Lead Engineer, MLOps at NxT Level
Boston, MA
$374,400–$499,200
Jul 21, 2026
Boston, MA
Jul 23, 2026
What this job asks for AI summary
A hands-on engineering leadership role responsible for owning the ML platform roadmap and managing a team covering ML infrastructure, MLOps, and embedded data science engineering at a logistics technology company. Day-to-day work spans standardizing training and serving infrastructure, deployment pipelines, and monitoring, while embedding engineers into production science systems for forecasting, routing, pricing, and supply chain optimization. Suits an experienced ML engineer comfortable splitting time between people management, architecture, and writing code.
Senior level · 4+ years · Remote · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
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
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 $178,991 (middle half $141,096–$225,584).
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 (10)
The role is titled 'Technical Lead Manager' with explicit people-management duties (lead and grow a team, roadmap ownership, hiring bar), making 11-3021 the primary SOC. However, the posting strongly emphasizes hands-on technical contribution — architecture, code reviews, writing code, on-call — so 15-1252 is a genuine runner-up.
The degree requirement is structured as a minimum: Bachelor's + 6 years OR Master's + 4 years. A Bachelor's is the lower gate; the overall years minimum is set to 4 (the minimum years possible under either path, paired with a Master's).
AWS is listed as 'preferably AWS' within the required qualifications section — it is still a hard gate on cloud platform experience; AWS is named as the preferred option with alternatives Azure/GCP.
Redshift, Databricks, and Snowflake are listed together as interchangeable examples of data warehouse experience in the required section; Redshift is used as the primary with the others as alternatives.
Ray, Flink, and Feast are listed together as interchangeable examples of open-source large-scale ML tooling in the required section; Ray is used as the primary with the others as alternatives.
ML training infrastructure, serving infrastructure, feature stores, orchestration, monitoring, and deployment pipelines are all enumerated within the required ML platforms experience bullet — each is a distinct capability gate.
The Bonus Experience section is clearly labeled as optional; all skills drawn from it are marked preferred.
No compensation figures are provided in the posting.
Location is listed as 'United States' with no specific city or metro; the role appears to be remote-US.
Ignored 4 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML orchestration, logistics/supply chain ML, ML templates/internal platforms, AI-assisted development.
Read the full posting
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