Role Description & Responsibilities
Machine Learning
About Scale AI
Scale AI is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Machine Learning role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark .
HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team.
Key Responsibilities & Day-to-Day Scope
- ✓ Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions.
- ✓ Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping 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 more.
- ✓ Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition.
- ✓ Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field.
- ✓ Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker) and LLM frameworks (LangChain) is a plus.
- ✓ Professional Mindset : Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration.
- ✓ Duration : This is a fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest. This is a 1099 independent contractor engagement.
- ✓ Work authorization : We do not sponsor visas for Fellows. To participate in the HFC Fellows program, you need to have or independently obtain full-time work authorization in the country they reside in.
Official Qualifications & Technical Requirements
- • Community Network : Once you’ve received an invitation to join the HFC, you’ll also gain access to our newsletters, discussion channels, virtual sessions, IRL events, and much more.
- • Projects Logistics :
- • Project selection: You’ll regularly get matched to carefully selected projects from our partners. Depending on the partner, projects range from evaluating AI models to designing experiments, building RL environments, co-authoring research papers, and more.
- • Flexible schedule: There's no minimum commitment – you decide whether to take on a project. Most fellows spend 10–25 hours per week, on a schedule they set themselves.
- • Competitive pay: Project pay rates vary across platforms and depend on a number of factors, including but not limited to: projects, scope, skillset, and location. You’ll receive the pay information upon receiving project matching notifications.
- • 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. Note: If we invited you directly, your invitation will say whether this step applies.
- • Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.
Preferred Skills & Technology Stack
- + Familiarity with MLOps pipelines (Docker, Kubernetes, Kubeflow, Triton Inference Server).
- + Knowledge of distributed training techniques and GPU acceleration (CUDA).
- + Relevant coursework, research publication, or open-source contribution in ML/DL.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Scale AI
Verified EmployerScale AI champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.