AI/ML Engineer at airapps | Paris

At Hugging Face, we are committed to making AI accessible for everyone. Join us in building the fastest-growing platform for AI enthusiasts, boasting over 11 million users who have collectively shared more than 2 million models, 700,000 datasets, and 600,000 applications. Our open-source libraries have garnered over 600,000 stars on GitHub.About the RoleWe are looking for a talented and enthusiastic Open-Source Machine Learning Engineer to join our Paris team. In this pivotal role, you will be responsible for developing, integrating, and maintaining our core library, ensuring that cutting-edge AI for Robotics technology is accessible to our community.Your main responsibilities will include:ML Model Integration & Scaling: Port and scale PyTorch ML models for robotics applications, managing pretraining and large-scale training workflows.Core Library Development: Refactor, manage, and improve the API, architecture, and infrastructure of the core library to ensure robustness, scalability, and user-friendliness.Feature Development & Exploration: Lead the development and deployment of new, robust features while exploring and integrating new technologies relevant to AI and robotics.Community Engagement & Maintenance: Manage and merge community pull requests (PRs), address reported issues, and serve as a technical liaison for the community.Infrastructure & Benchmarking: Implement and maintain integrations with platforms like the Hugging Face Hub, perform benchmarking and profiling to ensure optimal performance, and manage library dependencies.About YouEducation: MS or PhD in Computer Science, Machine Learning, or a related field.Machine Learning Expertise: Hands-on experience with PyTorch and a solid understanding of efficient ML development and deployment abstractions.ML Literature & Systems Knowledge: Familiarity with current robot learning literature and experience in integrating ML models into larger systems.Strong Software Development Skills: Exceptional coding ability (e.g., Python) with experience in building and maintaining complex, production-quality libraries.Software Design & Maintenance: Proven track record in managing the technical lifecycle of a library, including refactoring, maintaining API stability, and dependency management.Bonus Points:Prior contributions to open-source libraries in robotics, particularly on LeRobot.If you are eager to join us but don’t meet every qualification, we still encourage you to apply! We aim to build a diverse team with a wide range of skills, experiences, and backgrounds.

About Mistral At Mistral AI, we harness the transformative power of artificial intelligence to streamline tasks, boost productivity, and foster creativity. Our innovative technology is designed for seamless integration into everyday workflows.We are committed to democratizing AI with high-performance, optimized, and cutting-edge open-source models, products, and solutions. Our extensive AI platform caters to enterprise needs in both on-premises and cloud environments. Among our offerings is le Chat, the AI assistant designed to enhance both personal and professional life.As a dynamic and collaborative team, we are passionate about AI and its potential to revolutionize society. Our diverse workforce thrives in competitive settings, dedicated to driving innovation. With teams located in France, the USA, the UK, Germany, and Singapore, we embody creativity, humility, and a strong team spirit.Join us at Mistral to help shape the future of AI and make a significant impact together. Discover more about our culture at https://mistral.ai/careers.Role SummaryAs a Machine Learning Engineer focused on open-source software, you will be pivotal in releasing state-of-the-art models and enhancing Mistral’s publicly available libraries. Your contributions will facilitate the transformation of research breakthroughs into practical solutions, significantly enriching Mistral's open-source ecosystem.About the Open Source Software TeamOur Open Source Software team collaborates closely with the Science team and various engineering and marketing departments. Members of the OSS team can navigate between production and research roles based on project demands and personal interests.Key Responsibilities• Release our advanced models on open-source platforms and libraries, such as vLLM, GitHub, and Hugging Face.• Maintain Mistral’s open-source libraries, including mistral-common, mistral-finetune, and mistral-inference.• Develop and maintain both internal and external-facing tools and services to support research and open-source initiatives.

Role overview sia is looking for a Machine Learning Engineer based in Paris. This position centers on building and refining machine learning models and algorithms that power sia’s software and platforms. The goal is to develop solutions that address practical, real-world needs. What you will do Design and develop machine learning models that support sia’s products Work closely with colleagues from various teams to address technical challenges Help enhance and evolve AI-driven features across our offerings Team and culture Join a group of professionals who value technology’s influence and enjoy working together on meaningful problems.

