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Machine Learning Engineer Software Engineer Jobs in Seattle, WA

Hive

Staff Machine Learning Engineer

Seattle, WA · On-site

$200K - $300K/yr

Hive also offers turnkey software applications powered by proprietary AI models and datasets ... Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in ...

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

Farmers use our software every day to make critical decisions and run more efficient, profitable ... We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ...

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

Farmers use our software every day to make critical decisions and run more efficient, profitable ... We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ...

Axon

Sr Machine Learning Engineer I

Seattle, WA · Hybrid

$118K - $163K/yr

Partner closely with software engineers to transition validated algorithms into scalable ... machine learning research. What You Bring * Bachelor's or Master's degree in Computer Science ...

Remitly

Staff Machine Learning Engineer

Seattle, WA · On-site

$208K - $260K/yr

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 ...

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All JobsMachine Learning Engineer Software Engineer JobsMachine Learning Engineer Software Engineer Jobs in Seattle, WA

Machine Learning Engineer Software Engineer information

See Seattle, WA salary details

$72.3K

$167.9K

$233.9K

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

As of Jul 9, 2026, the average yearly pay for machine learning engineer software engineer in Seattle, WA is $167,886.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,600.00 and $196,900.00 per year, depending on experience, location, and employer.

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

AspectMachine Learning EngineerSoftware Engineer
Required CredentialsBachelor's/Master's in CS, specialized ML coursesBachelor's in CS or related field
Work EnvironmentDevelops ML models, algorithms, data pipelinesBuilds software applications, systems, APIs
Industry UsageAI/ML projects, data-driven solutionsWeb, mobile, enterprise software

Machine Learning Engineers focus on designing and deploying ML models, requiring expertise in algorithms and data handling. Software Engineers develop broader software applications, emphasizing coding and system architecture. While both roles require programming skills, ML Engineers specialize in AI/ML tasks, whereas Software Engineers work across various software domains.

How do Machine Learning Engineer Software Engineers typically collaborate with data scientists and software development teams?

Machine Learning Engineer Software Engineers often serve as a bridge between data scientists and software development teams. They work closely with data scientists to understand and implement machine learning models, ensuring that the models are production-ready and scalable. Additionally, they collaborate with software engineers to integrate these models into existing applications, monitor their performance, and address any engineering challenges. This cross-functional collaboration is essential for delivering robust, end-to-end AI solutions that add real value to the business.
What are popular job titles related to Machine Learning Engineer Software Engineer jobs in Seattle, WA? For Machine Learning Engineer Software Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Software Engineer jobs in Seattle, WA look for? The top searched job categories for Machine Learning Engineer Software Engineer jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Machine Learning Engineer Software Engineer jobs? Cities near Seattle, WA with the most Machine Learning Engineer Software Engineer job openings:
Machine Learning Engineer Software Engineer jobs near you
Infographic showing various Machine Learning Engineer Software Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 89% Full Time, 7% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $167,886 per year, or $80.7 per hour.
Staff Machine Learning Engineer

Staff Machine Learning Engineer

Hive

Seattle, WA • On-site

$200K - $300K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 11 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!

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 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 code that can be shared across platforms
  • Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
  • Improve engineering standards, tooling, and processes
  • 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 ML engineers
  • Lead cross-functional collaboration with other teams
  • Contribute to defining strategic direction, planning the roadmap
  • 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
Minimum Requirements
  • You have a Bachelor's Degree in computer science or a related field
  • You have 8+ years of experience building web applications
  • You have successfully implemented highly-available distributed systems/microservices
  • You have delivered scalable backend APIs
  • You have strong interpersonal and communication skills with a bias towards action
  • You have experience writing code and training across distributed systems
  • You have the ability to understand and make well-reasoned tradeoffs in designing features
  • You are an expert in 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 are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
  • You can lead end to end development of new products
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 $200,000 - $300,000. 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.
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