17 jobs found in france

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. Transformers in NLP pushed forward the computational requirements and the trend started to expand to other modalities such as Computer Vision and Speech which are actively adopting Transformer architectures to build the latest state-of-the-art models. About the Role Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models. Workload efficiency is key to our mission of democratizing state of the art and we are...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 76K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the Role As a ML Engineer, you will work to improve the open-source accessibility of Document AI models and datasets. You will work towards creating datasets and training models from scratch, reproducing and building on top of the state-of-the-art Document AI techniques, in an effort to broaden open-source use cases and increase the availability of models with permissive licenses. You will get to work with a number of open-source tools, including but not limited to: Transformers, Datasets,...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to technology development for the better. We have built a platform in which over 100,000 models and thousands of demos and datasets are shared. From Computer Vision to Natural Language Processing and Audio, lots of communities are collaborating through the Hugging Face Hub to do open-source Machine Learning. About the Role As a Machine Learning Integrations Engineer, you will be key in driving the adoption of the Hub platform and open-source technologies by creating, fostering, and growing communities and developing tools to improve the developer experience. You’ll collaborate closely with the Open Source, Science, and Product teams. In your day-to-day, you would lead integrations with different Open Source libraries from the ecosystem and engage with external research groups to help them share their models and datasets on the Hub. You'll...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the Role For this position, you will deploy and benchmark transformer models for both training and inference on several cutting-edge hardware accelerators supported by the Optimum library . This internship will aim at writing an open-source tool for benchmarking models on numerous tasks and at publishing the results in various ways, such as (but not limited to): Lead a common Hugging Face/Habana submission to the MLPerf benchmark . This will consist in getting the best training time and...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the Role For this position, you will make cutting-edge diffusion model systems more accessible to the open-source community, focusing on image, audio, and video generation models. The primary focus of this internship will be on improving the sampling speed of large diffusion models through distillation or by implementing new sampling techniques. You will work in existing open-source libraries, such as Diffusers, Transformers, and Accelerate, to rapidly add new, exciting features and boost the...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the Role During your internship on code generation, you will work with the open-source and science team at Hugging Face to broaden the accessibility of machine learning models for code. You’ll get to contribute to initiatives such as CodeParrot and BigCode and use open-source libraries, such as Transformers, Datasets, Accelerate, or Megatron-LM. You will develop tools to prepare large-scale datasets, train language models for code, and evaluate them on code benchmarks with the goal to foster...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the Role Speech recognition models are getting bigger, but practitioners need something smaller. As a Research Engineer for Efficient Speech Recognition, you will work on a 3-6 month research project investigating how state-of-the-art speech models can be made more accessible to the open-source community. This is a hybrid open-source / open-science role at the intersection of engineering and science. This project will be closely integrated into existing open-source libraries, such as...

