Hugging Face

Role Description Roles at Hugging Face are very fluid and dynamic -- we're looking for someone who is comfortable taking on different challenges that evolve over time. This role sits on the Xet Storage team, the group responsible for the storage system behind all of Hugging Face. Today we store over 200PB (and growing rapidly!) of the world's most important ML & AI assets. Xet is the underlying storage architecture for the entire Hugging Face platform and community -- from the largest model repositories to the datasets and Spaces that millions of people build on every day. In this role, you'll work across two closely connected surfaces: - Contribute to xet-core, our open-source project written in Rust that powers hf-xet -- the Python library underpinning the Hugging Face Hub client and the wider ecosystem of open-source tools the community relies on. - Design, build, and operate meaningful and challenging features in the Xet Storage backend, contributing to the broader Infrastructure organization at Hugging Face. We're a small team building and operating incredible things at enormous scale, in a high-trust, low-process, async, and remote environment -- and we lean heavily on the latest AI tools to move fast. If you love writing low-level, high-performance code and are energized by the challenge of large-scale, scalable services, this is the team for you. This usually means proven experience building and operating production systems software, but we consider every applicant on an individual basis. Qualifications - 8+ years building and scaling distributed systems, storage, or networking infrastructure. - Proficiency in a low-level systems language, with Rust strongly preferred (we also work in Python, Typescript, Go, and C++ across the stack). - A track record of working independently in a high-trust, low-process environment -- you're comfortable with ambiguity and take ownership end to end. - Comfort operating in a fast-moving, async, and fully remote environment. - A passion for building simple, robust, and scalable systems relied on by engineering and science teams around the world. Requirements - Experience designing efficient, high-performance, fault-tolerant data storage and retrieval systems. - Experience operating production systems -- monitoring, alerting, and distributed debugging and recovery. - Familiarity with git internals, cloud infrastructure (AWS, Azure, GCP, Kubernetes), databases (relational and non-relational), or networking. Benefits - Flexible working hours and remote options. - Health, dental, and vision benefits for employees and their dependents. - Parental leave and flexible paid time off. - Reimbursement for relevant conferences, training, and education. - Company equity as part of the compensation package.

Role Description Roles at Hugging Face are very fluid and dynamic -- we're looking for someone who is comfortable taking on different challenges that evolve over time. This role sits on the Xet Storage team, the group responsible for the storage system behind all of Hugging Face. Today we store over 200PB (and growing rapidly!) of the world's most important ML & AI assets. Xet is the underlying storage architecture for the entire Hugging Face platform and community -- from the largest model repositories to the datasets and Spaces that millions of people build on every day. In this role, you'll work across two closely connected surfaces: - Contribute to xet-core, our open-source project written in Rust that powers hf-xet -- the Python library underpinning the Hugging Face Hub client and the wider ecosystem of open-source tools the community relies on. - Design, build, and operate meaningful and challenging features in the Xet Storage backend, contributing to the broader Infrastructure organization at Hugging Face. We're a small team building and operating incredible things at enormous scale, in a high-trust, low-process, async, and remote environment -- and we lean heavily on the latest AI tools to move fast. If you love writing low-level, high-performance code and are energized by the challenge of large-scale, scalable services, this is the team for you. This usually means proven experience building and operating production systems software, but we consider every applicant on an individual basis. Qualifications - 8+ years building and scaling distributed systems, storage, or networking infrastructure. - Proficiency in a low-level systems language, with Rust strongly preferred (we also work in Python, Typescript, Go, and C++ across the stack). - A track record of working independently in a high-trust, low-process environment -- you're comfortable with ambiguity and take ownership end to end. - Comfort operating in a fast-moving, async, and fully remote environment. - A passion for building simple, robust, and scalable systems relied on by engineering and science teams around the world. Requirements - Experience designing efficient, high-performance, fault-tolerant data storage and retrieval systems. - Experience operating production systems -- monitoring, alerting, and distributed debugging and recovery. - Familiarity with git internals, cloud infrastructure (AWS, Azure, GCP, Kubernetes), databases (relational and non-relational), or networking. Benefits - Flexible working hours and remote options. - Health, dental, and vision benefits for employees and their dependents. - Parental leave and flexible paid time off. - Reimbursement for relevant conferences, training, and education. - Company equity as part of the compensation package. - Opportunity to visit office spaces in NYC and Paris. - Support for a community that collaborates across the ML/AI field.

