Machine Learning Fellow - Human Frontier Collective (US)
Scale AI · United States
- Hybrid
- Full-time
- $120,000 / year
- United States
Job highlights
- Collaborate on advanced generative AI systems.
- Design, evaluate, and optimize PyTorch models.
- Co-author technical reports and research papers.
- Join a top-tier network of AI innovators.
- Flexible schedule with competitive pay.
About the role
About The Program
The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you u2019ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems u2014while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.What You'll Do
- ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
- HFC Community: Beyond the work, you u2019ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
- Contribute to Research Publications: Collaborate with Scale u2019s research team to co-author technical reports and research papers u2014boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).
Who Should Apply
- Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
- Professional Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
- Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
- Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.
Why Join the HFC?
- Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
- Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
- Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
- Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location.
Application Process
- Apply: We review applications on a rolling basis.
- Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
- Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.
About Us
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.We comply with the United States Department of Labor's Pay Transparency provision.PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants u2019 needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.Key skills/competency
- Machine Learning
- Python
- PyTorch
- TensorFlow
- Deep Learning
- AI Research
- Data Scientist
- Machine Learning Engineer
- Cloud Infrastructure
- MLOps
Skills & topics
- Machine Learning
- Python
- PyTorch
- TensorFlow
- Deep Learning
- AI Research
- Data Science
- Machine Learning Engineering
- AWS
- Docker
- Langchain
- MLOps
- PhD
- Postdoctoral
- Generative AI
How to get hired
- Tailor your resume: Highlight your PhD/postdoc, 1-3 years ML Engineer/Data Scientist experience, Python, PyTorch, and TensorFlow skills.
- Emphasize research: Showcase your passion for applied AI and any publications or contributions to AI research.
- Demonstrate collaboration: Mention experience working in interdisciplinary teams or contributing to group projects.
- Prepare for interviews: Be ready to discuss your research, professional background, and alignment with human-centered AI.
Technical preparation
Master Python and ML frameworks like PyTorch/TensorFlow.,Understand deep learning workflows and model optimization.,Familiarize yourself with cloud (AWS) and MLOps tools.,Practice evaluating ML code for efficiency and correctness.
Behavioral questions
Discuss a complex AI research project you led.,Explain how you collaborate in interdisciplinary teams.,Describe your passion for applied AI research.,Share how you approach problem-solving in ML.
Frequently asked questions
- What is the Human Frontier Collective (HFC) Fellowship at Scale AI?
- The HFC Fellowship at Scale AI is a program that brings together top researchers and domain experts to collaborate on high-impact projects shaping the future of AI. Fellows apply their expertise to design, evaluate, and interpret generative AI systems, gaining exposure to cutting-edge research and a network of leading thinkers.
- Is the Machine Learning Fellow role at Scale AI remote?
- Yes, the Machine Learning Fellow role at Scale AI is a fully remote, 1099 independent contractor opportunity. Candidates must be authorized to work in the United States, as visa sponsorship is not provided.
- What are the qualifications for the Machine Learning Fellow position?
- Ideal candidates have a PhD or postdoctoral degree in Computer Science or a related field, with 1-3 years of experience as a Machine Learning Engineer or Data Scientist. Strong proficiency in Python and ML frameworks like PyTorch and TensorFlow is required. Experience with cloud infrastructure (AWS) and MLOps tools is a plus.
- What kind of projects will a Machine Learning Fellow work on at Scale AI?
- Fellows engage in high-impact projects with partnered AI labs, focusing on designing, reviewing, and optimizing PyTorch models, evaluating ML code, and advising on GPU optimization and scaling. They also contribute to research publications.
- What is the duration of the Machine Learning Fellowship?
- The Machine Learning Fellowship is an estimated six-month contract, with the potential for extension. The work involves flexible hours, ranging from 10-40 hours per week.
- How does Scale AI handle applications for the Machine Learning Fellow role?
- Scale AI reviews applications on a rolling basis. Following an initial application, candidates may be invited for an interview to discuss their experience and fit. A 90-day waiting period is enforced before reconsidering candidates for the same role.
- Can I apply for the Machine Learning Fellow role if I require visa sponsorship?
- No, visa sponsorship is not available for this role. Candidates must be authorized to work in the United States to be eligible for the Machine Learning Fellow position.
- What is the compensation for the Machine Learning Fellow role?
- The role offers competitive pay, with project rates varying based on factors such as project scope, skillset, and location. It is structured as a 1099 independent contractor opportunity.