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Principal Data Science ML Engineer - Hybrid - Seattle

Job Description

As a Principal Machine Learning Engineers at Nordstrom you will have the opportunity to develop and implement advanced machine learning systems and infrastructure, focusing on Merchandising, Supply Chain, and Inventory helping Nordstrom optimize profit while improving the customer experience.    

The Principal ML Engineer will collaborate closely with data scientists, software engineers, and product teams to translate complex business problems into production-ready solutions. You will drive architectural decisions for high-performance computing and cloud-based ML platforms, ensuring scalability and security. Your responsibilities include creating models and optimizing model performance, ensuring system reliability, and implementing efficient data pipelines. Additionally, you will mentor junior engineers and stay updated on emerging technologies to guide strategic innovation. Your role is critical in delivering robust, scalable, and efficient machine learning solutions that support business growth and innovation.

Key Responsibilities:

  • Design, implement, and scale critical machine learning systems and infrastructure to support Nordstrom’s business, particularly in Merchandising, Supply Chain, and Inventory.

  • Collaborate with cross-functional teams to set and align on machine learning platform strategies to meet company objectives.

  • Stay up-to-date with the latest technology in machine learning and apply this knowledge to tackle complex problems in innovative ways.

  • Collaborate with leadership to up-level the ML tech stack and improve the performance of the organization.

  • Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products or services.

  • Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management.

  • Provide technical direction that influences the entire ML community.

  • Mentor junior engineers and promote best practices in ML operations (MLOps).

Qualifications:

  • 10+ years of related experience in applied Machine Learning. Strong programming skills in object-oriented languages (Scala / Python / Java/ C++ or equivalent), Data engineering skills, and a firm grasp of computer science fundamentals (data structures, algorithms, databases, etc.).

  • Bachelor’s, Master’s, or PhD in CS/ML/OR or related field.

  • Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.

  • Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms, and models).

  • Deep understanding of statistical and machine learning algorithms, and a finely honed intuition for fitting the best model class to a given situation.

  • Comfortable working with and across different cloud solutions - AWS/Sagemaker and GCP/Vertex AI experience a plus.

  • An ability to work both independently and collaboratively.

  • A broad perspective on problem-solving.

  • Strong communication skills and a desire to share your knowledge with team members and others.

Preferred Qualifications:

  • Experience partnering with cross-functional teams exercising sound judgment.

  • Track record of delivery in rapidly changing, highly collaborative, multi-stakeholder environments.

  • Experience working with a diverse group of engineers.

  • Experience contributing to AI publications.

 Core Competencies: 

  • Customer Focus: Commitment to delivering a seamless customer experience through technology solutions. 

  • Decision Quality: Ability to make sound decisions based on a mix of analysis, wisdom, experience, and judgment. 

  • Strategic Mindset: Capacity to take a long-term view and anticipate future trends and implications. 

  • Manages Complexity: Effectively navigates and simplifies complex situations and challenges. 

  • Communicates Effectively: Delivers clear, concise, and impactful messages to a variety of audiences. 

  • Drives Results: Demonstrates a strong drive to achieve meaningful outcomes. 

#LI-EB1

We’ve got you covered…

Our employees are our most important asset and that’s reflected in our benefits. Nordstrom is proud to offer a variety of benefits to support employees and their families, including:

  • Medical/Vision, Dental, Retirement and Paid Time Away
  • Life Insurance and Disability
  • Merchandise Discount and EAP Resources

A few more important points...

The job posting highlights the most critical responsibilities and requirements of the job. It’s not all-inclusive. There may be additional duties, responsibilities and qualifications for this job.

Nordstrom will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

Applicants with disabilities who require assistance or accommodation should contact the nearest Nordstrom location, which can be identified at www.nordstrom.com

© 2022 Nordstrom, Inc  

Current Nordstrom employees: To apply, log into Workday, click the Careers button and then click Find Jobs.

Pay Range Details

The pay range(s) below are provided in compliance with state specific laws. Pay ranges may be different in other locations.

Washington: $162,000 - $297,000 Annually

This position may be eligible for performance-based incentives/bonuses. Benefits include 401k, medical/vision/dental/life/disability insurance options, PTO accruals, Holidays, and more. Eligibility requirements may apply based on location, job level, classification, and length of employment. Learn more in the Nordstrom Benefits Overview by copying and pasting the following URL into your browser: https://careers.nordstrom.com/pdfs/Ben_Overview_17-19.pdf

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Average salary estimate

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$162000K
$297000K

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What You Should Know About Principal Data Science ML Engineer - Hybrid - Seattle, Nordstrom

As a Principal Data Science ML Engineer at Nordstrom in Seattle, you have the exciting opportunity to shape the future of our machine learning systems and infrastructure. Your expertise will be pivotal in enhancing our Merchandising, Supply Chain, and Inventory processes. This is more than just a coding job; it's about collaborating with talented data scientists, software engineers, and product teams to drive real-world solutions that optimize profit while enhancing the customer experience. You will take the lead on architectural decisions, ensuring our ML platforms are efficient, scalable, and secure. Your role involves creating and optimizing machine learning models, ensuring system reliability, and implementing robust data pipelines. A significant part of this position is to mentor junior engineers and keep an eye on emerging technologies that can spark strategic innovation. This is an opportunity to work in an environment where your contributions can make a direct impact on business outcomes, and where your creativity and problem-solving skills will shine. By joining Nordstrom, you are taking on a critical role that fosters business growth through cutting-edge ML solutions. We pride ourselves on supporting our employees—benefits include comprehensive medical and retirement plans, paid time off, and more. If you're ready to lead the way in a dynamic, hybrid working environment, Nordstrom wants you on our team!

