Machine Learning Engineer II
CLEAR - Corporate · New York, NY
$180,000–$220,000from the description
Jul 26, 2026
New York, NY
Jul 27, 2026
What this job asks for AI summary
This role centers on building and owning machine learning systems for a digital identity platform, covering model design, deployment, and monitoring across applications such as document processing, image analysis, and fraud detection. The work also involves constructing data pipelines at scale and collaborating with product stakeholders on requirements. It suits engineers with hands-on end-to-end ML experience who are comfortable making architectural decisions independently.
Mid level · 3+ years · New York-Newark-Jersey City, NY-NJ-PA · Full-time
Posted 2 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 90 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (data scientists). range 55–140
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 $103,548–$176,968). 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 (4)
The role title is 'Machine Learning Engineer' with no seniority level in the title, so advertised seniority is Unspecified. The 3+ years requirement and scope (building end-to-end ML systems, mentoring junior members, architectural decision-making) support a Mid-to-Senior read; the relatively low years floor and the absence of explicit org-wide or cross-team leadership scope place this at Mid.
SOC is a genuine toss-up between 15-2051 (Data Scientists — ML modeling, feature engineering, model deployment) and 15-1252 (Software Developers — end-to-end system building, data pipelines, deployment). The ML modeling and feature engineering emphasis tips it to 15-2051, but the strong engineering/pipeline/deployment framing makes 15-1252 a close runner-up.
The tech stack (Python, Postgres, Snowflake, dbt, AWS SageMaker, MLflow) is listed in a brief narrative 'highlight' section rather than a formal requirements block. Python, AWS SageMaker, and MLflow are the most directly tied to the ML engineering responsibilities described throughout the posting and are marked required; Postgres, Snowflake, and dbt appear only in the stack highlight and are marked preferred.
Compensation of $180,000–$220,000 is described as covering combined base salary AND new-hire RSU equity grant; actual cash base will be lower than the stated range.
Read the full posting
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