Community ML Research Engineer, non-AI scientific fields - US Remote

Community ML Research Engineer, non-AI scientific fields - US Remote

At Hugging Face, we are democratizing good AI. We build a platform for AI builders with over 5 million users, 100k organizations, 1M models, 300k datasets, and 300k apps. Our open-source libraries have more than 400k+ stars on Git Hub. We focus on developing open-source tools and models that push the boundaries of AI while remaining efficient and user-friendly.

As a Scientific Machine Learning Research Engineer, you will bridge the gap between cutting‑edge machine learning and scientific research in fields like biology, physics, or quantum research. You will be a technical generalist—equally comfortable diving into complex data pipelines, optimizing fast‑reads for distributed scientific datasets, and collaborating with researchers to build impactful ML tools.

You will be responsible for:

• Building and optimizing datasets and data pipelines for scientific use cases, with a focus on fast, scalable reads across distributed file systems (e.g., HPC, cloud, or hybrid environments)
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Developing and adapting ML tools (not just models) to address real‑world scientific challenges, from data preprocessing to model deployment
• Collaborating with non‑AI scientific communities to co‑design solutions, publish datasets, and create open‑source resources that lower the barrier to ML adoption in traditional sciences
• Engaging with researchers and institutions to identify high‑impact opportunities, whether through hands‑on technical work or strategic partnerships

You are a jack‑of‑all‑trades Research Engineer with a passion for making ML accessible to scientific domains. You have likely:

You will enjoy working here if you:

• Are a technical generalist who loves both the "weeds" (e.g., optimizing a dataset pipeline) and the "big picture" (e.g., shaping a collaboration's long‑term impact)
• Thrive in fast‑paced, ambiguous environments and can pivot between technical deep dives and cross‑team communication in Hugging Face's decentralized culture
• Believe the best solutions often come from iterative experimentation—whether it's testing a new data format, prototyping a tool, or refining a community workshop

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. 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 are very distributed and all remote employees have the opportunity to visit our offices. If needed, we will 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.

Checkout  for more information about the science team at Hugging Face.