Manager– AI/ML Engineering

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.
 

NIKE, Inc. does more than outfit the world’s best athletes. It is a place to explore potential, obliterate boundaries and redefine what can be. We look for colleagues who can grow, think, dream and create. Our culture thrives by embracing diversity and rewarding imagination. The Nike 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. 
 

WHO ARE WE LOOKING FOR  

Nike is looking for an emerging or experienced Engineering leader who can lead and grow teams of machine learning engineers, data scientists, and software architects to deliver scalable machine learning and artificial intelligence solutions to customers across our business. As a Manager in AI/ML Engineering, you will be a part of a cross-disciplinary (data/API/infra/infosec/ML) engineering leadership team tasked with collaborating to execute on the AI/ML organization’s charter. In this role you will be working at the intersection of machine learning and engineering (i.e., MLOps), leading teams to deliver innovative and high-quality services which power Nike’s supply chain. You will be a strong advocate and facilitator for both engineering best practices (e.g. code reviews, unit testing) and also the adoption of new technologies (e.g. DataBricks, SageMaker, LLM optimization) which can help us move faster on our journey. In this way, you will be responsible for coaching engineers to continuously elevate their engineering skills and for growing their careers at Nike. 

 

WHO WILL YOU WORK WITH  
Artificial Intelligence and Machine Learning (AI/ML) is one of the key groups within Data and Artificial Intelligence and we have been chartered to help scale machine learning across Nike.  We bring cross-disciplinary teams of data scientists and engineers to areas of the business which are early in their analytics journey. For areas of the business which are more mature and already have data science teams, we help scale machine learning by providing squads of engineers to maximize the velocity of those data science teams in delivering value to the business. Lastly, we work closely with our platform and architecture partners to develop capabilities which help machine learning scale easier at Nike (e.g. model management, A/B testing, feature stores).  This role reports to the Director of AI/ML Engineering. 

 

 
Essential Job Functions: 

• Collaborate as part of a cross-functional leadership team to grow highly skilled, diverse engineering teams that deliver solutions which unlock machine learning for Nike.  Engage employees, assist the teams by removing roadblocks, and align efforts across Nike’s matrix to drive progress forward and always win as a team. 

• Leverage your prior experience, knowledge of industry trends, and personal creativity to develop and drive new and innovative solutions which delight our customers in their mission to serve Athletes*. 

• Stay current with industry trends and recommend relevant technologies & products in the areas of analytics, machine learning, artificial intelligence, and data science. Given the rapid pace of change in technology and machine learning today, always be pushing the boundary of what’s possible and be on the offense always. 

• Embrace and embody Nike’s core values (maxims) in your work and interactions with peers, stakeholders, and direct reports.  Model clarity and accountability as a leader of Nike. Communicate effectively, build trust and strong relationships across the company, do the right thing. 

• Be a mentor to teams, individuals, and technical leaders to foster motivated contributors, collaborative stakeholders, and high performing teams.  Set high standards for engineering excellence, MLOPs, operational excellence, and drive innovation. 

• Curiosity. 

 

WHAT YOU BRING TO NIKE 

• Demonstrated technical leadership with deep knowledge and experience in delivering production grade software at scale. Able to dive deep into code and architecture to provide an informed opinion on benefits/trade-offs of different design choice. 

• Comparable Bachelor’s Degree in computer science, software engineering, or applicable field (’s degree or Ph.D. preferred). 

• 5+ years of experience across multiple roles in developing productionized code in software or data engineering, machine learning or a related field (experience delivering analytics and ML products preferred). 

• Experience in a technical leadership or management role using Agile frameworks, processes, and team structures. 

• Familiarity with ETL, ML, or analytics technologies such as Scikit-learn, Dask, Tensorflow, Kubeflow, Spark, EMR, or similar platforms and frameworks.  

• Must be able to meaningfully communicate, written, orally, and visually, technical topics with stakeholders and articulate the benefits and tradeoffs of each solution and connect them to business value. 

• Fluency in the application of open-source technologies and the impact of standardized platforms. Ability to make build/buy decisions in the area of Data Science, AI, & ML. 

• Must be able to articulate and evangelize aspects of MLOps, code management workflows, infrastructure as code, and the lifecycle of model development from experimentation to production and measurement.  This will include significant knowledge of software architecture and engineering best practices, especially modern cloud computing stacks for deploying machine learning at scale. 

• Practical skills in team leadership and building positive relationships across Product, Architecture, and Engineering, and ability to influence decisions and changes across loosely coupled teams. 

• The habits of a constant learner. 

 

 

Apply