Machine Learning Fellow - Human Frontier Collective (Canada)

United States Digital Space LLC; United States; Remote; USD 83,000 - 179,000; Full time

Job summary

United States Digital Space LLC is seeking a fully remote, 1099 independent contractor for the Human Frontier Collective Fellowship, estimated six months with potential extension. Eligible to work in Canada.

You’ll join top researchers to design, evaluate, and interpret advanced generative AI systems, collaborating across labs and platforms.

Required: PhD or postdoc in CS/related field, 1–3+ years ML experience; strong Python, PyTorch/TensorFlow; AWS, Docker, LangChain a plus.

Qualifications

• PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
• 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow).Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.

Responsibilities

• Engage in high-impact ML projects with partnered AI labs and platforms to design, review, and optimize PyTorch models.
• Collaborate on research publications to boost academic visibility.
• Evaluate ML code for efficiency, scalability, and correctness, advising on GPU optimization and trade-offs.

Skills

Python

PyTorch

TensorFlow

AWS

Docker

LangChain

ML Ops

Education

PhD or postdoctoral degree in Computer Science or related field

Tools

Git

Jupyter

Kubernetes

MLflow

Job description

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in Canada.

About the Program

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’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems-while 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’ll 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’s research team to co-author technical reports and research papers-boosting 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.

***PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.*

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, Ernst& Young, 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 [e-mail]. 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.*