in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world. We believe building engineering is more than system…
Engineering & IT · Nashville, TN
Machine Learning Engineer jobs in Nashville, TN
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
121
Open roles today
$43–$111/hr
Typical pay range
$148k
Median, full-time
12
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01
Open machine learning engineer roles
12 shown of 121 · sorted by freshness
$71.3k - $140.6k
Position Summary Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and help make... ...request handlingExperience with DockerExperience supporting machine learning workflowsExp…
our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your... ...centers to modernizing transmission systems, our industry-recognized engineers an…
$100.7k - $209.5k
-on. You will work closely with Demand Planning, Networking Engineering, Data Center Planning, Supply Chain, Product, and Finance teams... ...key demand drivers.Develop time-series, statistical, machine learning, and oth…
$102.68k - $171.13k
to be part of an inclusive, adaptable, and forward-thinking organization, apply now.We are currently seeking a Senior Oracle Data Engineer - Onsite to join our team in Nashville, Tennessee (US-TN), United States (US).We…
$91.4k - $187k
this role include (but are not limited to):Define and document learning objectives.Conduct research and collaborate with subject... ...and experience interacting with both business and development/ engineering staff at a…
$120.8k - $163.4k
The Forward Deployed Engineering (FDE) team within Business Innovation & AI (BIA) is looking for a Technical Program Manager who builds. FDE... ...coverage), 401(k) matching, paid time off, and parental leave. Learn more…
our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your... ...community, but around the world. HDR is looking for a Trenchless Engineer to join…
difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world. In the role of Engineer Rail, we'll coun…
in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.We believe building engineering is more than systems…
thinking organization, apply now.We are currently seeking a Data Engineer to join our team in Nashville, Tennessee (US-TN), United States... ...developing routines for managing data quality. Innovation and Learning: Quic…
in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world. HDR is seeking a Roadway Engineer to provide techni…
02
What machine learning engineers earn in Nashville
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $43–$60 | $90k–$125k |
| Mid level | $60–$82 | $125k–$170k |
| Senior | $79–$111 | $165k–$230k |
National ranges — pay in Nashville typically tracks these.
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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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