Senior Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services)
Capital One · McLean, VA
$229,900–$286,200from the description
Jul 13, 2026
McLean, VA
Jul 21, 2026
What this job asks for AI summary
A senior engineering role focused on building and operating large-scale ML infrastructure — covering distributed model training and inference, model orchestration, and observability — within a centralized AI platform team at a major bank. The work involves applying optimization techniques to improve production ML system performance and contributing to long-term technical roadmaps. It suits an experienced ML engineer with a strong background in both software engineering and applied AI, including familiarity with LLM inference, vector search, and cloud-based deployment.
Senior level · 6+ years · Washington-Arlington-Alexandria, DC-VA-MD-WV · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 8 times — it's one opening, so apply once.
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 3,950 people in the Washington-Arlington-Alexandria, DC-VA-MD-WV area plausibly meet what this posting asks for (software developers). range 2,100–5,100
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.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $158,337 (middle half $126,441–$180,105). 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 role spans multiple office locations (McLean VA, Cambridge MA, New York NY, San Francisco CA, San Jose CA); McLean VA is used as the primary CBSA since it is Capital One's headquarters and listed first. Compensation ranges vary by location: $229,900–$262,400 in McLean/Cambridge and $250,800–$286,200 in NY/SF/San Jose.
The programming language requirement lists Python, Go, Scala, or Java as interchangeable options; Python is named first and is the most common in ML contexts, so it is the primary skill with the others captured as alternatives.
The 6-year experience floor applies when the candidate holds a Bachelor's degree; a Master's degree reduces the requirement to 4 years. The lower bound (6 years) is used for the overall years minimum per the minimum-when-a-range rule.
Kubernetes, Kubeflow, Ray, and Polars appear only in a narrative 'broad stack' description ('such as … and more'), not in a requirements or qualifications section, so they are marked preferred.
The 7-year cloud platform experience and all other items under 'Preferred Qualifications' are marked preferred accordingly.
The alt SOC (15-2051 Data Scientists) reflects the strong ML research and algorithm-development emphasis; however, the primary framing is engineering and platform-building, so 15-1252 is the primary code.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML inference optimization.
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