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Machine Learning Teaching Assistant Jobs in Seattle, WA

Project Planning: Assist in the planning and estimation of software development projects, ensuring the efficient allocation of resources and timely delivery of solutions. Technical Leadership: Lead a ...

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Machine Learning Teaching Assistant information

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$15

$20

$26

How much do machine learning teaching assistant jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for machine learning teaching assistant in Seattle, WA is $20.54, according to ZipRecruiter salary data. Most workers in this role earn between $18.61 and $21.88 per hour, depending on experience, location, and employer.

What is a machine learning teaching assistant?

Machine Learning Teaching Assistants are individuals, often graduate students or knowledgeable undergraduates, who assist professors or instructors in teaching machine learning courses. Their responsibilities typically include helping students understand course material, grading assignments, holding office hours, and sometimes leading discussion or lab sessions. They act as a bridge between students and instructors, offering support for both theoretical concepts and practical implementation. By providing guidance and feedback, they help ensure students gain a solid understanding of machine learning principles and applications.

How does a machine learning teaching assistant typically collaborate with professors and students during a course?

As a Machine Learning Teaching Assistant, you will work closely with professors to develop and grade assignments, clarify course concepts, and facilitate discussions in lectures or lab sessions. You often serve as a bridge between students and faculty, providing guidance on programming tasks, troubleshooting code, and offering feedback on projects. Regular office hours and online forums are common venues for this support, making strong communication skills and a solid grasp of machine learning fundamentals essential. This collaborative environment helps you deepen your expertise while supporting student learning.

What are the key skills and qualifications needed to thrive as a machine learning teaching assistant, and why are they important?

To thrive as a Machine Learning Teaching Assistant, you need a solid foundation in machine learning concepts, programming (often Python), and relevant coursework or a degree in computer science or a related field. Familiarity with tools like Jupyter Notebooks, TensorFlow, PyTorch, and version control systems is commonly expected. Strong communication, patience, and organizational skills help you effectively support students and collaborate with instructors. These abilities ensure you can explain complex topics clearly, assist students efficiently, and contribute to a positive learning environment.

What are the most commonly searched types of Machine Learning Teaching jobs in Seattle, WA?

The most popular types of Machine Learning Teaching jobs in Seattle, WA are:

Infographic showing various Machine Learning Teaching Assistant job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $42,733 per year, or $20.5 per hour.

Senior Machine Learning / Data Engineer - Evaluation

Seattle, WA • On-site

$120K - $164K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 days ago


Job description

About VTI Aerospace

VTI Aerospace builds AI-powered perception and pilot assist technologies to unlock the future of aviation. With offices in Bozeman, MT and Seattle, WA, we are a team of engineers and technologists from Boeing, Airbus, Aurora, and beyond. We are passionate about pushing the boundaries of autonomy and aviation safety. Our company is dedicated to advancing the field of aviation with cutting-edge solutions

The Role

As a Senior Software Engineer – Evaluation, you will design and implement systems that measure and monitor the performance of our computer vision, automatic speech recognition (ASR), and small language model (SLM) systems. You will develop evaluation methodologies, benchmarking pipelines, and monitoring tools that ensure our AI systems perform reliably in real-world environments. You will help establish the evaluation standards and performance benchmarks that guide the development of all AI systems at the company.

You will work closely with machine learning and data engineering teams to evaluate model performance, identify failure modes, and guide improvements to data collection and model training, helping bring AI-powered aviation tools to market.

This role is ideal for someone who enjoys designing robust evaluation systems and uncovering insights from model performance data, and wants to have a direct impact on the quality and reliability of our AI systems.

What You'll Do
  • Define and implement evaluation methodologies for computer vision, ASR, and language systems
  • Identify and track key performance indicators (KPIs) that measure system and model effectiveness
  • Perform dataset coverage analysis to understand strengths, gaps, and biases in training and evaluation data
  • Identify model deficiencies and collaborate with ML engineers to improve training data and model performance
  • Build scalable model evaluation pipelines in Python for automated benchmarking and regression testing
  • Design and maintain systems for monitoring model performance and drift in production environments
  • Architect data models and storage systems for evaluation results using relational and time-series databases
  • Build dashboards and reporting tools to visualize model performance and evaluation metrics
  • Collaborate with ML and data engineering teams to improve evaluation workflows and data pipelines
  • Contribute to ground-truth data pipelines and processes that support reliable evaluation
What We're Looking For
  • 5+ years of experience developing production software systems in Python
  • Strong experience designing and implementing data processing or analysis pipelines
  • Experience building systems for machine learning evaluation, experimentation, or benchmarking
  • Experience working with large datasets and building scalable data workflows
  • Familiarity with statistical methods, experimental design, and model performance analysis
  • Experience building automated pipelines using tools such as Airflow or similar orchestration frameworks
  • Experience working with evaluation or experiment tracking tools such as MLflow or similar systemsExperience designing data models and working with relational databases and time-series data
  • Strong collaboration skills and ability to work closely with machine learning and data engineering teams
Bonus Points
  • Experience working with computer vision, ASR, or language models in production environments
  • Experience using PyTorch or other deep learning frameworks
  • Experience evaluating multimodal or large-scale AI systems
  • Experience building monitoring systems for ML models in production
  • Experience designing dataset analysis or data quality tooling
  • Experience building dashboards or monitoring tools using Grafana or similar platforms
Why You'll Love Working Here
  • Opportunity to work on meaningful problems in aviation and deliver products to industry at a rapid pace
  • Small team with significant impact on company direction
  • Collaborative and innovative environment
  • Competitive compensation and benefits
  • Opportunities for growth and leadership
Location

Work arrangement: On-site

Primary location: Seattle or Bozeman

Compensation & Benefits

Salary range: DOE

Benefits may include:
  • Health, dental, and vision insurance
  • Retirement plan or 401(k)
  • Paid time off and holidays
  • Professional development opportunities
Equal Opportunity Statement

VTI is proud to be an equal opportunity employer. We value diverse perspectives and encourage candidates from all backgrounds to apply

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