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 more than 1 Million+ models and 320K+ stars on GitHub, over 15.000 companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Grammarly and NASA. About the Role As an Open-Source ML Release Engineer, you will have a key role in collaborating with external groups in the release and adoption of their Open ML projects. You will work horizontally across the company (with the Open Source and Product teams) as well as with external stakeholders (such as Stanford, Meta, Cohere, Google, and Nous Research), enjoying autonomy to lead the collaborations. In day-to-day, this role can involve: Developing notebooks and fine-tuning scripts for new models. Crafting engaging demos to showcase the latest research. Collaborating closely with partners to promote and implement best practices in open ML. Generating high-quality technical content such as blog posts. Growing healthy and sustainable relationships with external partners. Testing and experimenting with new model integrations. Creating and improving tooling to lower the barrier of entry for new models. As the Open ML ecosystem grows, we seek an MLE who thrives in autonomy and a fast-paced environment, possesses a deep understanding of the ML landscape, and excels in interpersonal communication. You will work cross-functionally with the Open Source and Product teams and engage with external stakeholders. About you You’ll thrive in this role if you are passionate about being at the forefront of ML releases and enjoy collaborating with diverse teams and organizations. This position is ideal for someone who: Has a strong understanding of and empathy for the needs of the open ML community. Is willing to work across various teams and disciplines. Enjoys a broad range of tasks that can go beyond traditional engineering roles, sometimes wearing PM, developer, or hacker hats depending on the situation. Is excited about tackling challenging and diverse projects. Is comfortable working in a fast-paced, dynamic environment where priorities shift rapidly. Loves communicating with the community through blog posts, workshops or crafting ML memes. Is not afraid to pick up new tools and dive into new ML areas. 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. More about Hugging Face We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where you feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community, as well as the future of machine learning more broadly. Hugging Face is an equal opportunity employer, and we do not discriminate based on race, ethnicity, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or ability status. We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to grow continuously. We provide all employees with reimbursement for relevant conferences, training, and education. We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off. We support our employees wherever they are. While we have office spaces in NYC and Paris, we’re very distributed, and all remote employees have the opportunity to visit our offices. If needed, we’ll also outfit your workstation to ensure you succeed. We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.
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