Top Machine Learning Jobs in France

Leads consultative discovery, technical qualification, solution design, executive presentations, and sales campaigns for AspenTech industrial software. Partners with sales teams to align technology with measurable customer value, develops industry-specific messaging, engages senior executives, provides product feedback, coaches sales personnel, and represents the company at industry events. Requires extensive industrial software or solution consulting experience, technical domain expertise, multilingual fluency, and European work authorization.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Leads ESD protection strategy, architecture, design, validation, and sign-off for analog, mixed-signal, high-voltage, automotive, and industrial semiconductor products. Defines methodologies and roadmaps, investigates failures, collaborates across technology, package, validation, and systems teams, and develops simulation and AI-assisted design methods. Provides technical leadership, mentors engineers, supports customer escalations, and drives innovation through patents, publications, and research partnerships.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

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.

Conduct research across the full machine learning lifecycle, including ideation, model design, implementation, evaluation, training, inference optimization, and deployment. Develop novel machine learning methods and foundation models, establish evaluation protocols, scale training with GPUs or TPUs, and improve research engineering infrastructure for rapid experimentation.

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.

Build end-to-end data solutions for the U.S. Space Force’s PNT SE&I team using Palantir Foundry. Responsibilities include gathering requirements, developing applications and reports, transforming and modeling data, integrating REST APIs and enterprise systems, optimizing pipelines and datasets, and providing technical support, documentation, and training. The role is onsite in El Segundo and requires an active Secret clearance plus extensive related experience.

Lead pharmacovigilance domain expertise for Veeva Falcon by guiding safety case workflows, evaluating AI-driven outputs, shaping PV automation strategy, engaging early adopters, and designing complex stress-test scenarios. The role bridges hands-on drug safety operations with product and engineering teams to improve platform accuracy, compliance, and customer value.

Develop RF and radar signal-processing algorithms for detecting, characterizing, classifying, and identifying emitters in contested environments. Build electronic order-of-battle analytics, apply machine learning to modulation recognition and anomaly detection, fuse Radar, Radio, and Electronic Warfare data, and transition prototypes from MATLAB/Python into real-time implementations with software and embedded/FPGA teams. Validate performance using simulated and real-world datasets in laboratory and field conditions.

Develop and optimize real-time algorithms for 3D LiDAR perception, including point-cloud clustering, classification, semantic segmentation, and ground detection. Responsibilities include researching solutions, designing algorithmic improvements, creating evaluation datasets, integrating modules into C++ software, conducting unit and system testing, characterizing performance, and documenting results. The role requires machine learning and deep learning expertise, independent ownership, collaboration, and fluent English.

Develop and optimize real-time algorithms for 3D LiDAR perception, including point-cloud clustering, classification, semantic segmentation, and ground detection. Responsibilities include researching solutions, designing algorithm modules, building evaluation datasets, integrating developments into C++ software, conducting unit, performance, and system testing, and documenting results. The role requires collaboration across teams while independently owning algorithmic projects.

Develop predictive models, analyze structured and unstructured datasets, and support data-informed product decisions. Responsibilities include designing and validating machine learning algorithms, collaborating with product, engineering, and business teams, and improving data quality, reliability, and scalability in analytics workflows.

Lead operations consulting engagements across sourcing, procurement, supply chain, manufacturing, process operations, and digital operations. Break down complex problems, direct junior consultants, conduct sophisticated analyses, develop recommendations, collaborate with clients, and manage small project teams. Candidates should bring 4–8 years of relevant experience, sector expertise, strong analytical and communication skills, fluency in English and French, and willingness to travel.

Build and scale ML platform infrastructure, deploy production machine learning models, and maintain MLOps pipelines with version control, CI/CD, monitoring, and reliability practices. Develop tools and frameworks that streamline model deployment, collaborate with data scientists and engineers on end-to-end AI solutions, resolve production issues, and document and promote MLOps best practices across the technology organization.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Design, prototype, evaluate, and ship AI agents and reusable skills for product and analytical challenges. Build agent evaluators, guardrails, golden datasets, retrieval systems, and LLM-powered diagnostics. Collaborate with Product, R&D, GTM, and Design teams to frame ambiguous problems, analyze large datasets, develop predictive models, and create actionable insights. The internship requires a builder mindset, strong analytical ability, and proficiency in Python, SQL, data pipelines, and visualization.

Supports enterprise software sales by presenting Aera’s Decision Intelligence platform, conducting tailored demos, leading proofs of concept and value, facilitating workshops, developing ROI analyses and business cases, responding to proposals and RFx requests, and defining deployment roadmaps. Partners with sales, product management, marketing, delivery, and customer success teams while engaging technical and executive stakeholders. The role requires supply chain expertise, consultative communication, and approximately 25% travel.

Own the full sales cycle for technically complex B2B deals involving APIs, on-premises deployments, and custom licensing. Manage multi-stakeholder negotiations, build strategic customer relationships, drive retention and expansion, and develop sales processes in an early-stage environment. Collaborate with engineering, research, product, solutions engineering, and legal teams while translating customer needs into product feedback.

Develop Python tools for quantitative trading research, improve simulation and backtesting frameworks, collaborate with quantitative researchers to enhance trading strategies, and support EMEA-focused research. The intern will work with distributed global teams and gain exposure to large-scale systems, workflow orchestration, and production-grade software engineering practices.

Supports responsible enterprise AI adoption by monitoring market trends, evaluating AI solutions, assisting onboarding and rollout, and developing training, coaching, guidance, and communications. Provides user support on prompting and agentic AI, identifies adoption barriers, translates technical developments into business language, and promotes compliant, productive AI use across workforce teams.

Own production optimization of LLM and VLM inference systems, improving latency, throughput, memory efficiency, GPU utilization, quality, reliability, and cost. Deploy and benchmark inference engines, build compression and quantization workflows, implement acceleration techniques, diagnose serving bottlenecks, and collaborate with kernel, platform, research, product, and customer teams.

Lead enzyme screening and biocatalytic process development for small-molecule APIs. Apply reaction engineering, kinetic modeling, DoE, machine learning, and robotics to optimize and scale processes, transfer to pilot scale, document results, and drive digital transformation across international multidisciplinary teams.

Build end-to-end machine learning systems spanning research reproduction, model evaluation, inference infrastructure, backend services, and product interfaces. Design rigorous experiments, evaluation datasets, and verification workflows; analyze model internals; investigate provenance and evasion; and convert findings into reliable production systems with APIs, background jobs, observability, testing, documentation, and user-facing React/TypeScript experiences.