Job Summary This job req is subject to Job Description This job req is subject to overtime discounts (0.95x exempt; 1.35x non-exempt) and a 10% discount after six months of service Dell certifications are required once a…
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.
222
Open roles today
$40–$103/hr
Typical pay range
$137k
Median, full-time
4
Fresh in this list
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01
Open machine learning engineer roles
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Engineer smarter solutions. Strengthen every project. This position provides technical support and education of specified products... ...our purpose, Making Construction Better, we’re driven to keep learning, growing, an…
and services that help our clients optimize their operations and captivate their customers. Job Description The Field Engineers are responsible for supporting the identification of quality issues and assisting with hands…
for a greener, safer, better world of mobility. AVL Test Systems Inc. is growing our Service team and looking for a Senior Service Engineer to support a key customer near Plymouth, Michigan. This is an exciting opportuni…
Job Title: ML Ops Engineer Location: Dearborn, MI (Hybrid 4 Days/Week Onsite) Duration: 12 Months Note Only W2... ...experienced ML Ops Engineer to design, build, and optimize scalable machine learning data pipelines on…
My name is Mahalakshmi, and I'm reaching out from Intellectt Inc. regarding an exciting contract opportunity for a Plant Modelling Engineer based in Warren, MIwith one of our prestigious clients. I would love to connect…
well. My name is Purna , and I m reaching out from Intellectt Inc . regarding an exciting opportunity for a Plant Modelling Engineer based in Warren, Michigan (Onsite)with one of our prestigious clients. I would love to…
Bargaining Unit: 2290-Detroit Building & Trades CouncilPlumbers Loc Description Plumbing Inspector Buildings Safety Engineering & Environmental Department "We create safe environments for city residents." The BSEED missi…
$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…
actionable insights that give our clients a competitive advantage. We're seeking a Senior Full-Stack BI Architect / Fabric Data Engineer to design and implement innovative, domain-driven data solutions that humanize data…
scarcity, quality, productivity, and energy. Together, we pursue a shared mission to create a more sustainable future. As the Field Engineering Intern you will be joining a strong technical service environment. In this r…
$146k - $219k
join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated t…
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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.
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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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