Open to remote work except in South Dakota, Vermont and West Virginia.
The annual base salary for this position ranges from $199,200.00 in our lowest geographic market to $471,100.00 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 is a technology company. From our flagship website and five-star mobile apps to developing products, leading big data and providing groundbreaking engineering and systems support, our teams at NIKE Global Technology exist to revolutionize the future at the confluence of tech and sport. We invest and develop advances in technology and employ the most creative people in the world, and then give them the support to constantly innovate, iterate and serve consumers more directly and personally. Our teams are innovative, diverse, multidisciplinary and collaborative, taking technology into the future and bringing the world with it.
Who we are looking for
Nike is looking for an elite 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. You will work on a variety of complex business problems specifically focused on inventory optimization, demand sensing and forecasting, pricing and markdown, replenishment optimization, etc. You will lead teams across multiple Geographies. You will test new and interesting hypotheses, productionalize and scale ML solutions in the cloud as APIs, stream processing, or massive batch processing. You will use big data, parallel processing technologies, traditional machine learning methods, and deep learning techniques to quantitatively plan product demand, allocate resources, and target the right customers with the best products. You will champion partnerships with best of breed open-source communities, commercial vendors, and universities. Above all, your work will accelerate Nike’s core mission of serving Athletes.
Who you are
- A shown technical leader with deep knowledge and experience in creating production grade, end-to-end machine learning services at scale. As comfortable discussing modern ML algorithms (e.g. RNNs, LLMs, Reinforcement Learning, GenAI), optimization techniques, deep learning, as you would discuss the CAP theorem. Able to dive deep into code and architecture to provide an informed opinion on benefits/trade-offs of different design choices.
- Highly organized and able to handle multiple timelines, priorities, and teams with ease. At the same time, able to quickly flex and pivot due to changing circumstances which present new opportunities for Nike.
- An effective communicator who can seamlessly progress between discussing high level vision with executives to low level tactics with the dev team. You are able to influence people and align efforts across the company to act as one in pursuit of a common goal.
- A constant learner who is passionate about staying at the forefront of the engineering and machine learning landscape through reading journals, books, or blogs. In equal measure, someone who is passionate about growing people and understanding how to effectively lead an organization.
What you will work on
- Build a compelling vision and an amazing machine learning engineering organization to support Demand Forecasting, Supply Chain Optimization, new AI and GenAI products at Nike.
- Develop a vision and long-term goals for how your teams will serve Nike’s employees and consumers with AI, plan the strategy for achieving those goals, and oversee its implementation towards the north star you set.
- Build and grow highly skilled, cross-functional product teams that deliver end-to-end AI capabilities for Nike (e.g. optimized demand forecasting, allocation optimization, fulfillment, etc.). Manage the professional development and career plans for those on your teams, help us develop the technology leaders of tomorrow.
- Set high standards for engineering excellence, MLOPs, operational excellence, and drive innovation through Nike’s personalization function.
- Apply engineering and machine learning best practices to consistently deliver scalable,production-grade solutions while actively managing costs and overhead. Continually raise the bar to improve standards, quality, reliability, and velocity of the teams.
- Use your prior experience, knowledge of industry trends, and personal creativity to develop new and innovative solutions which delight our customers. 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 stakeholders, and direct reports.
- Role model transparency and accountability as a leader of Nike. Communicate effectively, build trust and strong relationships across the company, do the right thing.
- Engage employees meaningfully, assist the teams by removing roadblocks, align efforts across Nike’s matrix to drive progress forward and always win as a team.
Who you will work with
Artificial Intelligence and Machine Learning (AI/ML) is one of the key groups within Enterprise Data and AI and we have been chartered to help scale machine learning across Nike. One way we do this is by bringing cross-disciplinary teams of data scientists and engineers to areas of the business which are early in their AI 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 improve the velocity of those data science teams in delivering value to the business. Our teams work across time zones in the US West, US East, and Europe. 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).
What you bring
- Bachelor’s Degree in computer science, software engineering, or related field (Masters or Ph.D. preferred)
- 10 + years of experience in developing production grade code, preferably related to analytics or machine learning.
- Deep knowledge of software architecture and engineering best practices, especially modern cloud computing stacks for deploying machine learning and microservices at scale. For example, AWS Sagemaker, EKS for Kubernetes, Docker for containers, Jenkins for CI/CD, Tensorflow or Keras for a deep learning framework.
GenAI Artificial intelligence (AI) MLOps reinforcement-learning amazon-eks Docker Kubernetes Machine Learning TensorFlow keras Jenkins Amazon SageMaker LLM