Lead Machine Learning Engineer AI/ML - Consumer Marketplace (Remote Work Option)

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 we are looking for

Nike is looking for a Lead Machine Learning Engineer to join our growing team. This role is part of a squad within Enterprise Data & AI Consumer AI/ML team, that is responsible for building solutions that will transform the customer experience in Nike Digital Platform. Playing a key role in the development of digital tools, processes, and experiences, the ideal candidate is a problem-solver who is motivated to learn new technologies, communicate ideas and knowledge, and collaborate with teammates. You will work with a cross-functional team to build solutions that will transform the customer experience in Nike Digital Platform. You need to be able to work with ambiguity and abstract requirements, developing features quickly in a team context, balancing speed with quality. Above all, your work will accelerate Nike's core mission of serving Athletes*

WHO WILL YOU WORK WITH?

Our team has Machine Learning Engineers, Software Engineers, and Data Scientists. You will work day-to-day with your peer Machine Learning Engineers, Software Engineers, Product Management and other squad team members to achieve business objectives. You will also engage with other Global Technology functions and teams on organizational and technical goals.

WHAT YOU WILL DO

• Apply machine learning, collaborative filtering, NLP, and deep learning methods to massive data
• Provide technical leadership, establishing standards and principles for your team to follow.
• Support investigation of new software packages/tools, APIs, and algorithms to deliver quality analytics and machine learning at scale
• Collaborate with a cross functional agile team of software engineers, data engineers, ML experts, and others to build new product features
• Contribute to all processes of the ML lifecycle: data collection, annotation, modeling, evaluation, deployment, and monitoring
• Write production-quality code for ML models as online services and APIs
• Present complex analyses clearly and concisely
• Ability to build collaborative relationships with peers and multi-functional partners
• Provide support by writing documentation and tutorials as well as providing guidance to users with a variety of technical skills.

       

WHAT YOU BRING

• Bachelor's Degree or higher in Statistics, Computer science or a combination of relevant education, training, …