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Machine Learning Engineer Jobs in Portland, OR (NOW HIRING)

Chabez Tech

Machine Learning Engineer

Portland, OR

Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 Months Contract Experience Level: 5+ years of experience Required Qualifications • Bachelor's or ...

Chabez Tech

Machine Learning Engineer

Portland, OR · On-site

Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 Months Contract Experience Level: 5+ years of experience Required Qualifications • Bachelor's or ...

Chabez Tech

Machine Learning Engineer

Portland, OR

Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 Months Contract Experience Level: 5+ years of experience Required Qualifications Bachelor's or ...

Varsity Tutors

Machine Learning Tutor

Portland, OR · Remote

$40/hr

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

Deloitte

AI Solutions Architect

Portland, OR · On-site

$66.75 - $88/hr

... machine learning, and generative artificial intelligence use cases, including secure and high-availability deployment models • Collaborating with architects, engineers, data scientists, and ...

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Machine Learning Engineer information

See Portland, OR salary details

$33.4K

$136.6K

$205.2K

How much do machine learning engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for machine learning engineer in Portland, OR is $136,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,600.00 and $164,400.00 per year, depending on experience, location, and employer.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
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 Machine Learning Engineer jobs in Portland, OR? For Machine Learning Engineer jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Portland, OR look for? The top searched job categories for Machine Learning Engineer jobs in Portland, OR are:
What cities near Portland, OR are hiring for Machine Learning Engineer jobs? Cities near Portland, OR with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you

Machine Learning Engineer

Chabez Tech

Portland, OR

Contractor

Posted 5 days ago

Job description

Job Description

Job Title: Machine Learning Engineer
Location: Portland, OR - Onsite (Local only / F2F interview)
Duration: 24 Months Contract

Experience Level: 5+ years of experience

Required Qualifications
•    Bachelor’s or master’s degree in computer science, Machine Learning, Electrical Engineering, or related field 
•    5+ years of experience in machine learning, data science, or AI engineering 
•    Strong programming skills in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) 
•    Experience with time-series data analysis and anomaly detection 
•    Hands-on experience with causal inference methods (e.g., Bayesian networks, structural causal models) 
•    Experience building or working with knowledge graphs (Neo4j, RDF, graph databases) 
•    Understanding of explainable AI techniques (SHAP, LIME, counterfactual analysis) 
•    Experience deploying ML models in production systems 
•    Strong problem-solving skills and ability to work with complex, real-world datasets

Preferred Qualifications
•    Experience with fault tree analysis (FTA), reliability engineering, or failure analysis 
•    Background in industrial systems, semiconductors, manufacturing, or IoT environments 
•    Experience with graph-based ML / Graph Neural Networks (GNNs) 
•    Familiarity with RCA methodologies (FMEA, 5 Whys, fishbone diagrams) 
•    Experience with vector databases, RAG systems, or LLM-based reasoning 
•    Knowledge of MLOps practices (CI/CD, monitoring, model governance) 
•    Experience working in air-gapped or high-security environments 
 

Additional Information

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