Senior ML Engineer - Generative AI & AWS

Nike; New South Wales; On-site; AUD 180,000 - 260,000; Full time

Job summary

Nike is seeking a Senior AI/ML Engineer to influence and develop robust machine learning and generative AI solutions that impact the business. The role requires hands-on Python, strong algorithms, and AWS expertise, with an emphasis on MLOps, data engineering, and scalable architectures.

You will design and implement scalable applications, mentor teammates, and collaborate with stakeholders across Nike's global engineering teams to deliver data-driven decisions at scale.

Qualifications

• Undergraduate degree in CS or related field, or equivalent experience.
• 5+ years of professional software engineering experience.
• 3+ years in ML engineering or related fields.
• Strong knowledge of MLOps and production ML lifecycle.
• Proficiency in Python, Docker, and CI/CD.
• Experience with AWS, SageMaker, and data processing tech.
• Mentorship and technical leadership experience.

Responsibilities

• Design and implement scalable AI/ML solutions for Nike's corporate functions.
• Lead and mentor engineers, driving robust, maintainable code.
• Collaborate with stakeholders and other tech teams to coordinate dependencies.
• Develop and deploy prediction models and optimization programs at scale.
• Contribute to advanced analytics platforms and tooling for ML workflows.

Skills

Python

AWS

MLOps

CI/CD

Docker

Data structures

SQL

Team leadership

Education

Bachelor's degree in Computer Science

Master's degree in related field

Tools

SageMaker

Postgres

Redis

Databricks

Spark

Job description

Nike is seeking a Senior AI/ML Engineer to influence and develop robust machine learning and generative AI solutions that impact the business. The role requires hands-on Python, strong algorithms, and AWS expertise, with an emphasis on MLOps, data engineering, and scalable architectures.

You will design and implement scalable applications, mentor teammates, and collaborate with stakeholders across Nike's global engineering teams to deliver data-driven decisions at scale.