI-ready data platforms, data lakes, lakehouses, warehouses, pipelines, integrations, and sovereign data spaces. Works directly with customers to assess data ecosystems, identify AI opportunities, define transformation roadmaps, and deliver production-ready solutions and proofs of value. Requires strong expertise in distributed data systems, AI architectures, interoperability standards, cloud technologies, automation, CI/CD, DataOps/MLOps, security, governance, and consulting.

Design and develop bulk and single-cell multi-omics sequencing pipelines, lead omics acquisition strategy, support drug discovery projects, help design biological experiments, and contribute to academic publications and conferences. The role requires strong R, Python, and Bash programming, software engineering practices, and bioinformatics expertise, with opportunities to work on machine learning-based digital twin technology.

Lead and grow a team of Applied Scientists to research, prototype, and productionize AI/ML capabilities across Product Analytics (event understanding, conversational analytics, automated insight reporting, session-replay issue detection). Define technical vision and roadmap, stay hands-on technically, hire and onboard team members, and coordinate delivery with product and engineering stakeholders.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

As a Technical Account Manager, you'll drive customer adoption of AI tools, manage projects, deliver demos, and advocate for user feedback while collaborating across teams to ensure customer success.

Lead Workday Compensation implementations and HCM transformations: run workshops, gather requirements, configure, test, deploy, lead workstreams, liaise with clients and teams, and apply Accenture/Workday methodologies and AI-enabled tools.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Part-time research internship (Alpic + MICS) studying security of LLM + MCP server systems. Investigate attack vectors, develop and train a guardrail classifier to scan MCP inputs/outputs, and train models on Alpic production data. Potential to convert to full-time.

Serve as a pre-sales applied AI architect partnering with GSIs and cloud providers (AWS/GCP) to develop joint GenAI solutions, codify reference architectures, support strategic customer deals, enable partner developer communities, and provide product feedback to inform roadmap and partner strategy.

Design and deploy large-scale ML solutions for adtech: research CTR prediction and online learning, translate papers into production, run A/B tests, monitor live model performance, and collaborate with engineering teams to deliver high-throughput, low-latency prediction systems.

Full-cycle recruiter for an AI safety startup, sourcing and hiring engineering, AI research, product, and business roles across the US and Europe. Build technical pipelines, conduct structured interviews, assess candidates for technical and cultural fit, improve recruiting processes and tooling, and advise hiring managers and leadership.

Lead strategic selling of enterprise AI applications and use cases to Global 1000 customers. Develop account engagement plans, drive business development, collaborate with product and engineering, and expand customer footprints. Serve as a technical-sales leader, translating complex AI/ML concepts into business value. Travel to customer sites up to 50%.

Own Go-To-Market for performance media buyers: build relationships, close and onboard clients, represent Kayzen at industry events, advise prospects on product strategy, and funnel market feedback across teams.

Lead strategy, platform development, and AI-driven analytics for MCC data domains. Align dashboards and KPIs, manage external data and analytics engineers, implement GCP-based data pipelines and Looker reporting, drive GenAI/ML use cases, and partner with stakeholders and the central data office to enforce governance and maximize data-driven decision-making.

Design and deploy ML models and multi-stage data pipelines to measure and predict the causal impact of advertising. Analyze experiments and third-party data, build tooling for A/B test analysis, collaborate with Data/Product/Engineering to bring research to production, and influence bidding strategies at scale.

Design, develop, and operationalize scalable AI and machine learning solutions for enterprise clients. Responsibilities include building and deploying production models, data pipelines, DevOps and MLOps systems, deep learning and generative AI applications, distributed computing solutions, and high-performance simulations. The role involves working with large datasets, optimizing model storage and retrieval, validating business value, conducting AI research, and collaborating with business and technical stakeholders to deliver production-ready systems.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.