Join Our Team as a Machine Learning EngineerAt Harmattan AI, we are pioneering the development of autonomous and scalable defense systems that make a meaningful impact. With our recent $200 million Series B funding, which has propelled our valuation to $1.4 billion, we are expanding our innovative teams to deliver essential systems to allied forces.Our core values include a commitment to technological advancement with real-world applications, a relentless pursuit of excellence, ambitious goal-setting, and tackling the most complex technical challenges. We thrive in an environment where high standards, accountability, and execution are paramount.Role OverviewAs a Machine Learning Engineer on our Foundational team based in Paris, you will be crucial in developing the cognitive capabilities of our tactical robots. Your primary responsibility will be to architect and scale large, multi-modal foundational models that derive robust battlefield representations through Self-Supervised Learning (SSL) from extensive unlabelled Electro-Optical (EO) and Infrared (IR) data. These foundational weights will empower our Edge AI team to create highly accurate models for tactical hardware.Key ResponsibilitiesArchitectural Design: Innovate neural network architectures (such as Vision Transformers) and loss functions (including Masked Autoencoders and Contrastive Learning) to effectively learn from both paired and unpaired EO and IR datasets.Training Infrastructure Management: Oversee and enhance training pipelines across multi-node GPU clusters, optimizing mixed-precision training and data loading processes.Evaluation of Representations: Establish metrics and linear-probing benchmarks to validate that the latent space captures meaningful semantic features prior to model distillation.Data Strategy Development: Assess current EO/IR data lakes and implement cross-attention mechanisms to integrate diverse sensor features.Collaboration: Work closely with Data Engineers on data ingestion pipelines and partner with the Edge AI team to ensure seamless transitions of high-performance models.

About NablaAt Nabla, we are a pioneering team of entrepreneurs, clinicians, and engineers dedicated to revitalizing the joy of practicing medicine.In collaboration with a network of clinician innovators, we have leveraged cutting-edge machine learning technologies to create Nabla: the foremost AI assistant that is reestablishing the vital human connection in healthcare. By optimizing clinical documentation, Nabla empowers clinicians to prioritize what truly matters - patient care. Currently, over 85,000 clinicians from more than 130 healthcare organizations rely on Nabla to enhance their daily care delivery.We are embarking on an exciting journey: Ambient listening, dictation, coding, and command capabilities are merging into a proactive assistant that intuitively improves clinical and financial workflows.With a recent $70M Series C funding, we are expanding our team to build the next generation of clinical AI and enhance the lives of clinicians and patients globally.Join us at this pivotal moment!Leading AI Solutions for HealthcareNabla's impressive growth is the culmination of three years of dedicated product development.Our team, guided by former Meta AI Research engineers, consistently foresees how AI can transform healthcare delivery. The Machine Learning division continually harnesses the latest innovations to realize AI's full potential in healthcare.Notably, Yann LeCun, Meta’s Chief AI Scientist and Turing Award recipient, serves as an advisor to Nabla.Engineering Culture at NablaOur engineering environment is streamlined, agile, and highly technical. Our teams encompass machine learning, native desktop applications, and platform infrastructure to deliver AI solutions in clinical settings reliably and at scale.Your RoleAs a Senior Machine Learning Engineer, you will be instrumental in transforming clinicians’ workflows, enhancing patient care, and ensuring Nabla stays at the forefront of AI advancement. You will take the lead on impactful projects and play a key role in the maturation of our products, contributing to the overall success of our mission.

Role overview Ubisoft Entertainment S.A. seeks a Machine Learning Engineer (H/F/NB) for its Paris team. The role centers on designing AI solutions that enhance gameplay and introduce new features for players. What you will do Create and refine machine learning models to support both game development and player engagement. Use data analysis to guide and improve AI-powered features. Work closely with other teams to bring machine learning solutions into Ubisoft games. Location This role is located in Paris.

Role Overview iliad-free is hiring a Machine Learning Engineer in Paris. This position focuses on developing and improving products with advanced machine learning techniques, including work with large language models (LLMs). The role sits within the tech and digital teams, where close collaboration drives new solutions for telecommunications challenges. What You Will Do Work alongside technical and digital colleagues to design, build, and refine machine learning models Apply modern algorithms and technologies to real-world product needs Contribute ideas and code that shape current and future projects Impact Results from this work help iliad-free stay competitive and innovative within the telecommunications sector. Contributions in this role have a direct effect on ongoing and upcoming projects.

