At Hugging Face, we’re on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 5 million users & 100k organizations who collectively shared over 1M models, 300k datasets & 300k apps. Our open-source libraries have more than 400k+ stars on Github. We focus on developing open-source tools and models that push the boundaries of AI while remaining efficient and user-friendly.
About the Role
As a Community Machine Learning Research Engineer, you will be collaborating with science communities while doing impactful machine learning research.
You’ll be responsible for :
- Build and facilitate non-consortium-based research collaborations with researchers in non-AI scientific fields (e.g., biology, physics, chemistry, quantum, fluid dynamics) to explore innovative applications of ML tools.
- Co-build ML tools and models for scientific use cases, co-developing solutions and publishing pre-trained models or datasets tailored to these domains.
- Educate and engage with the scientific community through tutorials, workshops, and open-source contributions to bridge the gap between ML and traditional sciences.
- Foster strategic partnerships and community research initiatives with academic institutions and organizations to advance interdisciplinary innovation and adoption.
The work will likely be pretty varied: in some cases, you might work with industry or academic partners early in the research process. In other cases, you might set up these collaborations at a high level and guide them to the final release. We’re interested in folks who are willing to experiment with different models and figure out how to have the most impact while working with the amazing science machine learning community.
About You
You have done cutting-edge machine learning research and/or engaged and collaborated with the research community, such as Jean-Zay, Alan Turing Institute, PRACE, Lawrence Berkeley National Laboratory, Institute for Quantum Computing …
You'll enjoy working here if you:
- Have a generalist Research Engineer with an ability to experiment with different models and figure out how to have the most impact while working with the amazing science machine learning community.
- Are comfortable working in a fast-paced and ambiguous environment, aka shifting sands of startup land. This includes communicating with other teams to efficiently join forces, in Hugging Face’s very decentralized/anarchic organization.
- Enjoy understanding technical domains deeply and are willing to really get into the weeds.
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.
Checkout hf.co/science for more information about the science team at Hugging Face.
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 people 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. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias toward impact and is always challenging ourselves to continuously grow. 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 flexible parental leave and 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. However, this job offer is quite special as it's best if you are in-person in our new Paris office. We provide relocation packages if necessary.
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.
We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.
