Machine Learning Fellow - Human Frontier Collective (Canada)

Scale AI; Canada; On-site; CAD 68,880 - 110,208; Part time

Benefits offered by this job

Flexible schedule

Professional development opportunities

Competitive pay up to $80/hr

Job summary

A leading AI company in Canada seeks candidates for the Human Frontier Collective Fellowship. This fully remote position allows fellows to collaborate on high-impact AI projects and gain exposure to cutting-edge research. Ideal applicants should have a PhD in a relevant field, along with extensive experience in building and fine-tuning deep learning models in PyTorch. The role offers flexible hours and competitive pay, making it a unique opportunity for advancing AI expertise in an innovative setting.

Qualifications

• Advanced degree in a relevant field.
• Hands-on experience with deep learning models.
• Familiarity with GPU performance and optimization.

Responsibilities

• Engage in high-impact projects with AI labs.
• Analyze and critique complex ML code.
• Provide feedback on GPU performance.

Skills

Deep learning model building in PyTorch

GPU optimization techniques

Analyzing complex ML code

Explaining ML behaviors

Education

PhD or higher in Computer Science or related field

Tools

PyTorch

CUDA

Job description

Canada

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

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’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

• Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design and review advanced deep learning problems while analyzing and critiquing complex ML code and AI-generated PyTorch implementations. Apply expert judgment on GPU performance, profiling, and hardware‑aware architecture and scaling 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.
• Advanced degree (PhD or higher) in Computer Science, Electrical/Computer Engineering, Applied Math, AI/ML, or a related field.
• Hands‑on experience building and fine‑tuning deep learning models in PyTorch, including architectures like Transformers, CNNs, and diffusion models.
• Familiarity with GPU performance and optimization, including memory management, CUDA kernels, and profiling tools.
• Skilled at analyzing research‑level model code and giving clear, actionable feedback.
• Able to clearly explain complex ML behaviors and trade‑offs.

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: Up to $80/hr, based on experience, skills assessment, 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, 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 [e-mail]. Please see the United States Department of Labor's Know Your Rights poster for additional information.

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’ 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.