1

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

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 ...

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 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 ...

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 ...

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 ...

Machine Learning Engineer

Seattle, WA · On-site

$165K - $209K/yr

... data engineering, machine learning engineering, or related roles. * Data Pipelineexperience, designingand scaling data pipelines for unstructured or semi-structured data, including ingestion ...

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 ...

Machine Learning Engineer

Seattle, WA · On-site

$165K - $209K/yr

... data engineering, machine learning engineering, or related roles. * Data Pipelineexperience, designingand scaling data pipelines for unstructured or semi-structured data, including ingestion ...

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 ...

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 ...

next page

Showing results 1-20

Machine Learning Engineer information

See Bothell, WA salary details

$35.2K

$143.9K

$216.3K

How much do machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer in Bothell, WA is $143,949.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $173,300.00 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.

What are the most commonly searched types of Machine Learning Engineer jobs in Bothell, WA? The most popular types of Machine Learning Engineer jobs in Bothell, WA are:
What are popular job titles related to Machine Learning Engineer jobs in Bothell, WA? For Machine Learning Engineer jobs in Bothell, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Bothell, WA look for? The top searched job categories for Machine Learning Engineer jobs in Bothell, WA are:
What cities near Bothell, WA are hiring for Machine Learning Engineer jobs? Cities near Bothell, WA with the most Machine Learning Engineer job openings:
Machine Learning Engineer (Seattle)

Machine Learning Engineer (Seattle)

PitchBook

Seattle, WA • On-site

Full-time

Medical, Life, Retirement

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Machine Learning Engineer role at PitchBook

Get AI-powered advice on this job and more exclusive features.

At PitchBook, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We’re deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company. Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there’s going to be some ambiguity along the way, but we excel when we challenge ourselves. We’re willing to take risks, fail fast, and do it all over again in the pursuit of excellence. If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you.

About the Role

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation. We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As a 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 structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands‑on approach to designing, building, and optimizing ML solutions that power user‑facing features on the PitchBook Platform.

You will be deeply involved in the end‑to‑end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources and applying ML to enrich our datasets with predictive and generative intelligence.

Primary Job 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.
  • Contribute to a culture of technical excellence by sharing knowledge, pairing with teammates, and actively participating in code and design reviews. Provide situational guidance to junior engineers and contribute to team best 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.
Skills and Qualifications
  • Bachelor’s degree in Computer Science, Mathematics, Data Science, or related technical field; advanced degrees are preferred.
  • 2+ 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.
  • Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus.
  • 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.
  • 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.
  • Must be authorized to work in the United States without the need for visa sponsorship now or in the future.
Benefits + Compensation at PitchBook Physical Health
  • Comprehensive health benefits
  • Additional medical wellness incentives
  • STD, LTD, AD&D, and life insurance
Emotional Health
  • Paid sabbatical program after four years
  • Paid family and paternity leave
  • Annual educational stipend
  • Ability to apply for tuition reimbursement
  • CFA exam stipend
  • Robust training programs on industry and soft skills
  • Employee assistance program
  • Generous allotment of vacation days, sick days, and volunteer days
Social Health
  • Matching gifts program
  • Employee resource groups
  • Subsidized emergency childcare
  • Dependent Care FSA
  • Company‑wide events
  • Employee referral bonus program
  • Quarterly team building events
Financial Health
  • 401k match
  • Shared ownership employee stock program
  • Monthly transportation stipend

Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation
  • Annual base salary: $125,000-$180,000
  • Target annual bonus percentage: 10%
Working Conditions

Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week. The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on‑going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

Life At PB

We are consistently recognized as a Best Place to Work and our culture is at the heart of our success. It’s our fundamental belief that people do and create great things and that people are the cornerstone of prosperity. We believe that proactively seeking out different points of view, listening to