$118.3k - $177.45k
Scientist to join our Audience & AI group as part of the Revenue Science engineering team. This role will be responsible for supporting product development efforts related to data analyses, AI, machine learning, optimiza…
Engineering & IT · Chicago, IL
Machine Learning Engineer jobs in Chicago, IL
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
339
Open roles today
$47–$119/hr
Typical pay range
$159k
Median, full-time
8
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Open machine learning engineer roles
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year + benefits We're looking for a hands-on Stand Maintenance Engineer to help keep our coffee drive-thru stands running smoothly.... ...Troubleshoot and service commercial refrigeration units, ice machines, and other c…
$91k - $115k
apply now.We are currently seeking a Business Consultant - AI/ML Engineer to join our team in Chicago, Illinois (US-IL), United States... ..., develop, and deploy scalable Artificial Intelligence and Machine Learning sol…
$100k - $200k
Introduction Since 1973, East West Bank has served as a pathway to success. With over 110 locations across the U.S. and Asia, we are the premier financial bridge between the East and West. Our teams of experienced, multi…
$85.6k - $149.4k
Sentri7 Drug Diversion platform. Working closely with product, engineering, data science, and customer-facing teams, this role helps... ...professional experience in data science, predictive modeling, or machine learning…
$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…
$140k - $180k
Machine Learning Engineer, Associate Director – AI Innovation Teams Fitch Ratings is seeking a Machine Learning Engineer to join our new AI Innovation teams in Chicago—a bold initiative building the AI-powered future of…
$125k - $140k
reporting and decision making. You will help migrate legacy processes to a cloud-native platform built on Azure, Databricks and modern engineering practices, while helping shape the target future state architecture.Respo…
$209k - $238.5k
Overview Machine Learning Engineer 5 (Senior Manager, IC) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and…
$179.4k - $204.7k
Overview Machine Learning Engineer 4 Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery en…
knowledge of regression analysis and statistics. · Experience with Python, SQL, Big Data, Hadoop, and data visualization tools. · Machine learning experience is a plus. · Ability to analyze large datasets and identify pa…
troubleshoot performance issues, and implement optimization techniques. Collaborate with data architects, data scientists, AI engineers, and analysts to support data-driven solutions. Support data modeling, ETL/ELT, mast…
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What machine learning engineers earn in Chicago
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $47–$65 | $97k–$135k |
| Mid level | $65–$88 | $135k–$184k |
| Senior | $86–$119 | $178k–$248k |
Adjusted for the Chicago 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
02
Senior ML Engineer
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Staff ML Engineer
04
ML Platform Lead
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