Engineering Manager, Machine Learning Platform at Affirm
$204,000–$290,000from the description
Jul 26, 2026
—
Jul 27, 2026
What this job asks for AI summary
An engineering manager role leading a team responsible for the infrastructure that powers machine learning model training and serving at a fintech company. Day-to-day work spans roadmap planning, team coaching, and staying hands-on with technical decisions across GPU infrastructure, deployment workflows, and low-latency serving systems. Best suited to someone with a background in production ML or distributed systems who has prior experience managing engineers.
Senior level · 7+ years · Remote · Full-time
“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 14,400 people nationally plausibly meet what this posting asks for (computer and information systems managers). range 6,100–21,600
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
What the occupation pays Median $178,991 (middle half $141,096–$225,584). 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 (8)
This is a people-management role with direct reports, hiring responsibility, and roadmap ownership — classified as Computer and Information Systems Managers (11-3021). The alt SOC (15-1252) reflects the JD's emphasis on meaningful hands-on engineering involvement and technical judgment.
The role is fully remote (#LI-Remote) with no fixed primary location; two US pay tiers are given (CA/WA/NY/NJ/CT: $230K–$290K; all other US states: $204K–$264K). The pay band figures reflect the full US range ($204K–$290K).
The degree requirement states 'Bachelor's degree in a technical field or equivalent practical experience' — equivalent experience is explicitly accepted, so no hard degree gate is set.
The 7+ years overall experience requirement includes 2+ years managing engineers; the management tenure is a role-level gate captured in the overall years minimum (7).
Model training, model serving, deployment workflows, and GPU infrastructure are listed as a set of alternatives — the JD requires hands-on experience in 'at least one of' these areas.
Deep learning, transformer architectures, and large-scale training/serving are framed as 'familiarity with modern ML workloads' — treated as preferred rather than hard gates.
Applied ML modeling experience is explicitly called 'a plus' — omitted from the skills list as it names no specific technology.
No specific named technologies, frameworks, or tools (e.g. PyTorch, Kubernetes, Kubeflow, Ray) are mentioned anywhere in the posting; the skills extracted reflect the capability areas the JD does name.
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.