DESCRIPTION FORMATTING RULES (CRITICAL - FOLLOW EXACTLY)

Your job is to output clean, readable Markdown while PRESERVING ALL ORIGINAL CONTENT AND STRUCTURE EXACTLY.

ABSOLUTE RULES - NEVER VIOLATE:

NEVER add, remove, or modify any text/wording from the original
NEVER paraphrase or rewrite sentences - keep exact wording
NEVER remove sections, paragraphs, disclaimers, or any content
PRESERVE all links exactly as they appear
PRESERVE the natural flow and spacing of the original document

MARKDOWN FORMATTING:

for main section headings (bold standalone titles like "The Role", "You Will", "Requirements")
for sub-section headings
NEVER use # (H1) - the job title is already the page H1
Use "-" bullet lists for ANY list of items
CRITICAL: If content is clearly a list (requirements, responsibilities, benefits), format as bullet list
Bold for inline emphasis, key terms, skills - preserve existing bold from original
Italic for emphasis or disclaimers - preserve existing italic from original
text for ALL hyperlinks - preserve every link

SPACING RULES:

Preserve the natural paragraph breaks from the original content when they exist
IF the original lacks proper spacing (e.g., everything is one giant paragraph), ADD logical breaks:
- Blank line before each section heading
- Blank line between distinct topics/sections
- Blank line before and after bullet lists
NO blank lines between bullet points in the same list
NO multiple consecutive blank lines (max 1 blank line between elements)
The output should be scannable and readable, even if the input wasn't

OUTPUT QUALITY:

Clean, scannable markdown that matches the original document's flow
Professional formatting that readers can quickly parse
All content intact - nothing added, nothing removed

TITLE FORMATTING RULES (CRITICAL)

The "title" field MUST use the EXACT format: "[Job Title] - [Company Name]"

Always use a HYPHEN (" - "), NEVER "at"
Example: "Senior ML Engineer - OpenAI" (CORRECT)
Example: "Senior ML Engineer at OpenAI" (WRONG — never use "at" in the title field)
Clean up the raw title: fix capitalization, remove company name if already embedded, remove location info
Keep the job title portion concise but don't lose important qualifiers (e.g., "Senior", "Lead", "Staff")
The "metaTitle" field uses a DIFFERENT format ("[Job Title] at [Company]") — do NOT confuse the two

SALARY DISPLAY FORMAT (IMPORTANT)

Format salary display as compact "k" notation:

$187,000 - $220,000 → "$187k - $220k"
$100,000 - $120,000 USD → "$100k - $120k"
€80,000 - €100,000 → "€80k - €100k"
Always use "k" for thousands, remove ".0" decimals
Include currency symbol at the start, not the end

WORK MODE INFERENCE RULES

Determine workMode using these rules IN ORDER:

If explicitly stated ("remote", "hybrid", "on-site", "in-office") in title/description → use that
If location contains "Remote" → REMOTE
If multiple countries/continents listed → REMOTE (high confidence)
If location is specific city only (e.g., "London", "New York", "Tokyo") with no remote mention → ONSITE
If "flexible" or "work from home options" mentioned → HYBRID
If unclear after all checks → null

EXPERIENCE LEVEL EXTRACTION RULES

Extract experienceLevel using these rules:

From title keywords (highest priority):
- "Intern/Internship" → ENTRY
- "Junior/Jr/Associate" → JUNIOR
- "Mid/Mid-level" → MID
- "Senior/Sr/Staff/Principal" → SENIOR
- "Lead/Tech Lead/Team Lead" → LEAD
- "Director" → DIRECTOR
- "Head of/Head" → HEAD
- "VP/Vice President/Chief/C-level/CTO/CEO/CFO" → C_LEVEL
From years requirement in description:
- 0-1 years → ENTRY
- 1-2 years → JUNIOR
- 3-4 years → MID
- 5+ years → SENIOR (unless title indicates higher level)
If no indicators → null

LOCATION RULES (CRITICAL - keep compact)

Goal: Locations must be SHORT and COMPACT. Max 5 comma-separated values total.

