Become a Part of the NIKE, Inc. Team

NIKE, Inc. does more than outfit the world’s best athletes. It is a place to explore potential, obliterate boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream and create. Its culture thrives by embracing diversity and rewarding imagination. The 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 YOU’LL WORK WITH

Working as part of Global Technology’s Machine Learning/AI organization, our team supports the Nike Digital Channels by implementing innovative athlete* facing experiences. You’ll work directly with technical and non-technical Machine Learning/AI stakeholders, athlete*s, and other teams within Global Technology.

 

WHO WE ARE LOOKING FOR

We are looking for an ambitious Software Engineer I – Machine Learning/AI with a passion for cloud-native development and platform ownership. You are someone who thrives in a collaborative environment, is excited by cutting-edge technology, and excels at problem-solving. You have a strong understanding of AWS Cloud Services, Kubernetes, DevOps, Databricks, Python and other cloud-native platforms. You should be an excellent communicator, able to explain technical details to both technical and non-technical stakeholders and operate with urgency and integrity.


To be considered for this position, the candidate should:

  • Have strong technical and non-technical communication skills, including translating business and research goals into technical requirements.
  • Bachelor’s degree in information technology, computer science or related field. Will accept any suitable combination of education, experience or training.
  • 1+ years’ experience building and deploying machine learning models in production environments with Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow).Strong experience building and deploying machine learning models in production environments
  • Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow).
  • Experience working with data pipelines and distributed systems (e.g. Spark, Airflow) to support ML workflows
  • Experience designing and delivering production-grade LLM/agent workflows, including tool/function calling, orchestration patterns, and retrieval-augmented generation (RAG).
  • Experience integrating LLM capabilities into existing services and SDLC, including CI/CD, testing strategies (unit/integration + LLM evals), and safe rollout patterns (feature flags, canaries, A/B tests)
  • Ability to collaborate effectively across functions, demonstrating strong ownership and a collaborative mindset
  • Demonstrates an agile mindset, adapting approaches based on data and evolving priorities while maintaining focus on outcomes
  • Growing AI fluency, with the ability to independently apply ML techniques and emerging tools (including LLMs) to solve problems responsibly.
  • Experience with AWS SageMaker, Docker/containerization, FastAPI.
  • Experience with inference optimization (latency tuning, caching, embedding serving, and search ranking/information retrieval

WHAT YOU’LL WORK ON

 

  • Build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement.
  • Own problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment.
  • Develop and maintain scalable ML pipelines using tools such as Spark and Airflow to support reliable, high-quality model delivery.
  • Apply modern ML frameworks (e.g. PyTorch or TensorFlow) to design, train, and optimize models in production environments.
  • Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset.
  • Collaborate cross-functionally with Product and Engineering, working with purpose to translate product questions into ML solutions.
  • Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor.
  • Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.

Apply Now
What You Can Expect

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.

Two people smiling and embracing in an outdoor setting