$209k - $238.5k
Overview Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll par…
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.
369
Open roles today
$47–$119/hr
Typical pay range
$159k
Median, full-time
2
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Open machine learning engineer roles
12 shown of 369 · sorted by freshness
Job Title: AI/ML Engineer Location: Chicago, IL (Hybrid) Type: Contract Core GenAI Expertise: Hands on experience working with GenAI applications including LLMs, RAG architecture, prompt engineering and Agentic AI concep…
$75k - $90k
Field Service Engineer - Plasma Technology About Oxford Instruments Our purpose is to accelerate the breakthroughs that create a... ...attire. o Proactive problem-solving and openness to continuous learning. o Effective…
Class of Q1' 2026 supporting the Data Center Critical Facilities Engineer. The training will be on the cutting-edge of technology in a... ..., or HVAC and skilled Mechanical trades? Or desire to learn a new skill or trad…
member of a victim of crime or abuse, or any other status protected by applicable law. We use artificial intelligence in our hiring process. Learn more here . This posting is for a backfill position, meaning it is to fil…
We're looking for a ** Machine Learning Engineer* * to help build and improve AI-powered products. You'll work with large datasets, train and evaluate machine learning models, and collaborate with software engineers to b…
$95 - $105 per hour
TEKsystems is seeking a Machine Learning Engineer to support one of our major customers that sits in Chicago. THIS IS 100% REMOTE and LONG TERM. Top 3–5 Skills - Strong engineering foundation. - Ability to understand the…
$150k - $225k
Senior Market Data Engineer Location : New York, Chicago, or San Francisco ROLE OVERVIEW Our client, a global, multi-strategy asset management firm, is hiring a Senior Market Data Engineer to join their team. The ideal c…
$110k - $120k
Job Description — Field Service Engineer II (LINAC) | Direct Hire (W2) Position: Field Service Engineer II (FSE II) – Linear Accelerators... ...discussed during interview). Engineers typically support 2–3 machines on ave…
AI/ML Software Engineer - Healthcare – Full-Time - Remote (Accepting applications from Mid-West and East Coast States, USA only) – Job ID 26AIML301 Description Serious Development is a boutique healthcare strategy, produ…
$40 - $45 per hour
Job Description Job Description Job Title: Data Center Service Technician (PDU Systems) Location: Greater Chicagoland Area Travel: Regional Travel, 75% Compensation: $40–$45/hour (straight time) + OT (1.5x) Schedule: On-…
restoration companies running thousands of jobs. This is not a “prompt engineer” role. You’ll design, train, and ship domain-specific language... ...to figure it out ~ If there’s something interesting to learn or solve,…
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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
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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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