Development, and Validation (VDDV) team is at the forefront of advanced engineering at General Motors, applying state-of-the-art CAE methods to... ...work and at home-so you can focus on realizing your ambitions. Learn h…
Engineering & IT · Detroit, MI
Machine Learning Engineer jobs in Detroit, MI
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
145
Open roles today
$40–$103/hr
Typical pay range
$137k
Median, full-time
11
Fresh in this list
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01
Open machine learning engineer roles
12 shown of 145 · sorted by freshness
$68.3k - $192.9k
what matters.The Battery Manufacturing Engineering team is opening new highways with our next... ...of industrial process, PM planning, and machine safety standards.Vision Systems:... ...management processes, and capture…
Hardware (CCH) is part of GM’s Vehicle Software & Electronics Engineering (VSEE) organization within Software & Services Engineering. The... ...work and at home-so you can focus on realizing your ambitions. Learn how GM…
Job DescriptionAs a Virtual Analysis Engineer in GM’s Body Manufacturing Product Interface organization, you will help ensure vehicle designs... ...manufacturability in digital environments.Ability to learn and apply new…
Managing Director, Data Engineering & AIWho You'll Work WithAs a Managing Director in Slalom's Data & AI practice, you will lead the... ...organizations build the data foundations required to enable machine learning, gen…
$87.91k - $146.52k
: 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…
DescriptionRole overviewGeneral Motors is seeking a Principal Engineer to define the technical direction for next-generation camera systems... ...work and at home-so you can focus on realizing your ambitions. Learn how G…
$115.5k - $218.1k
to contribute to advancements in autonomy, electrification, smart mobility technologies, and more!In this position... The Systems Engineering Teams (SET) are focused on cross functional collaboration to rethink the base…
assignment in support of DTE’s emergency response to storms or other events that impact service to our customers.Job Summary Senior level engineer responsible for planning and conducting intermediate to more complex engi…
Job-ID29174198Reference26-24297Project Engineer Mechanical - PTW(Powertrain - Machining & Assembly)SummaryThe Project Engineer is accountable for the design... ...• Lead handover meetings with ESC • Review Lesson Learned…
to choose between performance and sustainability, design and engineering, ambition and integrity. In Lucid Air and Lucid Gravity, we have... ...hands-on support for the Auros QMS platform, lead lessons- learned and read-…
$40 - $42 per hour
Must Have Skills: ⦁ Bachelor’s degree in Electronics Engineering, Electrical Engineering, or related field with 5 or more years of experience ⦁ Strong knowledge of analog and digital circuit design specifically DC-DC con…
02
What machine learning engineers earn in Detroit
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 Detroit 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.
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Where this role goes
Typical progression
01
ML Engineer
02
Senior ML Engineer
03
Staff ML Engineer
04
ML Platform Lead
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