REMOTE JOBS:
- If open to all/most regions → just "Remote"
- If remote but limited to specific regions → use the CANONICAL REMOTE TOKENS below in parentheses
- If remote limited to 2 regions → "Remote (US, Europe)" (still 1 badge)
- NEVER list every individual country/city for remote jobs
CANONICAL REMOTE TOKENS (use these EXACT values inside parentheses):
- United States only → "Remote (US)"
- US + Canada / North America → "Remote (NA)"
- Europe / EU / EMEA / DACH / Nordics → "Remote (Europe)"
- Asia / Asia Pacific / APAC / SEA / ANZ → "Remote (APAC)"
- Latin America / South America / LATAM → "Remote (LATAM)"
- Middle East / MENA / GCC → "Remote (MENA)"
- Africa / Sub-Saharan Africa → "Remote (Africa)"
- UK only → "Remote (UK)"
- Specific country → "Remote (Singapore)", "Remote (Germany)", etc.
ONSITE/HYBRID with specific cities:
- For each city, ALSO include the country as a separate entry for discoverability
- Example: "Dubai" → "Dubai, United Arab Emirates"
- Example: "London, Berlin" → "London, United Kingdom, Berlin, Germany"
- If 4+ cities in same country → use country name: "United States" and at most 2 key cities
- NEVER include both city AND state AND country for the same place (e.g., "New York" not "New York, NY, United States")
- But DO include city AND country as separate comma entries: "New York, United States"
US-SPECIFIC:
- NEVER list states separately (no "CA, NY, TX, FL...")
- Many US cities → "United States" or top 2 cities + "United States"
- Remote in US → "Remote (US)"
MAX 5 comma-separated values in the locations field

TAG RULES (CRITICAL - content-derived skills only)

Goal: Tags must be SPECIFIC, ACTIONABLE skills/technologies/tools that appear IN THE JOB DESCRIPTION. They surface in "In-Demand Skills" and must help candidates filter by real requirements — not generic industry words.

FORBIDDEN TAGS (NEVER use these — they are useless on an AI job board):

"ai", "artificial intelligence", "machine learning", "tech", "product management", "business development", "marketing", "engineering", "design", "operations", "sales", "partnerships", "product marketing"
Any tag that merely restates the job category or industry (we already know it's AI/ML)
Any tag not explicitly mentioned or clearly implied by the job description text

REQUIRED: Tags must be EVIDENCE-BASED. Only include a tag if the description (or title) explicitly mentions that skill, tool, protocol, or practice. If the post doesn't mention specific technologies or methods, use 1–2 tags maximum or leave tags minimal.

GOOD TAGS (prefer these when present in the content):

AI/ML domains: "nlp", "computer vision", "reinforcement learning", "generative ai", "llm", "robotics", "autonomous systems"
Languages & runtimes: "python", "rust", "typescript", "go", "c++", "java", "cuda"
Frameworks & tools: "pytorch", "tensorflow", "jax", "hugging face", "langchain", "ray", "mlflow", "wandb"
Tools & practices: "figma", "wireframes", "product specs", "user research", "a/b testing", "sql", "react", "node"
Disciplines (only when clearly a focus): "ui/ux", "mlops", "data engineering", "compliance", "devrel", "deep learning"
Concrete deliverables/activities: "prds", "roadmaps", "model evaluation", "dashboards", "fine-tuning"

RULES:

Do NOT repeat words already in the job title (e.g. "Product Manager" → no tag "product management").
Prefer lowercase; well-known abbreviations are fine: "nlp", "ui/ux", "llm".
Max 3 tags, prefer 2. If nothing specific is stated, 0–1 tags is fine — do not fill with generic terms.
When in doubt, omit. Fewer accurate tags are better than generic ones.

RELEVANCY SCORING (for feed ranking)

Score how relevant this job is to an AI/ML job board audience (0-100).
This score controls feed ranking — it directly determines which jobs appear
first when a company has many openings. Be precise and consistent.

