Project Engineer Data Center MEP Location: Fort worth, TX Job Type: Long term contract Shift 1- Day Shift (7:00 AM 4:30 PM) Shift 2- (Swing Shift 3:30pm-1:00am) Key Requirements ~ Bachelor's degree required. ~ Support on…
Engineering & IT · Fort Worth, TX
Machine Learning Engineer jobs in Fort Worth, TX
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
128
Open roles today
$42–$107/hr
Typical pay range
$143k
Median, full-time
3
Fresh in this list
No email, no resume, no sign-up. Save any listing below and you start anonymously.
You're signed in. Saving a listing drops it straight into your pipeline.
01
Open machine learning engineer roles
12 shown of 128 · sorted by freshness
$65 - $70 per hour
that can be effectively built and maintained by less experienced engineers ~Anticipates trouble areas in systems under development and... ...mentors teammates and helps guide them to and along needed learning journeys ~O…
implementation and adoption. Our team brings expertise across artificial intelligence and data, digital experience, and platform engineering, enabling the organizations we serve to build lasting internal capability. We o…
$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…
challenges with flexibility and grace, learning new skills and advancing your career while... ...governance. The Data domain leans into Machine Learning and AI, as well as Data Science... ...decisions Implement data migr…
$90 - $100 per hour
Job Title: Data Scientist – Machine Learning & Generative AI Location: Fort Worth, TX 76155 (Hybrid) Durations: 6-12+ Months with possible... ...Experience working as a Data Scientist, Machine Learning Engineer, or in a…
Field Service Engineer - NETA Testing Spark Power, a trusted partner in energy in North America, is looking for a Field Service Engineer – NETA Testing in the Dallas-Fort Worth area to join our team. As a Field Service E…
$65 - $70 per hour
Position - Security Engineer Location - Fort Worth, TX (Hybrid) Job ID - 178604 Position Overview We are seeking a Directory Services Engineer to support critical cybersecurity initiatives focused on identity infrastruct…
Liaison Stress Service Engineer CS SVC Tech Spec II - Ft. Worth, TX in GAC Fort Worth Unique Skills: At Gulfstream, our people are at the heart of everything we do. We believe in inspiring and empowering every individual…
performance Tuition assistance Job Title: Senior Data Engineer Company: Techoauth Solutions LLC Location: Fort Worth... ...healthcare data or HIPAA compliance Experience working with AI or machine learning data platforms…
and retrieval processes to support data warehousing and analytics. ~ Provide technical leadership and mentorship to junior data engineers. ~ Ensure compliance with industry standards and best practices in data engineerin…
$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…
02
What machine learning engineers earn in Fort Worth
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $42–$58 | $87k–$121k |
| Mid level | $58–$79 | $121k–$165k |
| Senior | $77–$107 | $160k–$223k |
Adjusted for the Fort Worth 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.
06
Where this role goes
Typical progression
01
ML Engineer
02
Senior ML Engineer
03
Staff ML Engineer
04
ML Platform Lead
Ten quiet minutes a day
Applying for machine learning engineer jobs in Fort Worth?
Robbi carries this page into your first day: your role, your city, your shift preference. Then it hands you a few small things each morning and keeps the pipeline honest.
Save what looks right here, then let Robbi hand you a few small things each morning and keep the follow-ups honest.
Start with this search
No email, no resume, no sign-up.
Open your tracker
Everything you saved is already there.