AI Alignment Fellow at National Fair Housing Alliance
Washington, DC
$31.25/hrfrom the description
Jul 9, 2026
Washington, DC
Jul 21, 2026
What this job asks for AI summary
An eight-week, part-remote research fellowship based in Washington, D.C., focused on the mathematical relationship between individual and group fairness in machine learning systems. The fellow will conduct formal theoretical work — including proof development and functional bound derivation — alongside legal and policy analysis of anti-discrimination frameworks, using AI-assisted tools throughout. Output includes co-authored academic papers, technical reports, and policy briefs aimed at civil rights practitioners and regulators. Best suited to a quantitatively rigorous researcher with grounding in algorithmic fairness theory and an interest in civil rights law.
Mid level · Washington-Arlington-Alexandria, DC-VA-MD-WV · Temporary
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 800 people in the Washington-Arlington-Alexandria, DC-VA-MD-WV area plausibly meet what this posting asks for (data scientists). range 420–1,050
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $135,107 (middle half $108,024–$176,763). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (10)
This is an 8-week temporary fellowship, not a permanent position. No benefits or leave accrual are included.
The role is hybrid: 2 days/week in NFHA's Washington, DC office on Pennsylvania Avenue, with the remainder remote. It is not fully remote.
The primary degree requirement is a doctoral degree in progress or conferred in a quantitative discipline; however, candidates with a master's degree and demonstrated research experience are explicitly considered — so no hard degree floor is set.
SOC classification is genuinely ambiguous: the role blends formal ML/statistics research (15-2051 Data Scientists) with AI governance and policy analysis work that could fit 15-1299 (Computer Occupations, All Other). The mathematical/computational research emphasis was treated as primary.
Python and R are listed together as a joint proficiency requirement ('Python and/or R'); Python is named first and R is captured as an alternative.
Mathematica and SageMath are listed as interchangeable symbolic computation environments under a preferred/familiarity framing ('familiarity with… such as Mathematica, SageMath, or equivalent').
Fairlearn and AIF360 are listed as preferred fairness toolkits ('preferred'), not hard requirements.
AI governance policy experience (civil rights law, anti-discrimination frameworks) is described as 'strongly preferred' and 'a significant asset' — not a hard gate.
'Algorithmic fairness' is retained as a named skill because the JD gates on demonstrated working knowledge of specific, named fairness criteria (demographic parity, equalized odds, calibration, Lipschitz continuity) as a hard requirement; it is the closest canonical label for this concrete technical domain.
Posting is for a temporary engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.
Read the full posting
The employer publishes the full description on their own site — read it there ↗. Or sign in to read it here — it's free, and it also lets you track this application.