Principal Machine Learning Engineer, ITC

Working within Nike's Corporate Functions Artificial Intelligence team, this Principal AI/ML Engineer will help deliver AI capabilities for Nike's corporate functions. The role involves joining a globally distributed team solving machine learning problems at scale, designing and implementing scalable applications that leverage prediction models and optimization programs. The engineer will own projects end-to-end from conception to operationalization and provide technical vision and guidance to teammates.

• Design and implement scalable applications that leverage prediction models and optimization programs to deliver data-driven decisions with business impact.
• Contribute to core advanced analytics, machine learning, and generative AI platforms and tools to enable prediction and optimization model development.
• Work with business stakeholders, product owners, and engineering peers to ensure successful delivery of reporting solutions.
• Coordinate dependencies with other technology teams that lead upstream and downstream solutions.
• Influence and develop robust machine learning and generative AI solutions that have direct business impact.
• Own projects end-to-end from conception to operationalization, demonstrating an understanding of the full software development lifecycle.
• Provide technical vision and guidance to teammates.
• Mentor and contribute knowledge and software back to the analytics and engineering communities both within Nike and at large.

• Undergraduate degree in Computer Science, a Master's degree in a related engineering field, or equivalent experience.
• 10+ years of professional experience in software engineering.
• 3+ years of experience in the field of Machine Learning Engineering or related fields.
• Experience in Python, with a strong background in algorithms and data structures.
• Hands-on AWS experience and expertise with cloud architecture and technologies, especially Amazon Web Services.
• Experience with database technology (e.g., Postgres, Redis) and data processing technology (e.g., Sagemaker or DataBricks).
• Demonstrable history of team leadership and value delivery.
• Comfortable working in an agile product model, with expertise in agile development and test-driven development.
• Strong analytical mindset and experience leading others in problem solving.
• Proficiency working in a team and mentoring others to write robust, maintainable, and extendable code in Python, containerized in Docker and automated with CI/CD.
• Expertise with data structures, data modeling, and software architecture.
• Expertise in producing predictive or mathematical optimization models and deploying them to production.
• Experience with complex data sets, ETL pipelines, SQL, and general data engineering.
• Effective communication skills with team members, stakeholders, the business, and in code.
• Experience influencing technical strategy through all aspects of technical design and implementation.

• Expertise in MLOps or API development.
• Expertise with Spark, Kubernetes, Docker, Jenkins, Databricks, or Terraform.