$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…
Engineering & IT · Portland, OR
Machine Learning Engineer jobs in Portland, OR
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
115
Open roles today
$48–$122/hr
Typical pay range
$162k
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
8 shown of 115 · sorted by freshness
$35 - $42 per hour
Our MedTech Field Service Engineer experiences a unique opportunity employ their technical experience by collaborating with healthcare... ...into new opportunities while earning supplemental income and learning the medic…
$110.6k - $152.1k
rewarding career working with the industry’s best and most innovative engineers, then Jacobs is where you belong. We're looking for a... ...some experience with Revit software Forward thinking, eager to learn best practi…
Los Angeles, CA; Concord, CA; Salt Lake City, UT. As a Field Engineer , you will be working in one of our fab shops in the Portland... ...Engineers at Harder perform the following daily tasks: Learn, follow, and promote…
$9,731.21 per month
The City of Beaverton is seeking an Assistant City Traffic Engineer (ACTE) who will play a key role in shaping the future of traffic and transportation in the city. This position is in the Public Works Transportation Eng…
$40 - $46 per hour
sustainable future. Job Description Our Water Technology Business has an exciting opportunity available for a Field Service Engineer. The Field Service Engineer will be responsible for managing all aspects of water treat…
$110k - $130k
also support athletes through evaluation, consulting, scouting, and college placement. Learn more at [ **Role Overview** We're hiring a full-time ** Machine Learning / AI Engineer* * to help us build the intelligent syst…
The Hyatt Portland Airport is currently seeking a Maintenance Engineer to join our growing team! The Maintenance Engineer plays a critical role in assuring product quality through preventative maintenance of rooms/suites…
02
What machine learning engineers earn in Portland
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $48–$66 | $99k–$138k |
| Mid level | $66–$90 | $138k–$187k |
| Senior | $88–$122 | $182k–$253k |
Adjusted for the Portland 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 Portland?
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.