Frequently Asked Questions (FAQs) for Principal Data Science ML Engineer - Hybrid - Seattle Role at Nordstrom
What are the responsibilities of a Principal Data Science ML Engineer at Nordstrom?

The Principal Data Science ML Engineer at Nordstrom focuses on designing, implementing, and scaling critical machine learning systems to enhance our Merchandising, Supply Chain, and Inventory operations. You will collaborate closely with cross-functional teams to align machine learning platform strategies and advocate for best practices related to operational excellence, availability, and scalability.

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What qualifications are required for the Principal Data Science ML Engineer position at Nordstrom?

To apply for the Principal Data Science ML Engineer role at Nordstrom, candidates should have 10+ years of experience in applied machine learning, strong programming skills in languages like Scala, Python, Java, or C++, and a solid background in data engineering. A Bachelor’s, Master’s, or PhD in computer science, machine learning, or a related field is also essential.

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What technologies do Principal Data Science ML Engineers at Nordstrom work with?

Principal Data Science ML Engineers at Nordstrom engage with various technologies, particularly cloud platforms such as AWS and GCP. Knowledge of machine learning frameworks, data pipelines, and familiarity with large, high-scale software applications are also crucial in this position.

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How does Nordstrom support its Principal Data Science ML Engineers?

Nordstrom provides robust support for its Principal Data Science ML Engineers through ongoing professional development, mentorship opportunities, and access to the latest tools and technologies. Employees benefit from a range of incentives including competitive salaries, healthcare benefits, and a focus on work-life balance.

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What is the work culture like for a Principal Data Science ML Engineer at Nordstrom?

The work culture for Principal Data Science ML Engineers at Nordstrom is collaborative, dynamic, and focused on innovation. Engineers are encouraged to share knowledge, mentor junior team members, and contribute to the continuous improvement of our machine learning practices within a supportive team environment.

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Common Interview Questions for Principal Data Science ML Engineer - Hybrid - Seattle
Can you describe your experience with applied machine learning?

When answering this question, focus on specific applications of machine learning you implemented, including any innovative models you built and their impact on business outcomes. Highlight your thought process and how you approached problem-solving.

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How do you ensure the reliability of machine learning systems?

Discuss strategies you utilize such as implementing automated testing, continuous monitoring, and regular model evaluations. Provide examples where these practices helped you maintain system performance over time.

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What programming languages are you most comfortable with?

List the languages you excel in, such as Scala, Python, or Java, and give examples of projects where you used these languages to build effective machine learning models or infrastructure.

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How do you approach collaboration with cross-functional teams?

Share your experiences working with teams from different disciplines, discussing how you communicate complex concepts effectively and ensure alignment on project goals. Cite specific instances where teamwork led to successful outcomes.

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Tell me about a challenging machine learning problem you've solved.

Choose a relevant problem and outline the steps you took to approach it, the solution you implemented, and the results achieved. This shows your analytical capabilities and tenacity in problem-solving.

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What is your experience with cloud solutions in machine learning?

Discuss the cloud platforms you're familiar with, such as AWS or GCP, and specific projects where you've leveraged these platforms for machine learning applications. Describe how you utilized cloud solutions to enhance service delivery or performance.

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How do you keep up with new technologies in machine learning?

Mention the resources you use, such as journals, online courses, or community forums, to stay updated. Share any recent developments you've integrated into your work or experiments with new technologies and their results.

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What do you think are the best practices in MLOps?

List several best practices, such as version control, automated testing, and model monitoring. Provide insights into how you've implemented these practices in your previous projects to enhance operational efficiency.

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How do you manage competing priorities in a fast-paced environment?

Share your techniques for effective time management, such as prioritization frameworks or tools you use to juggle multiple projects. Highlight any specific success stories where you effectively managed tight deadlines.

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What areas of machine learning are you particularly passionate about?

Discuss specific areas within machine learning that excite you, whether it's deep learning, natural language processing, or a trend you're following. This will reflect your enthusiasm and dedication to the field.

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At Nordstrom, we empower our employees to set their sights high and blaze their own trails. This is a place where your success and growth are truly a result of your own efforts and achievements. Our teams are made up of motivated people who work...

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DATE POSTED
April 8, 2025

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