$110k - $150k
: J-U-B ENGINEERS, Inc. is seeking to hire a Professional Engineer – Lead, to work in our either our successful Salt Lake City or Logan... ...for more benefit details: To apply for this position and learn more about J-U-…
Engineering & IT · Salt Lake City, UT
Machine Learning Engineer jobs in Salt Lake City, UT
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
94
Open roles today
$45–$114/hr
Typical pay range
$152k
Median, full-time
5
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01
Open machine learning engineer roles
12 shown of 94 · sorted by freshness
Sr Data Scientist will work in teams addressing statistical, machine learning and data understanding problems in a commercial technology... ...include statisticians, computer scientists, software developers, engineers, p…
Sr. Entra ID Migration Engineer Location: Remote or Onsite - Salt Lake City, UT (for local candidates) Duration: 6+ Months W2 Contract Job Description We are seeking a highly experienced Sr. Entra ID Migration Engineer t…
$72k - $115k
development to deployment support. 2. Work closely with data engineers and developers to build and deploy interactive dashboards,... ...a good knowledge of the principal Python Data Science / Machine Learning (ML) librar…
$77.2k - $122.1k
and diversity, equity and inclusion. General Purpose The Grid Modernization organization is seeking a highly motivated Engineer I or Engineer II to support the design, implementation, commissioning, operation, and contin…
$60k - $75k
annual merit raises, and a 5% salary increase after six months. Learn, advance, and build a career that can take you in multiple... ...like food and beverage. Partner with automation and controls engineers to test, troub…
while undertaking routine preventative measures and deploying new hardware to users. Key Duties / Responsibilities The Support Engineer I has responsibility for Windows support including patch management and vulnerabilit…
industry-leading efficiencies, our best-in-class team leverages methodologies, governance and systems that are unparalleled in the engineering space. Are you looking for an opportunity to join a diverse group of professi…
DESCRIPTION: For our IT Department, we are seeking a Field Service Engineer to provide reliable, professional on-site support for end-user... ...you. Our industry-leading Alter Domus Academy offers six learning zones for…
Role Summary The Senior Service Engineer is the highest level of escalation within reactive support. This role resolves complex, high-impact issues, leads technical response during major incidents, and raises team capabi…
$140k - $231k
services and capabilities Plan and direct data science / machine learning projects within the team. Design and implement machine learning... .... Leverage best practices in machine learning and data engineering to develo…
$45 - $55 per hour
Position Overview We are seeking a highly skilled Field Service Engineer to install, commission, maintain, and troubleshoot industrial material handling and process equipment at customer manufacturing facilities across N…
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What machine learning engineers earn in Salt Lake City
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $45–$62 | $93k–$129k |
| Mid level | $62–$84 | $129k–$175k |
| Senior | $82–$114 | $170k–$237k |
Adjusted for the Salt Lake City 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
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ML Platform Lead
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