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Contract Machine Learning Engineer Jobs in 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 ...

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 ...

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 ...

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 ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

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Contract Machine Learning Engineer information

See Portland, OR salary details

$33.4K

$136.6K

$205.2K

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

As of Jun 13, 2026, the average yearly pay for contract 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 is a Contract Machine Learning Engineer job?

A Contract Machine Learning Engineer is a professional who builds and deploys machine learning models on a temporary or project-based basis. They typically work with companies seeking specialized expertise in data science, model development, or AI integration without committing to a full-time hire. Responsibilities may include data preprocessing, model training, algorithm optimization, and deployment. Contract roles allow for flexibility and are often remote, making them ideal for businesses with short-term AI needs or startups looking to scale their machine learning capabilities quickly.

What are the typical day-to-day responsibilities of a Contract Machine Learning Engineer?

As a Contract Machine Learning Engineer, your daily tasks usually involve gathering and preprocessing data, building and fine-tuning machine learning models, and collaborating with software engineers and product managers to integrate your models into production systems. You may also meet with clients or internal teams to gather requirements and provide technical insights, as well as document and present your findings to stakeholders. Work is typically project-based and may require a high degree of independence, flexibility, and adaptability. This dynamic environment often exposes you to a variety of industries and technical challenges, making each project unique and providing valuable experience for professional growth.

What are the key skills and qualifications needed to thrive in the Contract Machine Learning Engineer position, and why are they important?

To thrive as a Contract Machine Learning Engineer, you need a strong background in machine learning algorithms, data preprocessing, statistical analysis, and proficiency in programming languages such as Python or R, often supported by a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms (AWS, Google Cloud, Azure) or certifications in these areas are common requirements. Excellent problem-solving, communication, and time management skills are vital, especially when working with cross-functional teams and managing multiple projects remotely. These skills ensure effective delivery of high-quality, scalable machine learning solutions within tight project timelines and diverse client environments.

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 Contract Machine Learning Engineer jobs in Portland, OR? For Contract Machine Learning Engineer jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Contract Machine Learning Engineer jobs in Portland, OR look for? The top searched job categories for Contract Machine Learning Engineer jobs in Portland, OR are:

Machine Learning Engineer

Chabez Tech

Portland, OR

Contractor

Posted 19 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

All your information will be kept confidential according to EEO guidelines.