Machine Learning Fellow (Human Frontier Collective)

Scale AI; United States; On-site; USD 60,000 - 90,000; Full time

Benefits offered by this job

Health & Wellbeing

Career Growth

Community & Networking

Parental Support

Job summary

Scale AI's Human Frontier Collective Fellowship brings together top researchers and domain experts to collaborate on high-impact work 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.

Qualifications

• PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow).
• Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.

Responsibilities

• Design, evaluate, and interpret advanced generative AI systems.
• Engage in high-impact ML projects with partnered AI labs and scales platforms.
• Collaborate on research publications and contributing to technical reports.

Skills

Python

PyTorch

TensorFlow

Machine Learning

Education

PhD or postdoctoral degree in Computer Science or related field

Tools

Docker

Langchain

AWS

Job description

• 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
• 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)

Benefits

• Health & Wellbeing: Our holistic approach to supporting Scaliens includes comprehensive health coverage, dental and vision insurance, mental healthcare services, and more. PTO policies and accommodating schedules ensure you’ll get time off when you need it to relax and recharge. Note that our offerings may vary by region as we strive to respond to the unique needs of Scaliens around the globe.
• Personal & Career Growth: Continuously learn and grow through annual learning & development stipend, attending leadership breakfasts, manager training, speaker series, and joining an ERG.
• Building Scale Community: We welcome guests to our offices, and you can expect to see Scalien families and friends around. Join local happy hours, and accept invites to game nights, book clubs, and many other employee‑led community events.
• Parental Support: Balancing work and family is essential, and Scale understands the importance of having adequate leave policies in place to promote a healthy home and work life.

Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field

Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration

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 Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist