$180k - $250k
Role: Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250,000 / yr + stock options, 401k matching, and other benefits Role Overview: Seasats' vehicles operate in highly remo…
Engineering & IT · San Diego, CA
Machine Learning Engineer jobs in San Diego, CA
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
159
Open roles today
$51–$130/hr
Typical pay range
$174k
Median, full-time
6
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Open machine learning engineer roles
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intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest... ...edge AI research and production systems at the intersection of machine learning, com…
$168.8k - $253.25k
computing technologies for building and deploying automated machine learning and analytics pipelines, such as Azure, AWS, GCP, etc.Explore... ..., Mathematics, Computer Science, Electrical and Computer Engineering, or a…
$105k - $168k
Strategic Sourcing EngineerJob DescriptionThe Senior Procurement Engineer develops and industrializes the supply base, drives Product... .... Do the work of your life to help improve the lives of others. Learn more about…
$160k - $250k
Instagram, and YouTube. Job Description:Join Shield AI’s Hivemind SDK State Estimation and Vision team to build the tools that help engineers develop, understand, and validate autonomous navigation systems. You will turn…
automotive applications to energy management systems and healthcare devices. Why Consider This Job Opportunity The Senior Machine Learning Engineer works on meaningful, real-world challenges where machine learning direct…
experience with ML frameworks (PyTorch, TensorFlow) MLOps and model lifecycle management Azure cloud experience Strong software engineering and coding best practices Platform operations and support experience Nice to Hav…
We are seeking a Senior CJA Implementation Engineer to lead the design, implementation, configuration, and reporting of Adobe Customer Journey Analytics (CJA) alongside a website implementation. The role will support the…
Description Responsibilities Own small to medium components of machine learning systems from technical designthrough implementation and... ...to plan Build and maintain data pipelines and feature engineering workflows to…
$140k - $195k
Machine Learning Engineer III The Marlin Alliance, Inc. | San Diego, CA | Hybrid | Clearance Required About The Marlin Alliance Incorporated in 2002, The Marlin Alliance is a digital transformation company dedicated to e…
$165k - $195k
The Marlin Alliance, Inc. is seekinga talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced machine learning mode…
$110k - $180k
The Marlin Alliance, Inc. is seeking a Senior Machine Learning Engineer to design, develop, and implement advanced machine learning models and algorithms in support of naval applications. This role requires deep technica…
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What machine learning engineers earn in San Diego
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $51–$71 | $106k–$148k |
| Mid level | $71–$97 | $148k–$201k |
| Senior | $94–$130 | $195k–$271k |
Adjusted for the San Diego 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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