$25 - $30 per hour
Field Service Engineer (Controlled Environments) Territory: Wisconsin & Midwest Compensation: $25-$30/hour + Quarterly Bonus + Ownership Equity About Class 1 Air Class 1 Air has been the Midwest's largest single source f…
Engineering & IT · Milwaukee, WI
Machine Learning Engineer jobs in Milwaukee, WI
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
88
Open roles today
$41–$105/hr
Typical pay range
$140k
Median, full-time
8
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01
Open machine learning engineer roles
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are the secrets to our success -- so we give you unlimited access to everything you need to create innovative new solutions on our engineering team. As a Sr. Data Engineer, you will design, build, and support scalable da…
$132.26k - $155.6k
every stage of your career. Try new things, learn new skills and discover what you excel... ...such as statistics, computer science, engineering or applied mathematics, or equivalent work... .../statistics, predictive mo…
We are looking for a Data Engineer to help shape and expand a cloud-focused data environment that supports analytics, operational reporting, automation, and emerging AI use cases. Based in Brookfield, Wisconsin, this pos…
$94.94k - $185.62k
: ANA United StatesWork Type: HybridDate Posted: 2026-08-28Arcadis is the world's leading company delivering sustainable design, engineering, and consultancy solutions for natural and built assets.We are more than 34,000…
IntroductionWe are looking for an Automation Engineer, SVS to join our Services Business Line,... ..., accountability, continuous learning, and practical problem-solving.What you’... ...to connectivity, digital services,…
$92.82k - $109.2k
opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.Job DescriptionThe Automation Engineer tests, creates, imple…
About the RoleAs Senior MLOps Engineer, you will focus on supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building scalable infrastructure, tools, and best practi…
$80 per hour
job summary: As a Senior AI/ML Engineer, you will play a central role in this transformation. You will be responsible for both building... ...5+ years of hands-on experience developing and deploying machine learning solu…
$23.1 per hour
subsidiary of WEC Energy Group, is seeking a Co-Op Student- Gas Engineer in our Milwaukee, Wisconsin and Pewaukee, Wisconsin locations.... ...perform required updates. * Participate in training opportunities to learn abo…
We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine learning infrastructure and deployment pipelines. The ideal candidate will have strong experience with cloud platforms,…
$70k - $100k
The Field Engineer supports on-site construction activities for commercial projects, ensuring work is completed safely, on schedule, within budget, and in compliance with plans and specifications. This role works closely…
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What machine learning engineers earn in Milwaukee
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $41–$57 | $86k–$119k |
| Mid level | $57–$78 | $119k–$162k |
| Senior | $75–$105 | $157k–$218k |
Adjusted for the Milwaukee 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
04
ML Platform Lead
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