and derivatives trading applications. The successful professional will combine deep capital markets knowledge with strong Python engineering skills to automate and validate complex trading workflows. What's In Store For…
Engineering & IT · Charlotte, NC
Machine Learning Engineer jobs in Charlotte, NC
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
312
Open roles today
$42–$108/hr
Typical pay range
$145k
Median, full-time
5
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01
Open machine learning engineer roles
12 shown of 312 · sorted by freshness
$27 - $32 per hour
MedTech is seeking Mechanical Field Service Engineers to support a nationwide medical device... ...hydraulic assemblies on dialysis machines. Complete required rinse, flush, testing... ...outcomes and population health w…
Qualifications: College or University education in Electrical, Electronic, or Computer disciplines Passion for technology and learning new software and hardware products Hands-on experience with IP Networking, server har…
$43.5k - $87.5k
people who want a career, not just a shift. As an Associate Field Engineer, you are entering the industry on the ground floor with a clear... .... Ready to Grow: Sharpen your skills through self-directed learning. We exp…
$64.17k - $88.23k
-based communication networks sold to businesses, governments and individuals for their own use. Scope of Position: Field Engineer( s) provide on-site and remote technical assistance globally to both internal and externa…
If you are a Field Service Engineer/ Professional looking for an opportunity to grow and develop professionally, Emerson has an exciting... ...center of everything we do. So, let's go. Let's think differently. Learn, col…
and brush rigging. Develop quality requirements for installation of components, including site inspection and test plans and engineering data record sheets. Support unit alignment and assembly of critical components. Res…
$120k - $140k
searching the globe for innovative, collaborative minds to join our best-in-class Aecon community! What is the Opportunity? At Aecon Engineering Services Inc. (United), we are a team of engineers, builders, planners, and…
Charlotte, NC Our client seeks a senior MLOps / DevOps Engineer focused on platform and infrastructure. The role emphasizes building... ..., scalable, and automated cloud environments that enable machine learning develop…
Description Job Description Service Fulfillment - Data Network Engineer Location: Charlotte, NC About Conterra Conterra... ..., MPLS, BGP. Experience with Cisco IOS-XR or the ability to learn this platform in an acceptab…
$95k - $110k
boosting enhancements. What You Bring ~ Bachelor’s in Engineering, Physics, Materials Science, Life Science , or similar. ~3–... .... Clean, methodical work habits and a love for continuous learning. Why You’ll Love It Y…
Data Systems Engineer (AWS, Snowflake, RedShift, Python, Scala, Hadoop, Spark, Kafka, Hive, API, Handling, API Development, Data Migration, Batch Data Pipelines) in Charlotte, NC API Development, AWS, AWS Lambda, Data Mi…
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What machine learning engineers earn in Charlotte
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $42–$59 | $88k–$122k |
| Mid level | $59–$80 | $122k–$167k |
| Senior | $78–$108 | $162k–$225k |
Adjusted for the Charlotte 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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