$71.3k - $140.6k
Position Summary Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and help make... ...request handlingExperience with DockerExperience supporting machine learning workflowsExp…
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.
162
Open roles today
$48–$122/hr
Typical pay range
$162k
Median, full-time
10
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
12 shown of 162 · sorted by freshness
This in-office requirement may be adjusted at the discretion of the company.Columbia Sportswear Company is seeking a Senior Data Engineer in Portland, OR responsible for designing and implementing Kimball-style dimension…
$94.94k - $185.62k
: ANA United StatesWork Type: HybridDate Posted: 2026-08-28Arcadis is the world's leading company delivering sustainable design, engineering, and consultancy solutions for natural and built assets.We are more than 34,000…
$110k - $150k
About Us:BW Design Group is a fully integrated architecture, engineering, construction, system integration, and consulting firm committed to helping our clients realize their most critical goals from Strategy to Commerci…
difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.HDR Engineering is currently seeking an E…
difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.HDR Engineering is currently seeking a Me…
our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your... ...community, but around the world. HDR is looking for a Trenchless Engineer to join…
our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your... ...centers to modernizing transmission systems, our industry-recognized engineers an…
our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your... ...centers to modernizing transmission systems, our industry-recognized engineers an…
$94.7k - $110k
Senior Electrical EngineerWe’re looking for a Senior Electrical Engineer to join Curtiss-Wright Williams Controls. As a Senior... ...Employer Match and Profit Sharing I Health and Wellness Benefits I Learning and Develop…
$105k - $143k
Machine Learning Infrastructure Engineer – Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This…
• • • • • • • • NIKE, Inc. Artificial Intelligence, Data, & Machine Learning Engineering Undergraduate Internship NIKE is a technology company. From our flagship website and five-star mobile apps to developing products,…
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.