$75 - $80 per hour
Job Description Job Description Senior AI Software Engineer – Agentic AI / PythonJob at a Glance Title: Senior AI Software Engineer – Agentic AI / Python Location: Orlando, FL (onsite 4 days per week) Contract: W2 only,…
Engineering & IT · Orlando, FL
Machine Learning Engineer jobs in Orlando, FL
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
193
Open roles today
$42–$108/hr
Typical pay range
$145k
Median, full-time
3
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Open machine learning engineer roles
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in the United States with Middlesex Paving earning an equally solid regional presence and reputation. Position Summary: The Field Engineer in heavy civil construction plays a vital role in supporting project execution by…
entertainment ecosystem. The Data Science team partners with data engineering, marketing, product, and executive teams to transform... ...industry experience (excluding internships) in data science and machine learning,…
$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…
$64.5k - $129.5k
we provide a work home for seasoned experts. As a Senior Field Engineer, you are the primary technical owner for turn-key project delivery... ...Dependent Care Spending Account Tuition Assistance To learn more about our…
$27 - $29 per hour
minutes to complete. Position Description: Our Field Service Engineers experience a unique opportunity to employ their technical... ...help improve patient outcomes and population health worldwide. Learn more at IQVIA is…
Job Details: Plumbing / Fire Protection Engineer – Orlando, FL Join a growing MEP consulting engineering firm with a strong project pipeline and a collaborative team environment. We are seeking a Plumbing / Fire Protecti…
Consulting, Information Technology, and Research Development and Engineering services. The fundamental distinction of the OST team is... ...industries. OST is successful because we listen to our clients, we learn from ou…
$62k - $101k
Position Summary The Analyst Maintenance and Engineering (M&E) Systems is responsible for ensuring the efficiency and reliability of the M&E tracking system (Trax-aero) from the business end by troubleshooting and resolv…
SUMMARY The Service Engineering Manager is a support function of our LTSA/Service Operations groups. The overarching goal is to provide technical engineering services to enable Mitsubishi Power to be first in class large…
$74k - $95k
Because of their continued growth, a General Contractor in the South Seattle (Tacoma) Area is seeking an Field Engineer - Commercial Construction Ground-up to join their team. As a leader in the building industry, my cli…
$35 - $50 per hour
FIELD SERVICE ENGINEER Seeking a Field Service Engineer who thrives in fast-paced industrial environments and is comfortable traveling... .... MUST HAVE EXPERIENCE WORKING ON DRYERS, BLENDERS, EXTRUSION MACHINES, AND CON…
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What machine learning engineers earn in Orlando
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 Orlando 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
01
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
02
Senior ML Engineer
03
Staff ML Engineer
04
ML Platform Lead
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