1

Junior Machine Learning Engineer Jobs in Seattle, WA

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role ... Provide situational guidance to junior engineers and contribute to team best practices * Build and ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that ...

Machine Learning Engineer

Seattle, WA · On-site

$93K - $125K/yr

Mentor junior engineers and help grow the team's technical depth. What You Need to Succeed Required Qualifications * Master's or Ph.D. in Computer Science, Machine Learning, or a related technical ...

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

They are seeking an Applied Machine Learning Engineer to develop products for their clients and the greenhouse industry, focusing on creating machine learning models and retraining systems.

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

The Sponsored Products and Brands - General Shopping Intelligence is looking for a talented Software Engineer with a strong machine learning engineering background to help us push the boundaries of ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Machine Learning Role 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 ...

Machine Learning Role 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 ...

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role ... Provide situational guidance to junior engineers and contribute to team best practices * Build and ...

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... Provide mentorship to and help onboard junior ML engineers * Collaborate cross-functionally with ...

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best ... Provide mentorship to and help onboard junior ML engineers * Collaborate cross-functionally with ...

next page

Showing results 1-20

Junior Machine Learning Engineer information

See Seattle, WA salary details

$38.1K

$81.7K

$124.6K

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

As of Jul 25, 2026, the average yearly pay for junior machine learning engineer in Seattle, WA is $81,710.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,200.00 and $91,000.00 per year, depending on experience, location, and employer.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a junior machine learning engineer do?

A junior machine learning engineer assists in developing, testing, and deploying machine learning models under supervision. They work with data preprocessing, feature engineering, and use tools like Python and libraries such as TensorFlow or scikit-learn to support AI projects. This role often requires foundational knowledge of algorithms, programming, and data analysis.

How much does a junior machine learning engineer make?

A junior machine learning engineer typically earns between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires advanced degrees, specialized certifications, and a strong track record of impactful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. These positions usually involve leadership, strategic planning, and significant experience, and they tend to be found in large tech companies or specialized AI firms.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

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 cities near Seattle, WA are hiring for Junior Machine Learning Engineer jobs? Cities near Seattle, WA with the most Junior Machine Learning Engineer job openings:
Infographic showing various Junior Machine Learning Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $81,710 per year, or $39.3 per hour.
Machine Learning Engineer

Other

Medical, Life, Retirement

Posted 7 days ago


Job description

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:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. 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.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite