Senior Machine Learning Ops Engineer at National Debt Relief, LLC.
UNAVAILABLE
$150,500–$173,000from the description
Jul 27, 2026
UNAVAILABLE
Jul 29, 2026
What this job asks for AI summary
This Senior MLOps Engineer role sits within the Data Platform organization and is responsible for building, deploying, and maintaining a scalable enterprise ML platform. Day-to-day work spans cloud infrastructure provisioning, CI/CD automation, containerized model serving, orchestration pipelines, and observability frameworks for production ML systems. The role suits an engineer who combines solid software development skills with hands-on cloud and MLOps operations experience.
Senior level · 6+ years · Remote · Full-time
Long application — this platform typically asks you to create an account and re-enter your work history.
“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 4,450 people nationally plausibly meet what this posting asks for (software developers). range 2,650–6,700
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.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762). 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 29, 2026. It is a model, not a headcount.
Why we read it this way (9)
The posting is tagged #LI-REMOTE, indicating fully remote work; no specific metro or state is required.
The degree requirement states 'Bachelor's degree … (advanced degree preferred)' — because an advanced degree is only preferred and no equivalent-experience clause is needed to waive the bachelor's, this is a soft gate; the degree requirement is set to None per the schema rule that only hard-required degrees are captured.
The 6-year overall experience figure comes from '6 years of experience in ML Ops, platform engineering, DevOps, or data platform engineering'; the 3-year AWS figure is captured on the AWS skill.
Kubernetes/ECS/EKS are listed under Required Skills as a single interchangeable requirement; ECS and EKS are captured as alternatives to Kubernetes.
FastAPI/Flask/Django are listed as interchangeable backend framework options under Required Skills; Flask and Django are captured as alternatives.
MLflow and its peer observability/experiment-tracking tools (Arize, Evidently, WhyLabs, Monte Carlo) appear under Preferred Skills and are marked accordingly.
Generative AI / LLM deployment experience appears under Preferred Skills and is captured as a preferred skill.
Feature store design and financial-services domain experience appear under Preferred Skills but name no specific technology, so they are omitted per the no-generic-concepts rule.
The SOC classification is Medium confidence: the role writes and ships ML infrastructure code (pointing to 15-1252 Software Developers), but has a substantial operational/platform-ops dimension that could also support 15-1244.
Read the full posting
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