1

Freelance Google Machine Learning Engineer Jobs in Seattle, WA

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

This Senior Machine Learning Engineer role is part of the Distribution & Supply team which sits within our Technology division. The Distribution & Supply team builds and optimizes the machine ...

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

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 ...

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

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 ...

As a Staff Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our AI strategy. The Core AI/ML team is responsible for building the foundational machine learning ...

We're looking for a Machine Learning Engineer to join Snap Inc! What you'll do: * Build and deploy machine learning models that power core products, serving millions of Snapchatters * Apply modern ML ...

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

As a Machine Learning Engineer at Axon , you'll help build AI solutions that are transforming public safety and advancing our mission to Protect Life . You'll work alongside talented ML engineers and ...

We're looking for a Machine Learning Engineer to join Snap Inc! What you'll do: * Build and deploy machine learning models that power core products, serving millions of Snapchatters * Apply modern ML ...

Showing results 41-60

Freelance Google Machine Learning Engineer information

See Seattle, WA salary details

$16

$54

$150

How much do freelance google machine learning engineer jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for freelance google machine learning engineer in Seattle, WA is $54.29, according to ZipRecruiter salary data. Most workers in this role earn between $27.64 and $70.29 per hour, depending on experience, location, and employer.

What does a freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

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

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

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

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

What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Seattle, WA?

For Freelance Google Machine Learning Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Freelance Google Machine Learning Engineer jobs in Seattle, WA look for?

The top searched job categories for Freelance Google Machine Learning Engineer jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Freelance Google Machine Learning Engineer jobs?

Cities near Seattle, WA with the most Freelance Google Machine Learning Engineer job openings:

Senior Machine Learning Engineer

Hive

Seattle, WA • On-site

$160K - $250K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 21 days ago


Job description

About Hive
Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.
Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!
Senior Machine Learning Engineer
In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.
Responsibilities
  • Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
  • Write and maintain scalable, performant and secure code that can be shared across platforms
  • Meaningfully contribute to the product and core backend systems by suggesting and executing improvements
  • Improve engineering standards, tooling, processes and security
  • Develop novel, accurate, and performant ML algorithms for use at scale
  • Conduct metric-driven research experiments to improve model performance
  • Provide mentorship to and help onboard junior ML engineers
  • Collaborate cross-functionally with other teams
  • Utilize OWASP top 10 techniques to secure code from vulnerabilities
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements
  • You have a Bachelor's Degree in computer science or a related field
  • You have a minimum of 5 years of building production scale ML models
  • You know the ins and outs modern machine learning frameworks, such as PyTorch or Tensorflow
  • You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
  • You have experience writing code and training across distributed systems
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • You can lead end to end development of new products
  • You are very knowledgeable in at least one focus area of machine learning, such as computer vision or NLP
  • You strongly believe in high code quality, automated testing, and other engineering best practices
  • You have attention to detail and a passion for correctness
  • You are comfortable with ambiguity and scoping solutions with your teammates
  • You have strong interpersonal and communication skills with a bias towards action

Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Hive and we hope to meet you soon!
The current expected base salary for this position ranges from $160,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
Employees are eligible to participate in a number of Company-sponsored benefits, including health, vision and dental insurance. Employees are also eligible to participate in a gym membership as part of our commitment to employee wellness. In addition, employees will be entitled to paid vacation in accordance with the Company's vacation policy.
Hired applicant may receive an equity grant in the form of an option to purchase stock in the future for a specified price.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.