Hugging Face · 2 months ago
Community ML Research Engineer, non-AI scientific fields - US Remote
United States
Full-time
Remote
Mid LevelHugging Face is a leading platform for AI builders, aiming to democratize good AI with a vast user base and numerous shared resources. The Scientific Machine Learning Research Engineer will bridge the gap between machine learning and scientific research, focusing on building and optimizing datasets and collaborating with researchers to develop impactful ML tools.
AI InfrastructureArtificial Intelligence (AI)Foundational AIGenerative AIMachine LearningNatural Language ProcessingOpen SourceSoftware
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
Qualification
Required
Built or optimized datasets, data pipelines, or tools for scientific applications, especially in distributed or high-performance computing environments
Technical problem-solver who thrives in ambiguity
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
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
Preferred
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
Benefits
Reimbursement for relevant conferences, training, and education
Flexible working hours and remote options
Health, dental, and vision benefits for employees and their dependents
Flexible parental leave
Paid time off
Relocation packages
Company equity as part of their compensation package
Company
Hugging Face
Hugging Face allows users to build, train, and deploy art models using the reference open source in machine learning.
Founded in 2016
51-200 employees
H1B Sponsorship
Hugging Face has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (3)
2024 (5)
2023 (2)
2020 (2)
Funding
Current Stage
Late StageTotal Funding
$395.2MKey Investors
Salesforce VenturesLux CapitalAddition
2024-08-01Series Unknown
2024-01-16Series D
2023-08-23Series D· $235M
Leadership Team
Clément Delangue
Co-founder & CEO
Julien Chaumond
Co-founder
Recent News
GlobeNewswire
2026-01-06
The French Tech Journal
2025-12-25
Company data provided by crunchbase