95-100: Core AI/ML research or engineering that BUILDS models
(ML Engineer, AI Researcher, NLP Scientist, Computer Vision, RL, LLM, MLOps)
80-94: Software infrastructure that directly SUPPORTS AI systems
(GPU/CUDA Engineer, ML Platform, Distributed Training Infra, AI DevOps)
65-79: Technical roles at AI companies (Software Engineer, Backend, Security, SRE)
50-64: Product, data, and design roles tied to AI products
(AI Product Manager, UX Researcher on AI tools, Data Analyst)
30-49: Business and go-to-market roles (Sales, Marketing, Finance, Legal, Recruiting)
10-29: Administrative and support roles (Office Manager, Coordinator, Compliance)
0-9: Non-technical facility/manual roles (Electrician, Custodian, HVAC, Security Guard)

Key heuristic: Would someone browsing an AI job board be excited to find this listing?
A "Senior ML Engineer" at Anthropic = 98. A "Facilities Coordinator" at Anthropic = 5.

AI RELEVANCE CLASSIFICATION (CRITICAL — controls whether job is listed)

Classify whether this job involves AI/ML/LLM/agentic technologies.
This is a strict binary gate for companies that aren't pure AI companies.

Set "isAIRelevant": true if ANY of these apply:

The role is fundamentally about AI/ML (researcher, ML engineer, NLP scientist, etc.)
The job description requires building, training, deploying, or evaluating AI/ML models
The role involves significant use of LLMs, RAG, agentic frameworks, or AI APIs
The role directly supports AI systems (ML platform, AI infrastructure, GPU engineering)
The role is an AI product manager, AI designer, or AI-focused data scientist
The description explicitly lists AI/ML tools (PyTorch, TensorFlow, LangChain, etc.)

Set "isAIRelevant": false if:

The role is generic software engineering with no AI/ML mention in the description
The role is business/operations/admin with no AI/ML component
The role is at a company that does AI but THIS specific position doesn't involve AI
Example: "Recruiter" at Stripe — no AI involvement even though Stripe uses AI
Example: "Backend Engineer" at Datadog — builds dashboards, no ML mentioned
Example: "Office Manager" at any company — never AI-relevant

Be strict: a job at an AI-adjacent company is NOT automatically AI-relevant.
The role or description must explicitly involve AI/ML/LLM technologies.

EXTRACTION RULES ===

Extract data ONLY if clearly stated
If not found, return null (not empty string, not "Competitive")
Use the structured data from job board when available (more reliable than parsing description)
For categoryId: ALWAYS select best matching category based on title and description

AVAILABLE CATEGORIES (id:name):
1:Business Development, 2:Data, 3:Design, 4:Engineering, 5:Finance, 6:Legal, 7:Marketing, 8:Operations, 9:People Ops, 10:Product Management, 11:Research, 12:Sales, 14:Support

EXPERIENCE LEVELS: ENTRY, JUNIOR, MID, SENIOR, LEAD, DIRECTOR, HEAD, C_LEVEL

JOB LISTING TO ANALYZE ===

Title: Finance Fellow - Human Frontier Collective (US)
Company: Scale AI
Location: United States
Description:
PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role.

About the Program

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.

What You'll Do

Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Develop and evaluate complex financial scenarios to test and enhance AI accuracy in valuation, forecasting, and analysis; collaborate in interactive sessions to assess model outputs for market relevance and compliance; provide detailed feedback to improve AI capabilities; and contribute to specialized projects in financial modeling, risk assessment, and equity research.
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, Master, BBA in Finance, Economics, or related degrees.
Certifications: CFA or CPA strongly preferred.
Professional Background: 5+ years in FP&A, Investment Banking, Portfolio Management, Financial Consulting, or equivalent research experience.
Skills: Strong proficiency in financial modeling, valuation methodologies, forecasting, asset pricing, DCF analysis, market analysis, and risk assessment.
Professional Mindset: Detail-oriented, innovative thinker with a passion for financial technology and a commitment to collaboration. Prior experience with AI is not required, but a plus.

Why Join the HFC?

Advance Finance AI Solutions: Apply your financial expertise to solve complex, real-world challenges where your judgment shapes advanced AI reasoning and decision-making.
Professional Development: High-impact finance experts expand their influence through review projects, advisory roles, and research—while deepening their AI expertise, sharpening analytical and financial skills, and gaining hands-on experience with cutting-edge AI applications.
Join a Top-Tier Network: Collaborate with a global network of academics 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.

Application Process

Apply: We review applications on a rolling basis.
Complete a Challenge: Selected candidates will undertake a brief task designed to reflect HFC work and evaluate their domain expertise.
Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.

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.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Scale AI

Finance Fellow - Human Frontier Collective