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High competition: Tier-1 brand, popular ML role, mid-level experience and broad skill requirements.
Medium because core ML/MLOps skills transfer across industries, though enterprise corporate-functions experience is advantageous.
High due to explicit years, mandatory ML/MLOps, cloud, production engineering, and tooling requirements.
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Develop and deploy scalable machine learning and generative AI solutions with direct business impact for Nike’s corporate functions.
Design and implement AI applications leveraging prediction models and optimization programs to enable data-driven decisions.
Contribute to advanced analytics, ML, and generative AI platforms and tools supporting both model development and operationalization.
Undergraduate degree in Computer Science, Master’s in related engineering field, or equivalent experience.
5+ years professional experience in software engineering; 3+ years specifically in Machine Learning Engineering or related fields.
Proficiency in Python, AWS (ECR, SageMaker, Lambda, API Gateway), containers (Docker), CI/CD, and frameworks like Scikit-learn, PyTorch, or Tensorflow.
Experience with MLOps, data engineering (ETL, SQL), and pipeline orchestration tools such as AirFlow or Databricks Workflows.
Experienced technical leader with a history of mentoring and delivering value in agile, product-focused environments.
Strong expertise in cloud architecture, software design, and working with complex data sets at scale within distributed global teams.
Ability to influence technical strategy and collaborate effectively with stakeholders across multiple teams and functions.