Cloud Engineer
SynthBee Inc. · Pembroke Pines, FL
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Jul 12, 2026
Pembroke Pines, FL
Jul 20, 2026
What this job asks for AI summary
This role sits at the intersection of cloud infrastructure and machine learning operations, covering tasks such as deploying and monitoring ML models in production, maintaining cloud pipelines on platforms like AWS, GCP, or Azure, and supporting infrastructure management including containerization and CI/CD workflows. It suits someone with hands-on cloud and MLOps experience who can also collaborate across engineering teams and contribute to documentation and knowledge sharing.
Mid level · National
“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 $138,970 (middle half $107,524–$175,762).
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 (5)
The role sits at the intersection of ML engineering and cloud/software development — it could reasonably be classified as a Data Scientist (15-2051) given the ML model deployment and pipeline focus, but the dominant day-to-day work (building scalable software, CI/CD, cloud infrastructure, production integration) points to Software Developers (15-1252).
The posting uses a non-standard 'Knowledge / Skills / Abilities' (KSA) structure rather than explicit 'Required' vs. 'Nice to have' sections. All items under this section are treated as hard requirements, as the framing ('you might be a good fit if you have') reads as a unified qualifications block.
AWS SageMaker / Azure ML / Google AI Platform appear under 'Skills' within the KSA block but are phrased as 'hands-on experience with cloud-based machine learning services' — a softer framing compared to the direct infrastructure requirements above, so marked as preferred.
No compensation, employment type, or degree requirement is stated in the posting.
Seniority is assessed as Mid: the role involves working 'under the guidance of senior engineers,' participating in (rather than leading) performance monitoring, and supporting (rather than owning) ML deployments — signals consistent with a mid-level contributor despite the breadth of responsibilities.
Read the full posting
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