Scale AI
Machine Learning Fellow- Human Frontier Collective (Canada)
Remote Human Frontier Collective role with clear candidate location fit.
PostedRecently added
Eligible countries1 accepted country
Seniority signalOpen level
Work settingRemote
Accepted candidate locations
Canada
Role overview
Machine Learning Fellow- Human Frontier Collective (Canada)
Requirements and responsibilities
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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.
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