Senior Machine Learning Engineer at Tocaro Blue
Birmingham, AL
$130,000–$162,000
Jul 22, 2026
Birmingham, AL
Jul 24, 2026
What this job asks for AI summary
This role centers on building custom deep learning models for maritime perception — covering object detection, semantic segmentation, and multi-target tracking applied to radar and camera sensor data. The engineer will own dataset design, model training on large proprietary datasets, and deployment to resource-constrained edge hardware, while contributing to sensor fusion pipelines used in autonomous surface vessels for both defense and commercial marine markets. A strong background in ML beyond standard detectors, particularly with noisy or non-vision sensor modalities, is expected.
Senior level · 7+ years · Birmingham-Hoover, AL · Master's required · Secret clearance · 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
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $96,312 (middle half $74,840–$124,979).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (9)
The role sits at the intersection of ML research and software engineering — the primary day-to-day work is designing and training custom deep learning models (segmentation, tracking, fusion), which maps most naturally to Data Scientists (15-2051); however, the emphasis on deploying optimized C++ inference layers to edge hardware and building ML-Ops pipelines also supports Software Developers (15-1252) as a close runner-up.
Degree requirement: the JD states 'Advanced degree (MS/PhD)' as an essential qualification with no equivalent-experience escape clause, so Masters is set as the minimum hard-required degree.
Clearance: the JD states all employees must be eligible to obtain a U.S. DoD security clearance and restricts hiring to U.S. citizens and green card holders. This is framed as a gate ('must be eligible to obtain'), not merely a preference. The level is unspecified; Secret is the most common entry-level DoD clearance and is used here as the conservative interpretation.
The '7+ years' figure is stated at the role level ('applying machine learning and signal processing to real-world dynamic systems'), not tied to any single named technology, so it is captured as the overall experience minimum.
Semantic segmentation and object detection/classification are listed under essential qualifications with firm language ('demonstrated mastery'), so they are marked required even though they are methodologies — they are concrete, named ML task categories central to this role's gatekeeping.
C++ inference deployment, CNNs/transformers/RNNs, computer vision, edge deployment, MLOps, SLAM, and sensor fusion all appear under the 'Preferred Expertise' section and are marked accordingly.
No compensation figures are provided; the posting references only 'competitive base salary with potential equity.'
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): edge/embedded ML deployment.
Requires a Secret clearance — the cleared population is a small fraction of this occupation, so the real candidate pool is materially smaller than the estimate below, which does not model clearance.
Read the full posting
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