About UsAt MARGO, our consultants focus on what truly matters: tackling complex projects that combine intellectual challenges with real business impact.This is why we support leading players in finance, industry, and technology on their most strategic projects in Data Science, Machine Learning, and Artificial Intelligence.Why Join the AI Practice?You will be part of a team led by Hamza Bouanani, the AI Practice Manager at MARGO, and Lead Data Scientist at BNP Paribas.Working alongside him means joining a team of passionate experts, being technically and methodologically challenged, and contributing to high-impact projects for clients.Your ResponsibilitiesWe are seeking a Machine Learning Engineer to join our teams and engage at the heart of our clients' Data strategies (Industry, Finance, Energy). Your primary objective will be to industrialize Machine Learning algorithms and ensure their production lifecycle.You will operate on three major technical axes:1. Industrialization & Deployment (Model Serving)- Transforming research models (Proof of Concept) into robust, tested, and optimized production code.- Developing high-performance APIs (FastAPI, Flask) to expose models to business applications.- Containerizing solutions (Docker) and orchestrating on clusters (Kubernetes) to ensure scalability and high availability.2. MLOps Architecture & Automation- Designing and maintaining CI/CD pipelines dedicated to Machine Learning (automated retraining, model validation).- Implementing and managing data flow orchestration tools (Airflow, Kubeflow, Dagster).- Managing versioning of data and models (DVC, MLflow) to ensure reproducibility of experiments.

Join our dynamic team at Ubisoft as a Senior Machine Learning Engineer focusing on cutting-edge AI initiatives. In this role, you will leverage your deep understanding of machine learning algorithms and data analytics to develop innovative solutions that enhance our gaming experiences. Collaborate with cross-functional teams to drive AI projects from conception to implementation, ensuring top-notch performance and scalability.

Join our dynamic team at iliad-free in Paris as a Machine Learning Engineer Intern. This is an exciting opportunity for students or recent graduates to gain hands-on experience in the world of machine learning and large language models (LLM).As an intern, you will work closely with our talented engineers to develop innovative solutions that leverage advanced machine learning techniques. You will have the chance to contribute to real projects and enhance your skills in a collaborative environment.

Become a pivotal member of the Ubisoft AI Initiatives team, where you will help shape the future of information management at Ubisoft. Our projects range from advanced hybrid search systems to sophisticated agentic reasoning applications, all aimed at converting raw data into actionable insights for rapid decision-making. If you are eager to redefine the interaction between humans and AI in solving intricate challenges, this is the perfect opportunity for you.We are looking for a talented Senior Machine Learning Engineer who will be responsible for designing, constructing, assessing, and refining AI models and intelligent systems that drive our applications. Your work will bridge the fields of machine learning research, large-scale data systems, and production engineering, converting state-of-the-art AI innovations into solid, scalable solutions.Key ResponsibilitiesAI System Design & Optimization: Craft, refine, and enhance machine learning models, including those based on large language models (LLMs), retrieval methods, and multimodal systems for practical application.Development of Intelligent Retrieval & Agentic Pipelines: Create and enhance retrieval-augmented generation (RAG) pipelines and agent-based workflows, incorporating embeddings, vector searches, orchestration, and evaluation methodologies.Insight Extraction from AI Utilization: Utilize internal AI platform data (chat interactions, prompts, usage logs) to conduct topic extraction, clustering, and trend analysis, transforming usage patterns into actionable product insights.Model Production & Scaling: Deploy, supervise, and optimize machine learning models in cloud-native environments, ensuring they are scalable, reliable, and cost-effective.Performance Evaluation & Enhancement: Establish evaluation metrics, conduct experiments, and continuously enhance model quality, robustness, and user impact.Collaborative Engineering & Product Integration: Work closely with software engineers, site reliability engineers (SREs), and product teams to integrate AI systems within scalable architectures and deliver impactful solutions.

Our Mission? To empower small and medium-sized enterprises (SMEs) to thrive in their business endeavors and beyond by offering Europe's premier financial workspace. We seamlessly integrate advanced business tools—such as efficient invoicing, comprehensive spend management, and intuitive pre-accounting—with dedicated support available 24/7, enabling businesses to effortlessly navigate their financial landscape.Our Journey: Since our inception in July 2017, founded by Alexandre and Steve, Qonto has rapidly established trust, now serving over 600,000 clients. Our dedicated team of 1,600+ Qontoers has propelled us to be recognized in the LinkedIn Top Companies ranking in France!Our Values:Customer Commitment | We prioritize customer needs in every decision.Responsibility | Take ownership and drive results.Collaboration | Make teamwork seamless and productive.Excellence | Continuously strive to exceed expectations.Integrity | Uphold ethical standards and respect for all.Our Commitment to Diversity: At Qonto, we believe in cultivating an inclusive environment that fosters growth for everyone. We assess candidates based on their skills and potential, with an emphasis on diversity—currently comprising 55% international team members, 44% women, and 20% parents. Join us in shaping a workplace that values diversity and individual contributions.Learn about our initiatives for a discrimination-free hiring process.Join our AI Product team as a Senior Machine Learning Engineer to innovate and deploy AI solutions for over 500,000 business clients, leveraging Generative AI alongside established machine learning techniques.

