Machine Learning Engineer
Jane Street · New York, NY
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Jul 22, 2026
New York, NY
Jul 23, 2026
What this job asks for AI summary
A machine learning engineering role focused on building and maintaining training and inference infrastructure, improving research workflows, and helping shape the direction of an ML platform used in a trading environment. The work spans the full lifecycle from experimentation to production, requiring solid grounding in ML techniques — such as neural networks, ensemble methods, and gradient-boosted trees — as well as the mathematics underpinning them.
Senior level · New York-Newark-Jersey City, NY-NJ-PA · 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 1,800 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (data scientists). range 1,350–2,350
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 the occupation pays Median $138,970 (middle half $103,548–$176,968).
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)
Jane Street is headquartered in New York City; no location is stated explicitly in the posting, but the company's primary office is NYC. Remote is not offered.
The posting deliberately avoids a fixed qualifications list and states no minimum years of experience. Seniority is assessed as Senior based on the scope described: production ML infrastructure ownership, research workflow design, and end-to-end concept-to-production delivery.
PyTorch is called out as the team's preferred framework; JAX and TensorFlow are listed as welcomed alternatives in the same sentence and are captured in 'alternatives' accordingly.
Neural networks, random forests, and gradient boosting appear in narrative/context describing the breadth of modeling knowledge desired, not in a formal requirements section — marked as preferred.
No compensation, degree requirement, or clearance is mentioned. Employment type is inferred as full-time based on the permanent team-member framing ('join our growing ML team').
The role sits at the boundary between Data Scientist (ML modeling expertise, mathematical foundations) and Software Developer (building and maintaining ML infrastructure, research codebases). Data Scientist is the primary classification given the explicit emphasis on modeling techniques, mathematical background, and ML research; Software Developer is the runner-up given the strong infrastructure and engineering craft emphasis.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML training and inference infrastructure.
Read the full posting
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