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Senior Machine Learning Engineer Jobs in Portland, OR

Sr. Machine Learning Engineer

Hillsboro, OR

$113K - $156K/yr

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Senior AI Engineer - SFL Scientific

Portland, OR · On-site

$110K - $152K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Showing results 1-20

Senior Machine Learning Engineer information

See Portland, OR salary details

$63.1K

$134.2K

$194.6K

How much do senior machine learning engineer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for senior machine learning engineer in Portland, OR is $134,214.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,800.00 and $152,200.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Portland, OR? The most popular types of Machine Learning Engineer jobs in Portland, OR are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Portland, OR? For Senior Machine Learning Engineer jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Portland, OR look for? The top searched job categories for Senior Machine Learning Engineer jobs in Portland, OR are:
What cities near Portland, OR are hiring for Senior Machine Learning Engineer jobs? Cities near Portland, OR with the most Senior Machine Learning Engineer job openings:
Infographic showing various Senior Machine Learning Engineer job openings in Portland, OR as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $128,317 per year, or $61.7 per hour.
Sr. Machine Learning Engineer

Sr. Machine Learning Engineer

Intel

Hillsboro, OR

$113K - $156K/yr

Full-time

Medical, Retirement, PTO

Posted 3 days ago


Intel rating

8.7

Company rating: 8.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

19th of 156 rated electronics manufacturers


Job description

Job Details:Job Description: 
Job Description
Our Mission

At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people-powerful in capability, yet honest about its limits and protective of the data and resources it touches.

To get there, we build agentic AI that combines the best of local and cloud intelligence - private, affordable, and sustainable by design. Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. Today, neither approach can deliver this alone. Together, they give people real capability without compromise-data stays private, spend stays predictable, and energy use stays in check.

We're building intelligence that scales without sacrificing trust, cost, or the planet-because the future of AI should belong to the people it serves

Role Summary

We are seeking a **Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal candidate designs and implements algorithms for agent harness and post-training pipelines, develops RL environments and reward models, and conducts training runs to improve model capabilities for agentic applications.

What you'll do

Work in a dynamic team to:

  • Build evaluation benchmarks and metrics

  • Build and iterate on agent harness, including context engineering, agent memory, tools, skills.

  • Build, maintain, and iterate on the post-training pipeline: Develop robust, reproducible training workflows from data ingestion and preprocessing through model checkpointing and deployment

  • Design RL environments and reward functions - Develop environments, reward signals, and verifiable reward frameworks for training models on reasoning-intensive tasks.

  • Debug and optimize training runs - Profile training jobs, resolve bottlenecks, improve GPU utilization, and address numerical instability at multi-GPU scale

What you'll learn / grow into

Curiosity is required. You will develop:

  • How post-training techniques actually move model performance

  • How to make small models punch above their weight as agent backends

  • How model choices interact with runtime constraints on edge hardware

IMPORTANT:

Please be informed that Intel is proactively trying

to find candidates for this position which is frequently available

at Intel.

Please note that the position may not be available

at this time. If you would be interested in this position should it

become available, we would encourage you to apply, and our

hiring team will be glad to contact you when/if relevant.

Qualifications:
Qualifications

Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Required Qualifications
  • BS in CS, EE, Math or related STEM field

  • 8+ years software development background

  • 4+ years of hands-on experience in machine learning engineering, data science or ML research.

  • Experiences designing and building evaluation frameworks and benchmarks that accurately measure model capability improvements and alignment quality

  • Proficient in Python

  • Proficient in LLM architectures, optimization and model training dynamics.

Preferred Qualifications
  • Masters or PhD degrees are preferred.

  • Hands-on experience implementing and scaling the full **post-training pipeline** for language models including supervised fine tuning and reinforcement learning.

  • Ability to own and drive a research agenda independently, generating hypotheses and prioritizing experiments without step-by-step supervision.

  • Ambiguity tolerance: Comfortable making progress in fast-moving environments where problem definitions evolve and priorities shift.

  • Debug-first mindset: Willingness and skill to dive deeply into large, complex ML codebases to isolate and fix subtle issues.

  • Research-engineering balance: Ability to produce production-quality implementations of novel research ideas, balancing rigor with speed.

  • Collaborative work style: Comfort with cross-functional collaboration.

  • Clear technical communication: Ability to explain research results, architectural decisions, and trade-offs to both technical and non-technical stakeholders.

  • Ability to learn new technologies fast and adapt to changes with open-mindedness.

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Benefits at Intel

Our total rewards package goes above and beyond just a paycheck. Whether you're looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals. Go to Intel Benefits | Intel Careers for details of benefits available to you. Intel reserves the right to modify, change or discontinue benefit plans at any time in its sole discretion.

#LDI

Job Type:Shift:Shift 1 (United States of America)Primary Location: US, California, Santa ClaraAdditional Locations:US, Arizona, Phoenix, US, California, Folsom, US, Oregon, HillsboroPosting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/ABenefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $195,200.00-361,200.00 USDThe range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

*

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

What Intel employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Intel

Sourced by ZipRecruiter

Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore's Law to bring smart, connected devices to every person on Earth

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1968