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Internship Graduate Machine Learning Jobs in Seattle, WA

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Internship Graduate Machine Learning information

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$29K

$48.5K

$100.1K

How much do internship graduate machine learning jobs pay per year?

As of Sep 14, 2026, the average yearly pay for internship graduate machine learning in Seattle, WA is $48,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,000.00 and $52,300.00 per year, depending on experience, location, and employer.

What is an internship graduate machine learning?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do internship graduate machine learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.

What are the key skills and qualifications needed to thrive as an internship graduate machine learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

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

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

Infographic showing various Internship Graduate Machine Learning job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $48,461 per year, or $23.3 per hour.

Director, Machine Learning Science - Marketing

Seattle, WA • On-site

$358K/yr

Other

Medical, Dental, Vision, PTO

Re-posted 9 days ago


Expedia Group rating

6.9

Company rating: 6.9 out of 10

Based on 25 frontline employees who took The Breakroom Quiz


Job description

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Here, you’ll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors–Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together–help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Director, Machine Learning Science - Marketing

Expedia Group is looking for a Director of Machine Learning Science to lead the applied science team behind our Marketing organization. This team builds the models and optimization systems that decide how we bid on online advertising platforms and allocate marketing capital across channels and brands. The systems you own will directly shape the efficiency of one of the largest performance marketing programs in travel.

You will lead scientists and managers delivering production ML at scale, own the roadmap, and partner closely with Marketing, Product, Engineering, Finance, and Analytics leadership. The role suits a leader who pairs technical depth with a broad business perspective and a record of measurable impact.

In this role, you will:

  • Own the strategy, roadmap, and OKRs for the machine learning systems powering Marketing

  • Design and deliver production‑grade ML models and optimization systems that improve bidding, capital allocation, and ROAS

  • Apply rigorous experimentation and measurement to validate business impact

  • Recruit, develop, and retain applied machine learning scientists and managers, and support their growth in a complex environment

  • Prioritize the team’s investment across platform migration, new capabilities, and model innovation

  • Build partnerships across Product, Engineering, Finance, Analytics, and Marketing leadership, and align priorities with multiple product teams

  • Navigate and influence the EG data platform and ML technology stack in line with company goals

  • Contribute to the broader data science and analytics community across EG

Minimum Qualifications:

  • Graduate degree in machine learning, computer science, statistics, or a related quantitative field; or equivalent related professional experience. PhD preferred

  • 10+ years of relevant professional experience and 5+ years of people management experience, including leading high–performing machine learning teams

  • Track record of delivering high–impact machine learning products from concept to production at scale

  • Depth in supervised and unsupervised learning, statistics, and experimentation, including A/B testing, power analysis, Bayesian methods, and causal inference

  • Command of the ML development lifecycle and MLOps: CI/CD, testing, observability, and reliable releases

Preferred Qualifications:

  • Domain experience in bidding, pricing, elasticity modeling, capital allocation, search, personalization, ranking, or recommendation

  • Exposure to deep learning, LLMs, retrieval‒based systems, and reinforcement learning

  • Proficient programming skills: Python preferred, plus Java or Scala, and SQL or equivalent query languages

  • Hands‒on experience with ML and data engineering technologies such as Spark, Databricks, Kubernetes, and GPU compute

  • Discipline in data and feature engineering (quality, lineage, documentation) and in model design with clear objectives, constraints, and risk guardrails

  • Proficient communication, collaboration, and mentoring, with the ability to tailor complex concepts to technical and executive audiences

The total cash range for this position in Seattle is $224,000.00 to $313,500.00. Employees in this role have the potential to increase their pay up to $358,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.

Benefits and perks

Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediggroup.com/life.

Accommodation requests

Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.

About Expedia Group

Expedia Group includes three flagship consumer brands–Expedia, Hotels.com, and Vrbo–along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.

Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.

Equal Opportunity

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s I-9 to confirm work authorization.

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