Senior AI Machine Learning Engineer
The Hartford · Charlotte, NC
$117,200–$175,800from the description
Jul 27, 2026
Charlotte, NC
Jul 28, 2026
What this job asks for AI summary
A hands-on Senior AI/ML Engineer at The Hartford's Employee Benefits Applied AI and Analytics team, responsible for building, deploying, and maintaining enterprise-scale predictive and applied AI solutions across pricing, underwriting, and sales workflows. The role covers the full ML engineering lifecycle — feature pipelines, batch and near-real-time scoring, model monitoring, and generative/agentic AI buildout — while also mentoring junior engineers. Hybrid schedule, 3 days in office per week.
Senior level · 6+ years · Hartford, CT · 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 8 people in the Hartford, CT area plausibly meet what this posting asks for (data scientists). range 5–10
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 $129,118 (middle half $108,055–$164,673). 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 title in the posting header reads 'Sr Data Engineer' but the body consistently frames the role as 'Senior AI Machine Learning Engineer' focused on ML model pipelines, scoring, and applied AI — the ML/AI framing drove the SOC choice toward Data Scientists (15-2051) over Software Developers (15-1252), though the heavy production-engineering emphasis makes this genuinely ambiguous.
AWS and GCP are both listed as required cloud environments; they are captured as separate required skills rather than alternatives because the JD implies both are in active use.
A Bachelor's degree is listed as a minimum but the JD explicitly accepts '6+ years of equivalent experience' in lieu of a degree, so degree requirement is treated as None.
Master's degree is listed as preferred, not required.
Orchestration tools (Airflow, Cloud Composer, Step Functions, Vertex AI Pipelines), generative/agentic AI patterns (RAG, LLMs), CI/CD, containers, and infrastructure-as-code appear under the 'Preferred Experience' section.
Docker and Terraform are not named explicitly; they are inferred from 'containers' and 'infrastructure-as-code concepts' in the Preferred section — included as preferred given the concrete underlying technologies they represent.
No sponsorship available; STEM OPT I-983 not supported.
Read the full posting
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