Hugging Face is hiring a Community ML Research Engineer to bridge the gap between machine learning and scientific research in fields like biology, physics, or quantum research. You will be a technical generalist building data pipelines, developing ML tools, and collaborating with scientific communities.
What You'll Do
- Build and optimize datasets and data pipelines for scientific use cases, focusing on fast, scalable reads across distributed filesystems.
- Develop and adapt ML tools to address real-world scientific challenges, from data preprocessing to model deployment.
- Collaborate with non-AI scientific communities to co-design solutions, publish datasets, and create open-source resources.
- Engage with researchers and institutions to identify high-impact opportunities through hands-on technical work or strategic partnerships.
What We're Looking For
- Experience building or optimizing 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.
- Collaborated with non-AI research communities to translate their needs into technical solutions.
- Experimented with diverse ML approaches to solve domain-specific problems.
Nice to Have
- Experience tackling challenges like cross-filesystem data access or real-time scientific data workflows.
Benefits & Compensation
- 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 and paid time off.
- Opportunity to visit offices in NYC and Paris.
- Workstation outfitting if needed.
- Company equity as part of compensation package.
- Relocation packages if necessary.
Work Mode
This role is EMEA Remote with hybrid options available in Paris.
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.
