McLean, VA

Salary
$269,100–$307,200from the description
Posted
Jul 14, 2026
Location
McLean, VA
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

A senior individual-contributor role focused on building and deploying machine learning models and systems at scale within the financial services sector. The work spans the full ML lifecycle — from designing data pipelines and cloud-based architectures to developing and reviewing model code — with an expectation of providing technical leadership, guiding architectural decisions, and mentoring other engineers. Suited to a deeply experienced ML engineer with a strong background in distributed computing and production ML systems.

Senior level · 10+ years · Washington-Arlington-Alexandria, DC-VA-MD-WV · Bachelor's required · Full-time

Advertised as Principal, but the requirements read as Senior.

Must have (2)
distributed computing · 10+ yrsPython, C, C++ or Scala · 6+ yrs
Nice to have (4)
Dask or Rapids · 2+ yrsNumPyPandasScikit-learn

“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 780 people in the Washington-Arlington-Alexandria, DC-VA-MD-WV area plausibly meet what this posting asks for (data scientists). range 580–1,000

Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.

What won't set you apart
Python88%

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 (7)

The title 'Distinguished Machine Learning Engineer' maps to Principal in advertised seniority (Capital One's 'Distinguished' is their top individual-contributor level). However, the actual requirements — 10 years of distributed computing experience, 6 years of programming, 3 years of ML lifecycle — are consistent with a strong Senior engineer, so seniority is set to Senior.

Two salary ranges are listed: $269,100–$307,200 for McLean, VA and $244,700–$279,200 for Plano, TX. The McLean, VA (Washington metro) figures are reported here as the primary location.

The role is genuinely ambiguous between 15-2051 (Data Scientists — ML modeling focus) and 15-1252 (Software Developers — productionizing ML systems at scale). The emphasis on production ML systems, data pipelines, and software components leans toward engineering, but the ML lifecycle and modeling expertise lean toward data science; 15-2051 is chosen as primary with 15-1252 as the runner-up.

The PyData ecosystem skills (NumPy, Pandas, Scikit-learn) appear under Preferred Qualifications with a '2+ years' qualifier on the broader ecosystem; they are listed individually as preferred skills.

High Performance Computing is listed as an alternative context for Dask/RAPIDS experience ('2+ years of experience using Dask, RAPIDS, or in High Performance Computing') — it is not a named tool and is therefore not emitted as a separate skill.

Soft-skill and leadership items ('ability to attract and develop high-performing engineers', 'ML industry impact through conference presentations') are not emitted as skills per extraction rules.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML development lifecycle.

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