Machine Learning Fellow - Human Frontier Collective (Canada)

ABOUT THE ROLE Scale AI is inviting a Machine Learning Fellow to join its Human Frontier Collective (HFC) Fellowship as a fully remote, independent contractor based in Canada. The role spans six months with the possibility of extension and offers a unique opportunity to collaborate with leading AI labs and industry partners on high‑impact projects that shape the future of generative and applied AI. As a Fellow, you will be at the intersection of research and production, helping to design, evaluate, and optimize state‑of‑the‑art models while contributing to Scale’s public research portfolio. WHAT YOU'LL DO - Lead the design and review of PyTorch and TensorFlow models for real‑world deep‑learning workflows, ensuring efficiency, correctness, and scalability. - Evaluate complex ML code and AI‑generated implementations, providing actionable feedback on GPU optimization, memory usage, and performance trade‑offs. - Collaborate closely with Scale’s research team to co‑author technical reports, benchmark papers, and open‑source contributions such as SciPredict, PropensityBench, and Professional Reasoning Benchmark. - Engage with the HFC community, participating in interdisciplinary discussions, peer reviews, and advisory sessions that drive responsible AI research. - Deliver clear, reproducible documentation and reproducibility notebooks that support both internal stakeholders and the broader research community. - Maintain up‑to‑date knowledge of emerging ML frameworks, cloud infrastructure, and MLOps best practices to inform project decisions. WHAT YOU'LL NEED - PhD or postdoctoral degree in Computer Science, Computer Engineering, or a closely related field, with a strong publication record in AI or machine learning. - 1–3+ years of professional experience as a Machine Learning Engineer or Data Scientist, demonstrating end‑to‑end model development and deployment. - Advanced proficiency in Python and modern ML libraries (PyTorch, TensorFlow), coupled with hands‑on experience in GPU‑accelerated training and inference. - Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps tooling such as Docker, Kubernetes, and LangChain, enabling efficient model packaging and deployment. - A detail‑oriented, analytical mindset, capable of dissecting complex codebases and identifying subtle performance bottlenecks. - Excellent written and verbal communication skills, with the ability to translate technical insights into clear, actionable recommendations for cross‑functional teams. WHY REMOTE Scale AI’s distributed culture is built around asynchronous collaboration, allowing Fellows to work from any location in Canada while staying connected with a global network of researchers and engineers. The remote model supports a flexible 10–40 hour work week, giving Fellows the freedom to balance professional commitments with personal life. All Fellows receive the same high‑quality support as on‑site teammates, including access to internal tools, mentorship, and a vibrant community that encourages continuous learning and innovation. BENEFITS Scale AI offers a comprehensive benefits package for contractors, including health coverage, paid time off, a remote work stipend, and a dedicated learning budget for conferences, courses, and certifications. Fellows also gain early access to Scale’s proprietary data platforms and tooling, positioning them at the forefront of AI research and application.