Become a Part of the NIKE, Inc. Team
NIKE, Inc. does more than outfit the world’s best athletes. It’s a place where passionate individuals come together to create the future of sport. We are unapologetic about who we are and what we’re after—bringing innovation and inspiration to every athlete* in the world. We look for athletes who can push boundaries, elevate our potential and continue leading us to greatness. The next tastemakers, playmakers, risk takers and glue players. Are you game?
WHO YOU’LL WORK WITH
You will work within the Supply Chain Planning & Technology (SCPT) organization, partnering with Product Managers, Data Scientists, Engineering teams, and Supply Chain stakeholders across Deployment Optimization (DO), Controlled Allocation (CA), and Dynamic Marketplace Allocation (DMA). This role drives advanced analytics and AI-led decisioning across supply chain platforms.
WHO WE ARE LOOKING FOR
We are looking for a Lead Machine Learning Engineer who can bridge data science and production-grade engineering to solve complex supply chain problems at scale. You bring strong system design skills, hands-on ML expertise, and the ability to lead engineering teams in delivering enterprise-grade AI solutions.
You are comfortable working in ambiguous environments, making architectural decisions, and influencing technical direction across teams. You have deep experience in building scalable ML systems, operationalizing models, and ensuring performance, reliability, and governance in production environments.
8–10 years of experience in software engineering and machine learning, with 2+ years in a technical leadership role
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field (or equivalent combination of education and experience)
Strong programming expertise in Python or R
Hands-on experience with ML frameworks (PyTorch, TensorFlow, Keras) and MLOps practices
Strong experience with cloud platforms (AWS, Azure, Google Cloud Platform) and containerization (Docker, Kubernetes)
Solid data engineering experience with tools and platforms such as Databricks, Apache Spark, Hive, and Airflow is good have
WHAT YOU’LL WORK ON
You will design and deliver scalable machine learning solutions that power supply chain decision-making across Nike. You will lead the end-to-end lifecycle of ML systems, from data ingestion and model development to deployment and real-time monitoring.
Architect and build scalable ML systems leveraging optimisation, NLP (Natural Language Processing), and advanced analytics
Lead end-to-end ML lifecycle (MLOps) including data pipelines, model training, deployment, and monitoring
Provide technical leadership and mentorship to engineering and data science teams
Build and maintain production-grade ML pipelines using CI/CD practices
Optimize model performance, latency, and scalability while ensuring data security and governance
Collaborate with product and business stakeholders to translate complex problems into ML-driven solutions
Evaluate emerging technologies (Generative AI, LLMs, agent-based workflows) and drive adoption where relevant
OUR HIRING GAME PLAN
01 Apply
Our teams are made up of diverse skillsets, knowledge bases, inputs, ideas and backgrounds. We want you to find your fit – review job descriptions, departments and teams to discover the role for you.
02 Meet a Recruiter or Take an Assessment
If selected for a corporate role, a recruiter will reach out to start your interview process and be your main contact throughout the process. For retail roles, you’ll complete an interactive assessment that includes a chat and quizzes and takes about 10-20 minutes to complete. No matter the role, we want to learn about you – the whole you – so don’t shy away from how you approach world-class service and what makes you unique.
03 Interview
Go into this stage confident by doing your research, understanding what we are looking for and being prepared for questions that are set up to learn more about you, and your background.
