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

Huggingface•New York, NY

40d•Remote

About The Position

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'll 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.This role is for technical problem-solvers who thrive in ambiguity. You might prototype a dataset pipeline one week, debug a distributed filesystem bottleneck the next, or co-author a tutorial to onboard a new research community. We value curiosity, adaptability, and a willingness to roll up your sleeves-whether the challenge is technical or collaborative. You're a jack-of-all-trades Research Engineer with a passion for making ML accessible to scientific domains.

Requirements

Built or optimized datasets, data pipelines, or tools for scientific applications, especially in distributed or high-performance computing environments.
Worked with fast-reads, distributed storage, or large-scale data processing-bonus if you've tackled challenges like cross-filesystem data access or real-time scientific data workflows.
Collaborated with non-AI research communities (e.g., biology, physics, chemistry) to translate their needs into technical solutions, whether through code, documentation, or open-source contributions.
Experimented with diverse ML approaches (not just large models) to solve domain-specific problems, and enjoy iterating based on feedback from end-users.

Responsibilities

Building and optimizing datasets and data pipelines for scientific use cases, with a focus on fast, scalable reads across distributed filesystems (e.g., HPC, cloud, or hybrid environments).
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.

Benefits

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.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume