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Tier-1 brand, metro location, and broad ML/MLOps requirements increase candidate competition.
Core ML engineering and MLOps skills are transferable across industries, with moderate domain specificity.
Explicit 8+ years, 3+ years ML, and specific MLOps/AWS requirements make shortlisting highly strict.
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Own end-to-end development and operationalization of scalable AI/ML and generative AI solutions for corporate functions at Nike.
Lead technical direction, set engineering quality standards, and mentor team members in an agile product environment.
Design and implement predictive and optimization models integrated into production systems with measurable business impact.
8+ years of professional software engineering experience; 3+ years in machine learning engineering or related fields.
Undergraduate degree in Computer Science, or Master’s in related engineering field, or equivalent experience.
Proficiency in Python, AWS (SageMaker, Lambda, API Gateway, ECR), and database technologies (Postgres, Redis).
Experience with MLOps, containerization (Docker), CI/CD, and agile methodologies.
Experienced technical leader comfortable influencing strategy and mentoring engineers in an agile, collaborative environment.
Strong background in software architecture, data modeling, and deployment of machine learning models at scale.
Hands-on expertise with cloud-native AI/ML platforms, modern data processing pipelines, and MLOps practices.