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Machine Learning Engineer Jobs in Seattle, WA (NOW HIRING)

PitchBook

Sr. Machine Learning Engineer

Seattle, WA · On-site

$118K - $163K/yr

PitchBook, a Morningstar company, is seeking a Senior Machine Learning Engineer to join their Product and Engineering team. The role involves delivering AI-powered features that extract insights from ...

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems , relating to training edge ML models on massive ...

Orchard Robotics

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems , relating to training edge ML models on massive ...

PitchBook Data

Sr. Machine Learning Engineer

Seattle, WA

$118K - $163K/yr

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of ...

Microsoft

Principal Machine Learning Engineer

Redmond, WA · On-site

$188K - $304K/yr

We are seeking a Principal Machine Learning Engineer to accelerate our training of generative models in close collaboration with Maching Learning (ML) researchers, software engineers, and domain ...

Chewy

Senior Machine Learning Engineer

Bellevue, WA · On-site +1

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Apple

AIML - Machine Learning Engineer, MIND

Seattle, WA

$139K - $258K/yr

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will have an opportunity to be part of an ML innovation organization within Apple that has its roots in the ...

Chewy

Staff Machine Learning Engineer

Bellevue, WA · On-site

$186K - $297K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Staff Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Chewy

Senior Machine Learning Engineer

Bellevue, WA · On-site

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

Opendoor

Machine Learning Engineer- Services

Seattle, WA · On-site

$169K - $233K/yr

As a software engineer on the team, you'll collaborate with data scientists, machine learning engineers, product managers, and partner engineering and operations teams to turn ideas into resilient ...

Scowtt

Staff Machine Learning Engineer

Seattle, WA · On-site

They are seeking a Staff Machine Learning Engineer to lead and evolve the ML systems that power their Marketing AI and AI Sales Agents, with a focus on end-to-end ownership of ML systems and ...

Chewy

Staff Machine Learning Engineer

Bellevue, WA

$186K - $297K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Staff Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

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Showing results 1-20

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

Machine Learning Engineer information

See Seattle, WA salary details

$35.8K

$146.5K

$220.2K

How much do machine learning engineer jobs pay per year?

As of Jul 2, 2026, the average yearly pay for machine learning engineer in Seattle, WA is $146,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,500.00 and $176,400.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Seattle, WA? The most popular types of Machine Learning Engineer jobs in Seattle, WA are:
What are popular job titles related to Machine Learning Engineer jobs in Seattle, WA? For Machine Learning Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Seattle, WA look for? The top searched job categories for Machine Learning Engineer jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Machine Learning Engineer jobs? Cities near Seattle, WA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Seattle, WA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $146,543 per year, or $70.5 per hour.
Sr. Machine Learning Engineer

Sr. Machine Learning Engineer

PitchBook

Seattle, WA • On-site

$118K - $163K/yr

Full-time

Posted 16 days ago

Job description

Job Summary:
PitchBook, a Morningstar company, is seeking a Senior Machine Learning Engineer to join their Product and Engineering team. The role involves delivering AI-powered features that extract insights from data, requiring expertise in machine learning, natural language processing, and collaboration with cross-functional teams.
Responsibilities:
• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities
• Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards
• Support a culture of technical excellence by mentoring peers, sharing knowledge, and participating in code and design reviews. Promote innovation and continuous improvement through collaborative engineering practices
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles
• Support the vision and values of the company through role modeling and encouraging desired behaviors
• Participate in various company initiatives and projects as requested
Qualifications:
Required:
• Bachelor’s or advanced degree in Computer Science, Mathematics, Data Science, or a related technical field
• 6+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact
• Deep proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future
Preferred:
• Advanced degree preferred
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred
Company:
PitchBook offers financial data and tools on companies, deals, investors, and markets to support sales and business development. It is a sub-organization of Morningstar. Founded in 2007, the company is headquartered in Seattle, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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