Join our innovative team at Winamax as a Senior Machine Learning / AI Engineer. You will play a pivotal role in developing and implementing machine learning models that drive our data analytics and enhance user experiences. If you are passionate about harnessing AI technologies and enjoy working in a dynamic environment, we invite you to apply!

TLDR: We are seeking a skilled Machine Learning Engineer / MLOps Specialist to take ownership of our inference stack, optimizing serving engines and developing vector search pipelines. Your role will involve bridging the gap between Research and Product to deliver models that are efficient, cost-effective, and ready for production.About UsWhite Circle is an AI Safety company dedicated to enhancing the safety, reliability, and optimization of AI systems. Our platform is centered around defining straightforward, natural-language policies that dictate the appropriate and inappropriate behaviors of AI models. We continually test, enforce, and enhance these policies at scale to ensure optimal performance.We have successfully raised $11M from leading investors, founders, and executives from prominent organizations, including OpenAI, Anthropic, Hugging Face, Mistral, DeepMind, Datadog, and Sentry.Our infrastructure handles over 100 million API calls each month.We specialize in fine-tuning and training our own large language models (LLMs) to operate faster and more economically than any competing open or proprietary models.Your ResponsibilitiesOversee the end-to-end inference infrastructure: enhance latency, throughput, and cost efficiency across our model fleet.Develop and scale model serving solutions using TensorZero, vLLM/SGlang/TRT, and Kubernetes.Design and maintain vector search pipelines utilizing vector storage technologies.Demonstrate familiarity with support metrics (SLAs, FCR, deflection) and define service health KPIs.Transform research outcomes into practical applications: collaborate with the research team, assess production readiness, and manage deployment processes including formatting and sampling parameters.Your QualificationsA minimum of 3 years of experience in deploying high-performance ML systems in production, beyond just training notebooks.In-depth experience with inference optimization, including troubleshooting latency issues and understanding the differences between theoretical and actual throughput.Proficient across the tech stack: from CUDA kernels to Kubernetes manifests and Grafana dashboards.Preferred Qualifications: Experience with Rust, custom Triton kernels, and performance benchmarking.Why Join White Circle?Competitive salary ranging from $100,000 to $150,000 plus equity options.20 days of paid vacation annually.Opportunity to work from Paris with a hybrid work model, including a relocation package.Access to top-tier medical insurance in France.

Ubisoft Entertainment S.A. seeks a Team Lead Machine Learning Engineer in Paris to guide a group of engineers focused on enhancing gaming experiences through advanced machine learning techniques. This leadership role centers on both technical direction and team development within a creative environment. Key Responsibilities Lead a team of machine learning engineers, providing support and direction on project work. Foster collaboration and knowledge sharing among team members. Supervise the design, development, and deployment of machine learning solutions for gaming projects. Role Focus This position emphasizes both hands-on technical oversight and people management. The team works on projects that apply advanced machine learning to improve player experiences in Ubisoft games.

