Staff Machine Learning Engineer - Data at Kodiak
San Francisco, CA
$200,000–$265,000
Jul 20, 2026
San Francisco, CA
Jul 22, 2026
What this job asks for AI summary
This role centers on building and improving the data infrastructure that feeds machine learning models for an autonomous trucking system. Day-to-day work involves automating data pipelines using orchestration frameworks, curating and stratifying large-scale driving datasets, and maintaining metrics dashboards and datastores. It suits engineers with a background in ML data infrastructure, ideally with experience handling sensor data such as camera, lidar, or radar in a robotics or autonomy context.
Mid level · 3+ years · San Jose-Sunnyvale-Santa Clara, CA · Master's required · Full-time
Pay in the description: $200,000–$265,000
“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 30 people in the San Jose-Sunnyvale-Santa Clara, CA area plausibly meet what this posting asks for (database architects). range 8–50
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $202,313 (middle half $144,101–$222,457). 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 (7)
The role title is 'Machine Learning Engineer' but the day-to-day work is squarely focused on data pipelines, ELT infrastructure, dataset curation, and tooling for ML teams — not model research or training. This makes 15-1243 (Database/Data Architects) the closest SOC match, with 15-2051 (Data Scientists) as a plausible runner-up given the ML context.
The JD requires 'MS or PhD' as a minimum degree; MS is treated as the hard floor (Masters).
The '3+ years of practical experience working with ML teams' is stated alongside the degree requirement in the 'What you'll bring' section and is treated as the role-level experience minimum.
Apache Airflow and Metaflow are listed as interchangeable orchestration options ('AirFlow/Metaflow like orchestration frameworks'); Metaflow is captured as an alternative.
LLMs are mentioned in a narrative context ('utilizing LLMs and offboard models') as part of a broader tooling aspiration rather than a hard gate, so they are marked preferred.
The pay range ($200,000–$265,000) is stated as a base salary range for the SF/Silicon Valley location and spans 'several internal levels'; actual pay will vary by experience and interview performance.
The posting notes that some roles may require export-control eligibility checks (U.S. person status/citizenship), but no formal security clearance is explicitly required.
Read the full posting
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