Senior AI Engineer - Clinical Reasoning at NxT Level
New York, NY
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Aug 6, 2026
New York, NY
Sep 24, 2026
What this job asks for AI summary
A hybrid-onsite Senior AI Engineer role at a clinical AI company in New York City, focused on building production-grade agentic reasoning, retrieval, and evaluation systems that support real patient consultations. The work spans the full ML lifecycle — from training pipelines and fine-tuning to search/ranking and evaluation infrastructure — in a live healthcare environment. Suited to a research-minded engineer comfortable owning complex AI systems end-to-end alongside clinical and product partners.
Senior level · 7+ years · New York-Newark-Jersey City, NY-NJ-PA · Full-time
Posted 3 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 560 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (software developers). range 160–840
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 $170,499 (middle half $133,523–$210,499).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 7, 2026. It is a model, not a headcount.
Why we read it this way (6)
The posting offers two parallel experience paths: an advanced degree plus 3+ years of applied AI/ML, or 7+ years of relevant ML experience without a degree requirement — the degree requirement is therefore None.
The role is classified as Software Developers (15-1252) rather than Data Scientists (15-2051) because the emphasis is on building production systems — agentic pipelines, retrieval infrastructure, evaluation platforms, and training pipelines — rather than statistical modeling or research analysis. The runner-up is 15-2051 given the strong ML research framing.
The 'deep experience in at least two' areas requirement covers agentic architectures, model evaluation, model training/fine-tuning, and retrieval/RAG — all are marked required as they collectively form the hard gate, even though a candidate need only demonstrate depth in two.
Reinforcement learning, distillation, RLHF, FHIR, EHR, HL7, and synthetic data generation appear under 'Bonus Experience' or as secondary methods and are marked preferred.
No compensation figures are provided beyond 'competitive salary' and equity — no numeric range to extract.
The posting is from a staffing/recruiting intermediary ('our client'); the actual employer is unnamed.
Read the full posting
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