individuals opportunities for further advancement. As a Field Engineer in our Survey department, you will provide the Chief of the... ...Survey Field including: Trimble GPS, Robotics, and Topcon GPS machine control units…
Engineering & IT · San Antonio, TX
Machine Learning Engineer jobs in San Antonio, TX
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
100
Open roles today
$40–$103/hr
Typical pay range
$137k
Median, full-time
3
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01
Open machine learning engineer roles
12 shown of 100 · 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…
caring and attentive associates who are focused on providing efficient service and meaningful experiences. A General Maintenance Engineer B will be responsible primarily for general maintenance and repairs in guest rooms…
$45 per hour
specialized data scraping workflows for real-world use cases. Mindrift is looking for highly skilled Senior Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows for real…
$166k - $210k
We're hiring a Machine Learning Engineer to build and own the models behind our underwriting and decisioning systems at FloatMe. Our models determine who gets approved, how much, and under what terms — serving customers…
$53k - $106k
social media at @Carrier. About this role As a Field Engineer, you will be crucial to ALC’s business through the field commissioning... ...Dependent Care Spending Account Tuition Assistance To learn more about our benefi…
$37 per hour
Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system. In this role, as an AI Pilot – that’s ho…
We are engineers, high line workers, power plant managers, accountants, electricians, project coordinators, risk analysts, customer service operators, community representatives, safety and security specialists, communica…
Opportunity to participate in the company 401k plan with employer match Flexible work schedule About The Role: The Field Engineer (FSE) provides the front line interface of ARxIUM systems to the customer. The FSE, under…
$125k
Job Description Job Description Job Title: AI.ML Engineer (Google) Compensation: $125000 / Year Benefits: Medical insurance... ...for designing, building, and supporting scalable AI and machine learning solutions that im…
the installation and maintenance of mechanical systems at Data Centers and operations of specialized cooling systems. Acts as an Engineering resource for the complete H5 portfolio of mission critical facilities. Plans an…
Location: San Antonio, TX Position Summary The Systems Information Engineer serves as the senior M365 Systems Engineer responsible for enterprise administration, configuration, troubleshooting, and governance support for…
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What machine learning engineers earn in San Antonio
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $40–$56 | $84k–$116k |
| Mid level | $56–$76 | $116k–$158k |
| Senior | $74–$103 | $153k–$214k |
Adjusted for the San Antonio 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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