ZipRecruiter

Log In

1

Temporary Machine Learning Trainer Jobs in Everett, WA

Nvidia

Senior Machine Learning Engineer

Seattle, WA · On-site

$118K - $163K/yr

As a Senior Machine Learning Engineer at NVIDIA, you will build the machine learning brain that ... Analyzing complex datasets to determine the best approach for model training and optimization.

Expedia

Senior Machine Learning Scientist

Seattle, WA · Remote

$104K - $142K/yr

Senior Machine Learning Scientist The Senior Machine Learning Scientist is responsible for building ... Read and apply relevant academic and industry research to improve model architectures, training ...

Bespoke Labs

Machine Learning Engineer

Seattle, WA · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Bellevue, WA · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Capital Group

Machine Learning Engineer II

Seattle, WA · On-site

$111K - $151K/yr

... model training and deployment, and experience using machine learning to solve real business ... Temporary positions in the United States are excluded from the above mentioned compensation and ...

Capgroup

Machine Learning Engineer II

Seattle, WA · On-site

$111K - $151K/yr

... model training and deployment, and experience using machine learning to solve real business ... Temporary positions in the United States are excluded from the above mentioned compensation and ...

Apple

AIML - Machine Learning Research

Seattle, WA

$142K - $263K/yr

This involves developing sophisticated machine learning and large language models (LLMs) to ... Designing and developing advanced Reinforcement Learning technologies in the post-training of ...

Hive

Senior Machine Learning Engineer

Seattle, WA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... You have experience writing code and training across distributed systems * You have an ability to ...

Hive

Senior Machine Learning Engineer

Seattle, WA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... You have experience writing code and training across distributed systems * You have an ability to ...

Hive

Staff Machine Learning Engineer

Seattle, WA · On-site

$200K - $300K/yr

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in ... You have experience writing code and training across distributed systems * You have the ability to ...

Hive

Staff Machine Learning Engineer

Seattle, WA · On-site

$200K - $300K/yr

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in ... You have experience writing code and training across distributed systems * You have the ability to ...

Expedia

Senior Machine Learning Engineer

Seattle, WA

$139K - $183K/yr

This Senior Machine Learning Engineer role is part of the Distribution & Supply team which sits ... training, evaluation, and deployment. * Proven experience working with serviceoriented or ...

New

previous pagenext page

Showing results 21-40

All JobsMachine Learning Trainer JobsTemporary Machine Learning Trainer JobsTemporary Machine Learning Trainer Jobs in Everett, WA

Temporary Machine Learning Trainer information

See Everett, WA salary details

$30.9K

$96.5K

$124.3K

How much do temporary machine learning trainer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for temporary machine learning trainer in Everett, WA is $96,465.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,300.00 and $122,600.00 per year, depending on experience, location, and employer.

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

To thrive as a Temporary Machine Learning Trainer, you need a solid background in machine learning concepts, data analysis, and model evaluation, usually supported by a relevant degree or experience in computer science or a related field. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or scikit-learn), and educational tools is typically required. Strong communication, adaptability, and instructional skills help trainers effectively convey complex topics and respond to diverse learner needs. These skills ensure trainees gain practical knowledge and confidence, contributing to successful training outcomes and organizational goals.

What are some common challenges faced by temporary machine learning trainers, and how can they be managed effectively?

Temporary Machine Learning Trainers often face the challenge of quickly adapting to new team environments and rapidly understanding existing workflows. Additionally, they may need to balance delivering training sessions with handling updates to curriculum or technology. Effective communication with permanent staff and staying up-to-date with the latest machine learning tools can help manage these challenges. Being proactive in seeking feedback and clarifying expectations early on can also contribute to a smoother transition and more impactful training sessions.

What is the difference between Temporary Machine Learning Trainer vs Data Scientist?

AspectTemporary Machine Learning TrainerData Scientist
CredentialsRelevant certifications (e.g., AWS, Google Cloud), technical trainingAdvanced degrees (Master's or PhD) in data science, statistics, or related fields
Work EnvironmentTraining sessions, workshops, corporate training settingsData analysis, modeling, research environments, often in offices or labs
Employer & Industry UsageTech companies, educational institutions, consulting firmsTech, finance, healthcare, research organizations

While both roles involve working with data and machine learning, a Temporary Machine Learning Trainer primarily focuses on educating and training teams or clients on machine learning tools and concepts. In contrast, a Data Scientist develops models, analyzes data, and derives insights for decision-making. The roles differ mainly in their focus—training versus data analysis—though they share foundational technical skills.

What is a temporary machine learning trainer?

Temporary Machine Learning Trainers are professionals hired on a short-term or contract basis to develop, implement, and refine machine learning models or to train teams in machine learning techniques. Their responsibilities often include preparing training data, selecting appropriate algorithms, and ensuring models are accurate and efficient. They may also provide guidance to organizations on best practices and help upskill employees in machine learning concepts. These roles are typically project-based and may last from a few weeks to several months, depending on organizational needs.

What cities near Everett, WA are hiring for Temporary Machine Learning Trainer jobs?

Cities near Everett, WA with the most Temporary Machine Learning Trainer job openings:

Temporary Machine Learning Trainer jobs near you
Infographic showing various Temporary Machine Learning Trainer job openings in Everett, WA as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $96,465 per year, or $46.4 per hour.

Senior Machine Learning Engineer

Nvidia

Seattle, WA • On-site

$118K - $163K/yr

Full-time

Posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies

Job description

As a Senior Machine Learning Engineer at NVIDIA, you will build the machine learning brain that keeps NVIDIA's global DGX Cloud healthy, efficient and ready for the next waves of AI breakthroughs. DGX Cloud fuses NVIDIA GPUs, NVLink networking and the full AI software stack into elastic infrastructure powering large language models, drug discovery, autonomous driving and climate science. Your models will turn billions of telemetry signals into predictive insight. This frees customers to innovate while our platform runs smarter.

What you'll be doing:

  • Ground breaking and developing innovative machine learning algorithms and models that propel our AI products.

  • Build production models for anomaly detection, predictive maintenance and usage optimization.

  • Develop tools surfacing real time telemetry, efficiency metrics and long term trends.

  • Develop forecasting and simulation models for global scale planning.

  • Analyzing complex datasets to determine the best approach for model training and optimization.

  • Translate findings into clear engineering actions with infrastructure, operations and product teams.

  • Participating in cross-functional projects to integrate machine learning capabilities into various NVIDIA products.

What we need to see:

  • Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience).

  • 8+ years experience applying Machine Learning to operational systems.

  • Proven track record of building and deploying Machine Learning models in production environments.

  • Experience with time series analysis and optimization algorithms.

  • Familiarity with distributed systems and cloud platforms such as AWS and Kubernetes.

  • Strong software engineering skills and proficiency in Python.

  • Effective verbal/written communication, and technical presentation skills.

  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.

  • A track record of delivering high-impact projects to compete in a fast-paced environment.

Ways to stand out from the crowd:

  • Experience solving capacity planning problems.

  • Deep understanding of GPU performance metrics.

  • Familiarity with prometheus and PromQL.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 7, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

View All Nvidia Jobs

Apply