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

Amazon

Sr. SDE, EC2 Nitro Networking

Seattle, WA · On-site

$139K - $183K/yr

... Machine Learning, Cloud Gaming, Health, Fintech, and Video Streaming. Your work will impact ... Mentor junior engineers with scoping, design, and developing scalable and maintainable code ...

Amazon

Sr. SDE, EC2 Nitro Networking

Seattle, WA · On-site

$139K - $183K/yr

... Machine Learning, Cloud Gaming, Health, Fintech, and Video Streaming. Your work will impact ... Mentor junior engineers with scoping, design, and developing scalable and maintainable code ...

Socure

Data Scientist ll - Digital Intelligence

Seattle, WA · On-site +1

$140K - $170K/yr

In this role, you will develop machine learning features, analytical methods, and production ... Support junior data scientists and analysts through code review, analytical feedback, and sharing ...

Walmart

Senior, Data Scientist

Seattle, WA

The team consists of collaborative data scientists and machine learning engineers skilled in ... Mentor junior team members on analytical methods, coding best practices, and business context ...

Weyerhauser Co

Principal Data Scientist

Seattle, WA · On-site

Mentor junior team members and contribute to data science standards, reusable patterns, and best practices. Qualifications * 10+ years of experience developing and deploying machine learning and AI ...

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All JobsMachine Learning JobsJunior Machine Learning JobsJunior Machine Learning Jobs in Seattle, WA

Junior Machine Learning information

See Seattle, WA salary details

$8

$30

$53

How much do junior machine learning jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for junior machine learning in Seattle, WA is $30.68, according to ZipRecruiter salary data. Most workers in this role earn between $18.61 and $37.74 per hour, depending on experience, location, and employer.

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

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

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

What are popular job titles related to Junior Machine Learning jobs in Seattle, WA?

For Junior Machine Learning jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning jobs in Seattle, WA look for?

The top searched job categories for Junior Machine Learning jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Junior Machine Learning jobs?

Cities near Seattle, WA with the most Junior Machine Learning job openings:

Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $63,808 per year, or $30.7 per hour.

SRE - Enterprise & Cloud Security - AI Driven Security - Manager

Pwc

Seattle, WA • On-site

$99K - $232K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago

Key responsibilities

  • Leading the design and development of AI-driven security solutions to enhance enterprise and cloud security

  • Managing and mentoring teams to deliver data and analytics engineering projects that transform raw data into actionable insights

  • Overseeing the integration and deployment of data infrastructure and pipelines to support AI and machine learning initiatives

PwC rating

8.3

Company rating: 8.3 out of 10

Based on 77 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants

Job description

Industry/Sector

Not Applicable

Specialism

Cybersecurity & Privacy

Management Level

Manager

Job Description & Summary

The Opportunity
As an SRE - Enterprise & Cloud Security - AI Driven Security - Manager, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Cyber, Data & Tech Risk practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale. As a Manager, you will lead teams and manage client accounts, focusing on strategic planning and mentoring junior staff. You are accountable for confirming project success and maintaining standards. Enhancing your leadership style, you motivate, develop, and inspire others to deliver quality. You are responsible for coaching, leveraging team members' unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.
Responsibilities
- Leading the design and development of AI-driven security solutions to enhance enterprise and cloud security
- Managing and mentoring teams to deliver data and analytics engineering projects that transform raw data into actionable insights
- Implementing machine learning models and AI systems to support scalable software and platform solutions
- Overseeing the integration and deployment of data infrastructure and pipelines to support AI and machine learning initiatives
- Utilizing programming languages such as Python and C++ to develop and optimize AI algorithms and models
- Conducting complex data analysis to identify patterns and insights that drive business growth and decision-making
- Collaborating with stakeholders to address data challenges and improve data quality and integration
- Promoting the adoption of innovative technologies and practices within the cybersecurity and privacy domain
- Confirming compliance with professional and technical standards in all deliverables
- Encouraging team development by fostering an environment of learning and skill enhancement
What You Must Have
- At least a Bachelor's degree
- At least 5 years of experience
What Sets You Apart
- Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating proficiency in AI implementation and machine learning libraries
- Excelling in strategic planning and mentoring junior staff
- Embracing technology and innovation to enhance client delivery
- Managing projects with a focus on planning, budgeting, and execution

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.

What PwC employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About pwc

Sourced by ZipRecruiter

We know that the future success of our firm is contingent on equitable experiences for our people. From recruitment to partnership, we’re working hard to give every person an equitable opportunity to grow and to thrive as part of our community of solvers. We understand that establishing and maintaining a fair, equitable and welcoming environment for all people requires building a culture of belonging: a shift from awareness to empathy — while demonstrating inclusive leadership that cultivates trust among our people and our clients. PwC is committed to advancing diversity, equity and inclusion (DEI) through an evidence-based strategy designed to achieve well-defined and meaningful aspirational goals. Our aim is to solve problems for the long term, as that is how we build trust and continue to build on our culture of belonging. At the core of this endeavor are stated goals and a series of linked programs enabling targeted interventions at key moments in our employees’ career trajectories.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

London, London, UK

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