Become a part of our team and shape the future powered by intelligent machines. If you're driven by ambition, success, fun, and learning, Nexaminds is where you belong. As a Data Testing Engineer , you will be the Qualit…
Engineering & IT · Cincinnati, OH
Machine Learning Engineer jobs in Cincinnati, OH
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
142
Open roles today
$40–$103/hr
Typical pay range
$137k
Median, full-time
5
Fresh in this list
No email, no resume, no sign-up. Save any listing below and you start anonymously.
You're signed in. Saving a listing drops it straight into your pipeline.
01
Open machine learning engineer roles
12 shown of 142 · sorted by freshness
$55 - $70 per hour
Cincinnati, Ohio Duration: Contract Job ID: 178780 Job Overview: We are seeking a highly skilled and experienced Senior Data Engineer to design, develop, and support scalable IBM DataStage ETL solutions and enterprise da…
part of our dynamic and cohesive community. Job Title: Data Engineer II Location: Cincinnati, OH (Downtown 4x/wk) Years of... ...and recommend durable solutions. Curiosity and willingness to learn business context, data…
techniques to measure business impact, build production-ready machine learning solutions, and translate analytical insights into measurable... ...scalable, production-ready ML pipelines using software engineering and MLO…
Healthcare, Technology, Transportation, and local and federal Government agencies. Job Description Position : QA Data Engineer Location : Cincinnati, OH Job : Onsite Job Description : ~10+ years over all experience requi…
Our corporate activities are growing rapidly, and we are currently seeking a full-time, office-based Junior Data Engineer to join our Information Technology team. This position will work on a team to accomplish tasks and…
$30 - $35 per hour
*(513)229-2020 Job Title: Maintenance Engineering Technician Job Description This role... ...equipment, including steel draw machines, cutting machines, presses, threading machines... ...in workforce and business solutio…
Responsibilities: ~ Advance our AI capabilities by designing, developing, and deploying Gen AI solutions-including LLM fine-tuning, prompt engineering, RAG pipelines, agentic workflows, and integration of Gen AI into exi…
the US, Central and South America as needed. The Field Service Engineer will work on a team or individually, to install, perform preventive... ...and deliver trainings on Colibrium additive manufacturing machines. These…
$95k - $140k
Job Description Summary This role is a hybrid between an AI engineer, data scientist, and software developer, designed for someone who can operate across the full lifecycle of AI system development. You'll play a key rol…
Job Description Job Description Sr. Data Engineer for Cincinnati OH Will work on the projects from inception to end using Azure cloud technologies like PySpark, Spark SQL, Azure Data Lake Storage, Azure Data Factory, Azu…
work alongside fellow development specialists and become a crucial part of our dynamic and cohesive community. Job Title: Data Engineer - Datastage ETL I Location: Cincinnati, OH (Madisonville) Years of Experience: 2-4 T…
02
What machine learning engineers earn in Cincinnati
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $40–$56 | $84k–$116k |
| Mid level | $56–$76 | $116k–$158k |
| Senior | $74–$103 | $153k–$214k |
Adjusted for the Cincinnati market from national ranges.
03
What employers ask for
The skills these listings keep naming
Python and software engineeringPyTorch or TensorFlowML fundamentals and evaluationModel serving and APIsMLOps (tracking, registries, CI)Docker and KubernetesData pipelines and feature storesLLM fine-tuning and RAG (a plus)Monitoring and drift detection
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through taking a model from prototype to production.
Cover data pipelines, training reproducibility, serving, and monitoring. Emphasize that the model is a small part of the system — that framing is the job.
How do you monitor a model in production?
Discuss input drift, prediction distributions, delayed labels, and business metrics — plus what triggers retraining. Mention that silent degradation is the default failure mode.
How would you reduce inference latency or cost for a large model?
Options include distillation, quantization, batching, caching, and smaller models. Frame it as measuring first, then choosing the cheapest acceptable quality tradeoff.
Tell me about a time a model failed in production. What happened?
A real story about skew, drift, or a data bug — with detection and prevention — is far more convincing than claiming smooth deployments.
How do you evaluate a model beyond accuracy?
Talk about the metric matching the business cost of errors, slicing by segment, and offline-online gaps. Naming a case where accuracy misled is a strong touch.
When would you fine-tune an LLM versus use retrieval or prompting?
Start cheap: prompting, then RAG for knowledge, fine-tuning for behavior and format. Cost and maintenance burden should drive the answer.
How do you make training reproducible?
Version code, data, and config; track experiments; pin environments. This is engineering discipline applied to ML, which is exactly the role.
05
Resume tips that move the needle
For machine learning engineers specifically — generic advice costs you here
01
Center bullets on production systems: models served, request volume, latency, and the business metric they moved.
02
Show software engineering credentials explicitly — testing, CI, code review — since MLE hiring filters hardest on engineering rigor.
03
Name the MLOps tooling you have run (MLflow, SageMaker, Kubeflow, vector databases) as these are common screens.
04
Include LLM work with specifics — fine-tuning, RAG, evaluation — if you have it; vague 'GenAI experience' claims read poorly.
05
Distinguish your role on shared projects: built the serving layer, owned the pipeline, or trained the model.
06
Where this role goes
Typical progression
01
ML Engineer
02
Senior ML Engineer
03
Staff ML Engineer
04
ML Platform Lead
Ten quiet minutes a day
Applying for machine learning engineer jobs in Cincinnati?
Robbi carries this page into your first day: your role, your city, your shift preference. Then it hands you a few small things each morning and keeps the pipeline honest.
Save what looks right here, then let Robbi hand you a few small things each morning and keep the follow-ups honest.
Start with this search
No email, no resume, no sign-up.
Open your tracker
Everything you saved is already there.