Community Ml Research Engineer

Summary

Join Hugging Face's science team as a Community Machine Learning Research Engineer and collaborate with researchers in various scientific fields. You will build and facilitate research collaborations, co-develop ML tools and models for scientific use cases, and educate the scientific community. Responsibilities include fostering strategic partnerships and contributing to open-source projects. The role requires cutting-edge machine learning research experience and collaboration with the research community. The ideal candidate enjoys working in a fast-paced environment and is comfortable with ambiguity. Hugging Face offers various benefits, including flexible working hours, remote options, health benefits, flexible parental leave, paid time off, and company equity.

Requirements

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 …

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

• Flexible working hours and remote options
• Health, dental, and vision benefits for employees and their dependents
• Flexible parental leave
• Paid time off
• Reimbursement for relevant conferences, training, and education
• Company equity as part of their compensation package
• Relocation packages if necessary