# Machine Learning Fellow - Human Frontier Collective (UK) at Scale AI

> Remote · United Kingdom · Principal · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Ascaleai%3A4661647005 (read 2026-11-05).

## Facts (observed)

- Company: [Scale AI](https://alderhq.app/companies/scale-ai)
- Location text: United Kingdom; Remote (Growth only)
- Where it can be done from (inferred): Remote · United Kingdom (evidence: "Location: United Kingdom; Remote (Growth only)")
- Posted: 2026-02-12 (266 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/scaleai/jobs/4661647005
- Skills listed (inferred): Python, AWS, Docker, PyTorch, TensorFlow, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (United Kingdom, n 38): p25 £88k, median £114k, p75 £211k
- H-1B filings at this company for similar roles, FY26: 16, median offered wage $250k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))
- Licensed UK sponsor: registered as "Scale AI Limited" (checked 2026-11-03, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers))

## Description (the employer's text)

### About the Collective

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.

### Why join the HFC

HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team.

- 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.
### Who should apply

- 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.
### How it works

- 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.
- 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.
### 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. 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.
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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.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Ascaleai%3A4661647005 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.