Role Description Roles at Hugging Face are very fluid and dynamic -- we are looking for someone who is comfortable taking on different challenges that will evolve over time. In the short term, the focus of this role is to help develop Gradio (www.gradio.dev), a Python framework that lets users build machine learning web apps, and Trackio, a local-first, agent-friendly experiment tracking platform (https://github.com/gradio-app/trackio). Gradio and Trackio are used by more than 1 million developers each month, locally and to launch apps on Hugging Face Spaces. These apps have allowed machine learning to be accessible to a wide audience -- for the first time in history, anyone with an internet connection can use cutting-edge machine learning models right from their browser. - Designing, developing, and maintaining core features for Gradio and Trackio, ensuring scalability, reliability, and ease of use for ML developers. - Architecting complex Python projects and frameworks that serve as foundational tools for the ML community. - Collaborating with open-source contributors and engaging with the broader community through code reviews, discussions, and support. - Integrating modern frontend technologies to create seamless and intuitive user experiences for Python-based web applications. - Adapting to evolving engineering challenges and contributing to the direction of our developer tools as the landscape changes. Qualifications - Bachelor’s degree or equivalent in Computer Science or a related field - 5+ years of professional Python development experience - Experience architecting complex Python projects or frameworks - Professional experience with JavaScript or TypeScript - Professional experience with a modern frontend framework such as React or Svelte - Experience contributing to or maintaining open-source software projects Requirements - If you're interested in joining us, but don't tick every box above, we still encourage you to apply! We're building a diverse team whose skills, experiences, and backgrounds complement one another. We're happy to consider where you might be able to make the biggest impact. Benefits - Flexible working hours and remote options. - Health, dental, and vision benefits for employees and their dependents. - Parental leave and flexible paid time off. - All employees have company equity as part of their compensation package. - Reimbursement for relevant conferences, training, and education. - Opportunity to visit office spaces in NYC and Paris for remote employees. - Workstation outfitting to ensure success.

Role Description Roles at Hugging Face are very fluid and dynamic -- we are looking for someone who is comfortable taking on different challenges that will evolve over time. In the short term, the focus of this role is to help develop Gradio (www.gradio.dev), a Python framework that lets users build machine learning web apps, and Trackio, a local-first, agent-friendly experiment tracking platform (https://github.com/gradio-app/trackio). Gradio and Trackio are used by more than 1 million developers each month, locally and to launch apps on Hugging Face Spaces. These apps have allowed machine learning to be accessible to a wide audience -- for the first time in history, anyone with an internet connection can use cutting-edge machine learning models right from their browser. - Designing, developing, and maintaining core features for Gradio and Trackio, ensuring scalability, reliability, and ease of use for ML developers. - Architecting complex Python projects and frameworks that serve as foundational tools for the ML community. - Collaborating with open-source contributors and engaging with the broader community through code reviews, discussions, and support. - Integrating modern frontend technologies to create seamless and intuitive user experiences for Python-based web applications. - Adapting to evolving engineering challenges and contributing to the direction of our developer tools as the landscape changes. Qualifications - Bachelor’s degree or equivalent in Computer Science or a related field - 5+ years of professional Python development experience - Experience architecting complex Python projects or frameworks - Professional experience with JavaScript or TypeScript - Professional experience with a modern frontend framework such as React or Svelte - Experience contributing to or maintaining open-source software projects Requirements - If you're interested in joining us, but don't tick every box above, we still encourage you to apply! - We're building a diverse team whose skills, experiences, and backgrounds complement one another. - We're happy to consider where you might be able to make the biggest impact. Benefits - Flexible working hours and remote options. - Health, dental, and vision benefits for employees and their dependents. - Parental leave and flexible paid time off. - Reimbursement for relevant conferences, training, and education. - All employees have company equity as part of their compensation package. - Opportunity to visit office spaces in NYC and Paris for remote employees. - Workstation outfitting to ensure success.

