Senior Computer Vision / Applied AI Engineer at Simbe Robotics
$160,000–$200,000
Aug 4, 2026
—
Sep 25, 2026
What this job asks for AI summary
A Senior Computer Vision / Applied AI Engineer role at a retail robotics company, focused on building and owning production CV models across object detection, segmentation, OCR, barcode decoding, product recognition, and visual search. The engineer will manage the full model lifecycle — from dataset curation and annotation quality through training, evaluation, deployment, and production monitoring — with direct impact on retail shelf intelligence use cases.
Senior level · 5+ years · Full-time
Quick apply — this platform usually takes a CV and a few fields.
“or” means any one of them counts — you don't need all of them.
Posted 4 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
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 6, 2026. It is a model, not a headcount.
Why we read it this way (7)
No compensation is mentioned.
The role sits at the boundary between Data Scientists (15-2051) and Software Developers (15-1252): it involves heavy ML modeling and research (favoring 15-2051) but also production software engineering, data pipelines, and deployment tooling (favoring 15-1252). 15-2051 was chosen as primary given the dominant emphasis on model training, evaluation, and CV research.
PyTorch and TensorFlow are listed as alternatives since the posting requires one 'or' the other; PyTorch is named first.
ROS and ROS2 are listed as alternatives since the posting treats them interchangeably.
FiftyOne, CVAT, Labelbox, and Roboflow are listed as alternatives under a single skill since the posting presents them as equivalent data-centric ML tooling options.
'Synthetic data generation' is listed under Bonus Qualifications alongside simulation and active learning; it is marked preferred accordingly.
Barcode decoding and product recognition appear in the required qualifications section under 'Bonus Qualifications' (retail/product recognition context), so they are captured as preferred rather than hard gates.
Read the full posting
The employer publishes the full description on their own site — read it there ↗. Or sign in to read it here — it's free, and it also lets you track this application.