-grade SAP solutions and drive digital transformation initiatives across global enterprises. Job Summary The Senior Machine Learning Engineer will design, build, and deploy enterprise-scale ML models and pipelines using…
Engineering & IT · Cleveland, OH
Machine Learning Engineer jobs in Cleveland, OH
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
80
Open roles today
$40–$102/hr
Typical pay range
$136k
Median, full-time
3
Fresh in this list
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Open machine learning engineer roles
11 shown of 80 · sorted by freshness
$124.45k - $171.12k
across a variety of processes including welding, cutting, brazing, machining, process automation, and field repair. The Company leverages... ...OH Employment Status: Salary Full-Time Function: Engineering Pay Range: ($12…
$105k - $115k
below and let me know if you would be interested in exploring the opportunity. Job Description:- Job Title: Voice Engineer Location: Gahanna, OH Onsite Duration: Fulltime Hire with TCS Salary Range:- $105K to $115K Plus…
$32.82 - $40.4 per hour
Job Title: Maintenance Engineer Job Description This role requires practicing integrity, respect, accountability, continuous improvement... ..., the global leader in workforce and business solutions. To learn more, visit…
$83.3k - $133.28k
runs the world. This position reports to: Digital Solution Engineering Manager __ In this role, you will have the opportunity to... ...union, Puerto Rico] Go to and click on "Candidate/Guest" to learn more Health, Life &…
automation tools. The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented... ...RAG), and enterprise data systems. Collaborate with data engineers, software en…
job summary: Join a leading provider of high-precision multi-spindle machine tools dedicated to high-volume component manufacturing. We are seeking a highly specialized Field Service Technician to be the front-line techn…
clients. If this sounds exciting to you, let's chat! SENIOR DATA ENGINEER We are looking for a highly skilled and strategic Senior... ...to support production-grade Artificial Intelligence and Machine Learning applicatio…
$45 - $55 per hour
Position Overview We are seeking a highly skilled Field Service Engineer to install, commission, maintain, and troubleshoot industrial material handling and process equipment at customer manufacturing facilities across N…
$36 - $42 per hour
Position Overview We are seeking a Field Service Engineer to install, maintain, troubleshoot, and repair advanced industrial machinery... ...motion systems and guideways, hydraulic or pneumatic systems, and machine geome…
$30 - $50 per hour
CNC Field Service Engineer - High Travel Opportunity (95%) Domestic and InternationalWhat You'll Do Travel up to 95% to install, align... ...screw replacements, hydrostatic way maintenance, and precision machine alignmen…
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What machine learning engineers earn in Cleveland
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $40–$55 | $83k–$115k |
| Mid level | $55–$75 | $115k–$156k |
| Senior | $73–$102 | $152k–$212k |
Adjusted for the Cleveland market from national ranges.
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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.
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Resume tips that move the needle
For machine learning engineers specifically — generic advice costs you here
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Center bullets on production systems: models served, request volume, latency, and the business metric they moved.
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Show software engineering credentials explicitly — testing, CI, code review — since MLE hiring filters hardest on engineering rigor.
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Name the MLOps tooling you have run (MLflow, SageMaker, Kubeflow, vector databases) as these are common screens.
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Include LLM work with specifics — fine-tuning, RAG, evaluation — if you have it; vague 'GenAI experience' claims read poorly.
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Distinguish your role on shared projects: built the serving layer, owned the pipeline, or trained the model.
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Where this role goes
Typical progression
01
ML Engineer
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Senior ML Engineer
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Staff ML Engineer
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ML Platform Lead
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