Role Description As an Open-Source Machine Learning Engineer, you'll work to improve the open-source machine learning ecosystem. You'll mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch, and vLLM, and you'll interact with users and contributors across the broad open-source ML ecosystem. We'll brainstorm with you to put you in a position to do the work that interests you and that is impactful. - Help foster one of the most active machine learning communities. - Assist users in contributing to and using the tools you build. - Collaborate with researchers, ML practitioners, and data scientists through GitHub, forums, and Slack. Qualifications - Strong Python skills, with experience writing clean, well-tested, maintainable library code. - Deep hands-on experience with a modern deep-learning framework, especially PyTorch (JAX or TensorFlow a plus). - Practical experience with the Hugging Face open-source stack (Transformers, Datasets, Accelerate) or comparable ML libraries. - A public track record of open-source contributions, for example merged pull requests to ML or data libraries, that we can review on GitHub. - Solid understanding of modern machine learning and deep learning, including transformer architectures. - Experience collaborating with a technical community in the open (GitHub issues and reviews, forums, Slack or Discord). - Fluent written English for asynchronous collaboration across a distributed, global community. Requirements - Experience maintaining an open-source project (nice to have). - Prior contributions to Transformers, Datasets, Accelerate, or similar libraries (nice to have). - Familiarity with distributed training, inference optimization, or GPU/accelerator performance work (nice to have). - Experience training or fine-tuning models at scale (nice to have). Benefits - Flexible working hours and remote options. - Health, dental, and vision benefits for employees and their dependents. - Parental leave and flexible paid time off. - Reimbursement for relevant conferences, training, and education. - Company equity as part of the compensation package. - Support for remote employees to visit office spaces in NYC and Paris. - Workstation outfitting to ensure success.

Role Description As our first Data/Infrastructure Advocate Engineer, you'll bridge the gap between cutting-edge data infrastructure and the global community of data engineers, researchers, and developers. You'll champion Xet storage on the Hugging Face Hub, helping users efficiently store, version, and collaborate on large-scale datasets. This role is for someone who thrives at the intersection of technical depth (storage, Parquet, deduplication) and community advocacy, helping define the future of open data workflows. You'll collaborate with teams like Datasets, Hub, and Infrastructure to shape how developers interact with data on our platform, and inspire a community to build better, faster, and more scalable data pipelines. - Grow and nurture the open-source data/infra community: launch initiatives, collaborate with data-focused groups, and organize events or challenges. - Engage with communities like Apache Parquet, Open Table Formats, and data engineering forums to promote best practices and Hugging Face tools. - Promote the Hugging Face Hub as the go-to platform for data storage, versioning, and collaboration, curating and showcasing datasets, benchmarks, and tools like Xet. - Highlight use cases like efficient large-dataset updates, Parquet editing, and deduplication to demonstrate the Hub's value for data workflows. - Create demos, benchmarks, and tools (for example Colab notebooks) that illustrate best practices for data storage and versioning, and experiment with Xet, Parquet, and other formats. - Produce high-quality tutorials, blog posts, and videos that make complex topics accessible. - Share insights on storage optimization, dataset versioning, and deduplication to empower developers. - Actively participate in online communities (Discord, GitHub, forums) to highlight contributions, answer questions, and foster collaboration. - Make sure datasets and tools released on the Hub are well-documented, with clear examples, benchmarks, and use cases. Qualifications - 3+ years in developer relations or developer advocacy, ideally for data engineering, infrastructure, or ML tools and platforms. - An established public presence as a technical voice, with a track record of regularly publishing data/infra/ML content and a demonstrable, engaged audience on LinkedIn and X (Twitter). - A portfolio of developer-facing content you can point to: tutorials, blog posts, videos, demos, benchmarks, or conference talks. - Hands-on experience building and engaging open-source or developer communities (Discord, GitHub, forums). - Strong Python skills. - Hands-on experience with data libraries such as pandas, pyarrow, and huggingface/datasets. - Practical experience with storage systems and formats: Parquet, Open Table Formats, and S3. - Working knowledge of dataset versioning, deduplication, and compression. - Ability to explain complex technical topics clearly through writing, demos, or talks. - Fluent written and spoken English. Requirements - Experience with the Hugging Face Hub and datasets ecosystem, or with Xet. - Open-source maintainer or contributor experience. - Familiarity with large-scale data pipelines and data engineering workflows. - Experience producing notebooks (for example Colab) for tutorials and benchmarks. Benefits - Flexible working hours and remote options. - Health, dental, and vision benefits for employees and their dependents. - Parental leave and flexible paid time off. - Reimbursement for relevant conferences, training, and education. - Company equity as part of the compensation package.

