Lead Machine Learning Engineer, ITC bei NIKE

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

NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, protected veteran status, or disability. NIKE is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the employment process, please call +1 503-671-4156 and let us know the nature of your request, your location and your contact information.