Lead Machine Learning Engineer
Nike
About the role
Lead Machine Learning Engineer– NIKE USA Inc., Beaverton, OR. Develop robust advanced analytics and machine learning solutions that have a direct impact on the business; own projects end-to-end - from conception to operationalization, demonstrating an understanding of the full software development lifecycle; provide technical vision and guidance to the teammates; work with the Artificial Intelligence and Machine Learning (Al/ML) team at Nike with teammates in Portland, Boston, and Poland, and join a global organization working to solve machine learning problems at scale; design and implement scalable applications that leverage prediction models and optimization programs to deliver data driven decisions that result in immense business impact; contribute to core advanced analytics and machine learning platforms and tools to enable both prediction and optimization model development; develop and share new skills, mentor, and contribute knowledge and software back to the analytics and engineering communities both within Nike and at-large. Telecommuting is available from anywhere in the U.S., except from SD, VT, and WV.
Must have a Master’s degree in Information Systems, Computer Science and 2 years of experience in the job offered or in a engineering-related occupation.
Position requires:
- Python
- AWS (Amazon Web Services)
- Machine Learning / MLOps
- Docker • CI/CD (Jenkins)
- SQL and ETL Pipelines
- Data Structures, Data Modeling and Software Architecture
- Apache Spark • Kubernetes
- Databricks
- Terraform
- Database Technologies (Snowflake, PostgreSQL)
Apply at www.jobs.nike.com (Job# R-95900)
#LI-DNI
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.
Responsibilities
- Develop and operationalize advanced analytics and machine learning solutions.
- Own projects end-to-end and provide technical vision and guidance to teammates.
- Design scalable applications that use prediction models and optimization programs.
- Contribute to machine learning platforms, tools, and engineering communities.
- Mentor teammates and share technical knowledge.
Qualifications
- Master’s degree in Information Systems or Computer Science.
- At least 2 years of experience in the job offered or an engineering-related occupation.
- Experience with Python, AWS, machine learning and MLOps, Docker, CI/CD with Jenkins, SQL, and ETL pipelines.
- Knowledge of data structures, data modeling, software architecture, Apache Spark, Kubernetes, Databricks, Terraform, Snowflake, and PostgreSQL.
Benefits
- Reasonable accommodations for interview process
- Candidate accommodation support
Skills mentioned
About Nike
NIKE, Inc. is a purpose driven company fueled by a shared commitment to move the world forward through the power of sport. Guided by our mission to bring inspiration and innovation to every athlete* in the world, we champion sport’s values of inclusion and diversity while pushing boundaries to shape the future. At Nike, every teammate plays a role. We operate with an athlete’s mindset — working together, embracing our differences, and demanding more of ourselves and each other to drive collective success. Whether you’re building products, platforms, experiences or systems, your work contributes to something bigger: making athlete* dreams real. Explore opportunities at careers.nike.com and join our Talent Community at https://nikeats.avature.net/niketalentcommunity. *If you have a body, you are an athlete.
H-1B sponsorship history
Historical employer filing data was found for Nike. The employer record includes 2,365 historical certified applications. This is employer-level history, not a guarantee that this role currently offers sponsorship.