Lead AI/ML Engineer (P4645) at 84.51°
Cincinnati, OH
$125,000–$207,000
Jul 16, 2026
Cincinnati, OH
Jul 21, 2026
What this job asks for AI summary
A hands-on technical lead role focused on building hybrid systems that combine classical optimization solvers with modern AI and ML techniques — such as surrogate models, learned heuristics, and neural network-augmented constraint formulations. The work spans prototyping through production deployment, including MLOps pipelines, reusable APIs, and benchmarking. Suited to engineers with a strong operations research background who also have practical ML engineering and software development experience.
Senior level · 4+ years · Cincinnati, OH-KY-IN · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 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
Roughly 40 people in the Cincinnati, OH-KY-IN area plausibly meet what this posting asks for (data scientists). range 10–60
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 $104,907 (middle half $82,240–$133,799).
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 (11)
The title 'Lead AI/ML Engineer (G3)' carries no standard seniority level word, so the title states no level; the actual requirements (4+ years, technical lead scope, mentoring, production ownership) support a Senior classification.
The role sits at the intersection of ML/AI and classical optimization (operations research), making it a genuine hybrid between Data Scientists (15-2051) and Software Developers (15-1252). The primary day-to-day emphasis on ML modeling, surrogate models, learned heuristics, and optimization algorithm design tips it toward 15-2051, but the strong software engineering and daily coding expectations make 15-1252 a close runner-up.
Degree requirement is marked None because the JD lists 'Bachelor's or Master's' as alternatives with no single minimum enforced, and equivalent experience is implicitly accepted in that framing.
Pyomo appears both in the ML/optimization library list (where 3-of-several are required) AND is called out explicitly as 'specifically required' — it is therefore treated as a standalone hard gate.
For the ML/optimization library requirement, the JD states fluency in NumPy, pandas, PySpark plus 'at least 3 of the following: PyTorch, TensorFlow, scikit-learn, and Pyomo (Pyomo specifically required).' PyTorch is listed as the primary with TensorFlow and scikit-learn as alternatives to satisfy the remaining slots.
For optimization solvers, the JD requires 'at least two' from a named list; Gurobi is listed first with the others captured as alternatives.
MLOps tooling (MLflow, Azure ML, Databricks) is required; MLflow is listed as primary with Azure ML and Databricks as alternatives.
Cloud platform familiarity is required with Azure preferred; AWS and GCP are listed as alternatives.
Operations research fundamentals (LP, IP, MIP, constraint programming, stochastic/combinatorial optimization), reinforcement learning / neural combinatorial optimization, and graph neural networks all appear under the 'Preferred Experience' section.
No compensation range is stated in the posting.
Location is inferred as Kroger's headquarters area (Cincinnati, OH); the posting does not explicitly state a city or remote policy.
Read the full posting
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