As an early member of Hugging’s Face’s Success team, you will help leading companies successfully use AI. Companies range from cutting-edge startups to Fortune-500 giants. On a typical day, you might be advising data science teams on best practices for building models, writing a Jupyter notebook to show off a new technique developed by our researchers, researching the best way to adapt models to a niche domain, or working on a technical blog post. Your technical ability and drive to help others are key. With that, you will help the most sophisticated customers unlock the value of AI. What you are expected to do: Empathize with our customers to understand their issues and goals when using transformers (NLP and Vision primarily). Have the scrappiness and be excited to solve customer problems through research, coding up a solution, or talking to our many in-house experts. Build meaningful relationships with our customers and understand their goals. Comfortably explain...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. As an early member of Hugging’s Face Machine Learning Engineering Success team, you will play a critical role in driving successful technical engagements with prospects and customers and be an integral part of our overall enterprise sales process. You ask the right questions to quickly understand the customer's Machine Learning pain points and environment and articulate clearly and concisely the best possible technical solutions. You are curious and an avid learner. Most of all, you care about the...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. About the Role Since the launch of Hugging Face, we have experienced healthy growth and steady market demand. Our solutions are already used by +5000 users and +300 paid customers. As our first Account Executive in Europe (ideally in Paris or London), you’ll play a key role in building our portfolio of customers and driving our success. You’ll be responsible for the entire sales cycle, while being able to leverage company resources, to reach a successful collaboration with our prospects and customers. About you You'll love working here if you have a passion for new technologies and data. You are excellent at building deep relationships with prospects and customers. What matters to you is helping them build their Data strategy and find the right solutions. You have experience closing deals...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the role During this internship, you will work with the open-science and open-source teams at Hugging Face to help develop a fast and flexible framework for training large - 100 billion or above - Transformer models over distributed computing infrastructure. You’ll test and integrate features from cutting-edge research papers, and help make state-of-the-art innovations accessible to all, concentrating on scalability and speed - the key ingredients that make today’s large model research...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to technology development for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, and collaborations with dozens of open-source groups and researchers. About the Role As a Machine Learning Advocate Engineer for Audio , you will have a key role in driving the adoption of the Hub platform and Open Source technologies by creating, fostering, and growing communities, extending the use cases of the Hub, developing tools to improve the developer experience, and bringing feedback to the team. You’ll collaborate closely with the Open Source, Science, and Product teams. This is not a marketing position! Developer Advocacy at Hugging Face is deeply technical and having a generalist...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to technology development for the better. We have built a platform in which over 100,000 models and thousands of demos and datasets are shared. From Computer Vision to Natural Language Processing and Audio, lots of communities are collaborating through the Hugging Face Hub to do open-source Machine Learning. About the Role As a Machine Learning Advocate Lead , you will have a key role in driving the adoption of the Hugging Face Hub platform and Open Source technologies by contributing to the OS ecosystem in different domains and verticals (Computer Vision, Biotechnology, Healthcare, Art, etc), crafting tools to improve developer experience, and extending the use cases of the Hub. You’ll collaborate closely with Open Source, Research, and Product teams. As an experienced engineer and advocate, you will be crucial in mentoring other team members,...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. Hugging Face has a thriving open-source ecosystem with all backgrounds (from ML Researchers to students interested in model biases). With over a dozen open-source projects, an amazing community, and thousands of contributors and collaborators, this position is an opportunity to have an impact across the ecosystem. About the Role As a ML Community Builder , you will be key in driving the adoption of the Hugging Face Hub Open Source technologies and platform by scaling the community efforts and contributing to the OS ecosystem. You’ll collaborate closely with Open Source, Advocacy, Research, and Product teams. You'll get to foster and scale healthy machine learning communities. You'll also get to help users contribute to the tools HF builds, organize community events, and interact with researchers,...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the Role As a Machine learner, you will work mainly with existing open-source libraries, such as Transformers and Accelerate to boost the support for all the new advances in model training and fine-tuning such as DeepSpeed, fair scale, and all forms of model parallelism. You'll get to foster one of the most active machine-learning communities, helping users contribute to and use the tools that you build. You'll interact with Researchers, ML practitioners, and data scientists on a daily basis...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. Hugging Face has become the most popular, community-driven project for training, sharing, and deploying the most advanced machine learning models. Workload efficiency is key to our mission of democratizing state of the art and we are always looking to push the boundaries for faster, and more efficient ways to train and deploy models. About the Role If you are passionate about building Machine Learning solutions used by millions leveraging the cloud stack and services of Cloud Service Providers:...

Here at Hugging Face, we’re on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M+ installs and 65K+ stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. About the Role As a Developer Advocate Engineer , you will have a key role in driving the adoption of the Hub platform and Open Source technologies by creating, fostering and growing communities, extending the use cases of the Hub, developing tools to improve the developer experience, and bringing feedback to the team. You’ll collaborate extremely closely with both the Open Source, Science and Product teams. This is not a marketing position! Developer Advocacy at Hugging Face is deeply...