Principal Machine Learning Engineer

wn end-to-end ML Ops strategy and execution for high-impact initiatives.

• Design, build, and deploy scalable machine learning models across diverse domains, ensuring production-grade reliability and performance.

• Mentor and coach other Machine Learning Engineers, fostering technical excellence and growth.

• Translate business objectives into ML solutions, proactively developing options to achieve strategic goals.

• Experiment with and implement a broad range of algorithms, from classical models to deep learning architectures.

• Collaborate with product, engineering, and data science teams to integrate ML solutions into Nike's product creation and merchandising ecosystem.

• Drive continuous improvement in model performance through rigorous evaluation, error analysis, and optimization.

• Champion best practices in ML Ops, including CI/CD pipelines, monitoring, and governance.

WHO YOU WILL WORK WITH

You'll partner closely with peer machine learning engineers, data scientists, and product managers across Consumer Product & Innovation delivery teams. You'll also collaborate with engineering and platform teams to scale ML solutions globally.

WHAT YOU BRING

• PhD, Masters or Bachelors degree in Data Science, Applied Statistics, Software Engineering or related field. Will accept any suitable combination of education, experience and training.

• 8-10+ years of experience in machine learning engineering, with increasing leadership responsibilities (years may vary based on advanced degrees).

• Proven experience deploying ML models into production environments at scale.

• Expertise in ML Ops practices, including automation, monitoring, and lifecycle management.

• Strong foundation in machine learning algorithms and statistical methods, with exposure to a wide range of techniques.

• Proficiency in Python, SQL, and modern ML frameworks (e.g., TensorFlow, PyTorch, MLFlow, SageMaker).

• Experience with cloud-based ML platforms and distributed computing tools (e.g., Databricks, PySpark).

• Ability to mentor and lead technical teams, fostering collaboration and innovation.

• Excellent communication skills-able to simplify complex concepts for diverse audiences.

• Advanced degree in Computer Science, Machine Learning, or related field preferred.

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.