Become a Part of the NIKE, Inc. Team

NIKE, Inc. does more than outfit the world’s best athletes. It is a place to explore potential, obliterate boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream and create. Its culture thrives by embracing diversity and rewarding imagination. The brand seeks achievers, leaders and visionaries. At NIKE, Inc. it’s about each person bringing skills and passion to a challenging and constantly evolving game.

Open to remote work except in South Dakota, Vermont and West Virginia.

The annual base salary for this position ranges from $119,400.00 in our lowest geographic market to $267,500.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience.

Information about benefits can be found here.
 

WHO ARE WE LOOKING FOR

As a Lead Machine Learning Engineer within the Data & Artificial Intelligence (D&AI) organization, you will be developing sophisticated analytics systems that directly impact our business. You will get a chance to work on a cross-disciplinary team (DevOps/Data/Software Engineering) to enable data-driven decision-making across multiple projects. Being at this level you will be expected to own projects end-to-end, from conception to operationalization, demonstrating an understanding of the full software development lifecycle.  As a result, you will be expected to provide technical vision and guidance to your teammates; therefore, strong communication skills are critical in this role.

WHAT WILL YOU WORK ON

Working at the intersection of machine learning and software engineering, you'll create high-quality solutions that power Nike. Our AI/ML team is a collaborative and academic environment that promotes intellectual curiosity, diversity, and a drive to deliver knowledge and software back to the analytics and engineering communities. We're a global organization with teammates in various time zones, working to solve machine learning problems at scale.

As a member of our team, you'll design and implement scalable applications that leverage prediction models and optimization programs to deliver data-driven decisions with immense business impact. You'll contribute to core advanced analytics and machine learning platforms and tools, and thrive in an environment where talented colleagues share knowledge and skills.

We value and nurture our culture by seeking to always be collaborative, curious, fun, open, and diverse. If you're passionate about learning, contributing to the analytics and engineering communities, and working in a dynamic environment, we'd love to hear from you.

WHO WILL YOU WORK WITH

In this role, you’ll be working closely with the rest of our global team, along with commercial and consumer analytics, and enterprise architecture teams.

WHAT YOU BRING

Bachelor’s degree in computer science or a related field.5+ years of professional experience in machine learning or a related field, with a strong foundation in software development and technical leadership.Expert-level understanding of machine learning concepts, applications, and the lifecycle of an ML application in production, including the role of MLOps in the development lifecycle.Proven track record of delivering high-impact machine learning solutions, with a strong focus on scalability, reliability, and maintainability.Technical leadership skills, with experience in mentoring junior engineers and guiding technical decisions.Proficiency in writing clean, maintainable, and scalable code in Python, with a strong emphasis on software engineering best practices.Knowledge and hands-on experience with advanced machine learning techniques, such as deep learning, recommender systems & natural language processing.In-depth knowledge of computer science fundamentals, including data structures, algorithms, data modeling, and software architectures.Excellent communication skills, with the ability to effectively collaborate with team members, stakeholders, and communicate technical ideas through code, documentation, and presentations.Experience with technologies such as PyTorch, Spark, Docker, Jenkins, Airflow, and Databricks, with a strong understanding of their applications and limitations.Strong familiarity with MLOps and API development principles, with experience in designing and implementing scalable machine learning pipelines.Experience with cloud architecture and technologies, particularly Amazon Web Services.

Nice to Have:

Master’s degree in computer science or a related field.Experience with leading machine learning teams and guiding technical strategy.Experience with data engineering concepts, including data sets, ETL pipelines, SQL, and data warehousing.Understanding of agile development methodologies and test-driven development paradigms, with experience in implementing these practices in a team setting.Experience or interest in exploring the potential of Generative AI to accelerate development or deploying GenAI solutions in an enterprise setting.

We are committed to fostering a diverse and inclusive environment for all employees and job applicants. We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.

NIKE, Inc. is a growth company that looks for team members to grow with it. Nike offers a generous total rewards package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Nike employee shares one galvanizing mission: To bring inspiration and innovation to every athlete* in the world.

NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.