A pioneering tech firm is hiring a Junior Developer who will work remotely to develop a cloud-native monitoring stack using Python and Go. You will collaborate with a globally distributed team, write high-quality code, a…
Engineering & IT · Sacramento, CA
Machine Learning Engineer jobs in Sacramento, CA
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
87
Open roles today
$47–$119/hr
Typical pay range
$159k
Median, full-time
4
Fresh in this list
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01
Open machine learning engineer roles
12 shown of 87 · sorted by freshness
Electrical Engineer – Hydro Plants JOB-10047302 Anticipated Start Date August 24, 2026 Location Rancho Cordova, CA Type of Employment Contract Hire Employer Info Our client is an employee-owned engineering, procurement,…
Job Title: Rotating Engineer – Offshore Reliability Experience: Minimum 12 Years Qualification: Bachelor’s Degree in Mechanical Engineering Industry: Oil & Gas / Refinery (Offshore) Job Description: The Rotating Engineer…
$85k - $95k
spine and orthopedic surgeries along with disposable and reusable surgical patient care products. Job Summary The Field Service Engineer (FSE) is primarily responsible for technical support, repairing and servicing Mizuh…
Job Role:Data Engineer with AWS Glue Job Location: Sacramento, CA (Onsite) Job Duration: Long Term Job Summary: We are seeking a highly experienced Senior Snowflake Data Engineer with 10+ years of experience in designing…
Service Branch, the incumbent serves as the Chief of the Storage Engineering & Data Protection Unit. This unit is comprised of Information... ...the PM-0504 will not be reviewed during the SOQ scoring. To learn about the…
$54 - $61 per hour
walking, stooping, and handling materials ~ Use hands and arms in handling, installing positioning materials, and manipulating machines ~ Balance teamwork and individual responsibilities, exhibits openness to other views…
role, you will have the opportunity to participate in and lead engineering and design of the HVAC and plumbing systems in various types... ...Difference through infrastructure growth and development while learning and fo…
workforce, their communities, and the planet. The Manager of Engineering is a senior technician role responsible for managing... ...across our diverse family of brands and business units. Focused Learning and Development…
s IT classifications. Work-life balance, including hybrid or remote work options, when available. A culture that encourages learning, collaboration, and professional development. We're looking for someone who Enjoys solv…
cleaning and lubrication. Visually inspect tools, equipment, or machines. Carry equipment (e.g., tools, radio). Identify, locate, and... ...electrical schematics concerning plumbing and HVAC. Display advanced engineering…
$65.93k - $122.34k
Are you an Engineer looking for the next step in your career? Are you looking to work with cutting-edge technology? Join our Team... ...Waygate Technologies Equipment: Phoenix 2D & 3D CT X-ray Testing machine hardware an…
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What machine learning engineers earn in Sacramento
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $47–$65 | $97k–$135k |
| Mid level | $65–$88 | $135k–$184k |
| Senior | $86–$119 | $178k–$248k |
Adjusted for the Sacramento 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.
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.
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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.
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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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