Role Description As a Cloud ML DevRel Engineer, your goal is to grow the impact of the Hugging Face ML Cloud team by teaching the community of ML practitioners how to accelerate their training and inference workloads. The ML Cloud team works through strategic collaborations with: - Cloud providers: AWS, GCP, Azure, Cloudflare - AI accelerators: NVIDIA, AMD, Intel Gaudi, AWS Inferentia, TPU - Systems partners: Dell, Nutanix This is a solid engineering role with a strong flavor of education and community. Your impact comes from driving visibility and usage of partner integrations, through work like: - Publishing technical blog posts - Contributing documentation and code examples - Speaking to business and technical audiences at partner conferences - Producing and running webinars - Building and showing off demos - Leading go-to-market conversations with strategic partners You'll work at the front edge of generative AI and open source, hand in hand with some of the most important companies in the field. You'll have a lot of autonomy and full creative control, with the goal of having 10x the impact of a similar role at a big tech company. Qualifications - 3+ years in developer relations or developer advocacy, specifically for ML or AI products, tools, or platforms - An established public presence as a technical voice, with a track record of regularly publishing ML/AI content and a demonstrable, engaged audience on LinkedIn and X (Twitter) - A portfolio of developer-facing content you can point to: technical blog posts, conference talks, demos, code examples, or documentation - Comfort and experience with public speaking to technical audiences (conferences, webinars, workshops) - 3+ years of hands-on ML or software engineering experience, including taking models to production - Experience training or deploying ML models on at least one major cloud (AWS, GCP, or Azure) - Proficiency in Python - Practical experience with the Hugging Face stack (Transformers, the Hub, Inference Endpoints) or comparable open-source ML libraries - Working knowledge of GPUs or AI accelerators (NVIDIA, AMD, Intel Gaudi, AWS Inferentia, or TPU) and of training and inference optimization - Fluent written and spoken English Requirements - Open-source maintainer or contributor experience - An active presence in other developer communities (GitHub, Reddit, YouTube, Discord) - Familiarity with containers and orchestration (Docker, Kubernetes) - Experience with distributed training or inference-serving frameworks (for example vLLM, TGI, or Ray) Benefits - Flexible working hours and remote options - Health, dental, and vision benefits for employees and their dependents - Parental leave and flexible paid time off - Reimbursement for relevant conferences, training, and education - Company equity as part of the compensation package - Support for the ML/AI community

Role Description As a Cloud ML DevRel Engineer, your goal will be to increase the impact of the Hugging Face ML Cloud team by educating the community of ML practitioners on how they can benefit by accelerating their training and inference workloads. The Hugging Face ML Cloud team is working through strategic collaborations with the most used Clouds: - AWS - GCP - Azure - Cloudflare AI Accelerators: - NVIDIA - AMD - Intel - Gaudi - Inferentia - TPU Systems: - Dell - Nutanix This is a solid engineering role with a flavor of education and community. Your impact will be driving visibility and usage of integrations with strategic partners, through activities including: - Publishing technical blog posts - Contributing documentation and code examples - Speaking to business and technical audiences at partner conferences - Participating in, or producing webinars - Building and evangelizing demos - Leading GTM conversations with strategic partners You will be at the forefront of Generative AI (and how to build practical stuff with open source). You will work hand in hand with the most important companies in AI. You will enjoy a lot of autonomy and full creative control, with the goal to have 10x more impact than a similar role at a big tech corporation. Qualifications - Passionate about ML Engineering and building practical AI applications - Enjoys learning new challenging engineering concepts and technologies - Appreciates a good Developer Experience - Great communicator and educator - Comfortable with public speaking to technical audiences - Likes to move fast with high autonomy and experiment with new ways to ship things - Engaged with the ML community in a positive and helpful way - Experience in Open Source development is helpful Benefits - Flexible working hours and remote options - Health, dental, and vision benefits for employees and their dependents - Parental leave and flexible paid time off - Reimbursement for relevant conferences, training, and education - Company equity as part of the compensation package - Support for remote employees to visit office spaces in NYC and Paris - Workstation outfitting to ensure success