ML Engineer, II - Simulation Enablement at Torc Robotics
Ann Arbor, MI
$153,200–$183,800
Aug 6, 2026
Ann Arbor, MI
Sep 24, 2026
What this job asks for AI summary
This role embeds a Machine Learning Engineer within one or two Autonomy teams at an autonomous trucking company, acting as the primary liaison between a simulation/data platform and model teams working on perception, tracking, or behavior. Day-to-day work involves onboarding ML models to replay and recompute workflows, building and operating data pipelines at scale, ensuring metric evaluation and visualization tooling are adopted, and translating field feedback into platform requirements.
Mid level · 4+ years · Remote · 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 21,600 people nationally plausibly meet what this posting asks for (data scientists). range 9,100–32,500
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.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
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 (7)
The role is open to candidates in both the United States and Canada; the US-based flag is set to true because the US is explicitly included and the role is fully remote.
SOC classification is genuinely ambiguous: the role centers on ML model integration, data pipeline operation, and metric evaluation (pointing toward 15-2051 Data Scientists), but also involves substantial software engineering — building end-to-end data flows, onboarding pipelines, and debugging full-stack issues (pointing toward 15-1252 Software Developers). 15-2051 was chosen as the primary code given the ML model domain expertise and evaluation focus.
The degree requirement states a Bachelor's plus 4+ years OR a Master's plus 2+ years; because equivalent experience is not explicitly offered as a substitute for the degree, a Bachelor's could be considered a hard gate — however, the OR structure with a Master's makes the minimum ambiguous. Degree requirement is left as None to reflect that the threshold shifts with degree level.
Total years minimum is set to 4, reflecting the lower bound of the Bachelor's + 4 years path (the more common entry point).
No compensation figures are provided; the posting references a 'competitive compensation package' and notes pay varies by geography but gives no numbers.
Simulation/replay experience and autonomy/robotics ML model familiarity appear in the required qualifications section but are framed as domain knowledge rather than named tools, so they are not emitted as discrete skills per the schema rules.
Visualization tooling (Foxglove, OpenGL, Three.js) and large sensor data formats/tools (MCAP, Parquet, PyArrow, Daft, Pandas) and distributed compute frameworks (Ray, Anyscale, AWS HyperPods) all appear under the 'Bonus Points' section and are marked as preferred accordingly.
Read the full posting
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