About Mistral AIAt Mistral AI, we harness the transformative power of artificial intelligence to streamline processes, save time, and boost creativity and learning. Our innovative technology seamlessly integrates into everyday professional environments, enhancing efficiency and productivity.We democratize artificial intelligence through a suite of high-performance, optimized, open-source models and solutions. Our extensive AI platform caters to both enterprise and individual needs, featuring Le Chat, La Plateforme, Mistral Code, and Mistral Compute - a groundbreaking collection that delivers state-of-the-art intelligence to users.Our dynamic and collaborative team is passionate about the potential of AI to revolutionize society. Comprising a diverse workforce spread across France, the USA, the UK, Germany, and Singapore, we thrive in competitive settings and are dedicated to fostering innovation. We pride ourselves on being creative, humble, and team-oriented.Join us in shaping the future of AI and making a significant impact in the field. Explore more about our culture at https://mistral.ai/careers.Mistral AI participates in the E-Verify programRole OverviewResearch Engineering Team IntroductionOur Research Engineering team encompasses both the Platform (shared infrastructure & clean code) and Embedded (integrated within research squads) divisions. Engineers have the flexibility to shift along the research-to-production spectrum based on evolving interests and requirements.As a Research Engineer focused on Machine Learning, you will be instrumental in building and optimizing large-scale learning systems that underpin our open-weight models. Collaborating closely with Research Scientists, you will have the opportunity to join either:- **Platform RE Team**: Enhance the foundational training frameworks, data pipelines, and cluster tools utilized by all teams; or- **Embedded RE Team**: Integrate directly within a research squad (such as Alignment, Pre-training, Multimodal, etc.) and transform innovative ideas into scalable, repeatable code.Location: Paris / London (hybrid) or remote within EU/UKKey Responsibilities• Facilitate researchers by managing the intricate aspects of large-scale ML pipelines and developing robust tools.• Bridge cutting-edge research with production: integrate model checkpoints, streamline evaluation processes, and expose APIs.• Conduct experiments utilizing the latest deep-learning methodologies (including sparsified 70B+ runs and distributed training on thousands of GPUs).• Design, implement, and benchmark ML algorithms, while producing clear, efficient code.

Join Squad Maât at Doctrine as a Senior Machine Learning Engineer. In this role, you will collaborate with cutting-edge technologies and lead innovative projects that shape the future of machine learning. Your expertise will be pivotal in enhancing our predictive models and optimizing data-driven solutions.

About the Institute of Foundation ModelsThe Institute of Foundation Models is a premier research laboratory committed to the development, comprehension, application, and risk management of foundation models. Our mission is to propel advancements in research, cultivate the next generation of AI innovators, and contribute significantly to a knowledge-driven economy.Joining our team provides a unique opportunity to engage with cutting-edge foundation model training alongside distinguished researchers, data scientists, and engineers. You will confront some of the most fundamental and impactful challenges in AI development while contributing to the creation of revolutionary AI solutions capable of transforming entire industries. Your strategic and innovative problem-solving abilities will be crucial in positioning MBZUAI as a global center for high-performance computing in deep learning, facilitating groundbreaking discoveries that will inspire future AI trailblazers.The RoleAs a Research Engineer focused on speech and audio machine learning, you will serve as the link between research and production constraints, ensuring competitive performance. You will oversee the complete performance lifecycle of our machine learning speech systems, from designing scalable training infrastructures to achieving ultra-low-latency inference capabilities.

Quick Overview: In this role, you'll be at the forefront of AI development, training and refining vision-language models, extending their capabilities to video, creating alignment pipelines, developing evaluation benchmarks, optimizing production inference, and engaging with MoE architectures.About UsWhite Circle is a pioneering AI Safety organization dedicated to building a robust safety, reliability, and optimization framework for AI systems. Our platform operates on straightforward natural-language policies that dictate the appropriate behaviors of AI models. We automate the testing, enforcement, and ongoing enhancement of these policies at scale.We have successfully raised $11 million from prominent investors, including founders and senior leaders from OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and more.Our infrastructure processes over 100 million API calls every month.We specialize in fine-tuning and training our proprietary LLMs to ensure faster and more cost-efficient performance than any available open or proprietary models.We are a compact, highly motivated team. If you are eager to tackle challenging problems, get your work deployed rapidly, and significantly impact the construction of AI safety – we want to hear from you.Your Responsibilities:Train vision-language models from the ground up and fine-tune existing architectures for advanced image understanding.Expand VLM capabilities to video by designing innovative temporal modeling approaches and efficiently managing long-context.Develop impactful evaluation benchmarks focusing on visual QA, spatial reasoning, and video comprehension.Curate and maintain multimodal datasets, including creating synthetic data generation pipelines.Train and optimize MoE architectures to enhance multimodal inference efficiency.Deploy models into production, focusing on quantization, batching strategies, and latency optimization.You Will Excel If You Have:3+ years of experience in training and fine-tuning vision-language models (e.g., LLaVA, Qwen-VL, InternVL).A strong background in multimodal architectures, with a clear understanding of how vision encoders, projectors, and LLMs integrate.Hands-on experience with RLHF/alignment for multimodal systems, specifically GRPO, DPO, and reward modeling.Experience in video understanding, including temporal modeling and efficient attention mechanisms.