Nike - Beaverton, OR

posted 2 months ago

Full-time - Mid Level
Remote - Beaverton, OR
Leather and Allied Product Manufacturing

About the position

As a Senior Machine Learning Engineer within the AI/ML team at NIKE, Inc., you will play a pivotal role in developing advanced analytics systems that have a direct impact on the business. This position is designed for individuals who thrive at the intersection of machine learning and software engineering, commonly referred to as MLOps. You will collaborate with a cross-disciplinary team that includes data scientists, software engineers, and infrastructure experts to enable data-driven decision-making across various organizations within Nike. Your work will involve creating high-quality solutions that leverage the latest technologies in statistical, unsupervised, supervised, and machine learning models at a global scale. In this role, you will be responsible for analyzing and profiling data to uncover insights that support scalable solutions. You will clean, prepare, and verify the integrity of data for analysis and model creation, while also tracking model accuracy, performance, relevance, and reliability. Your expertise will be crucial in applying a variety of machine learning and collaborative filtering methods to data sets, as well as aiding in the development of APIs and software libraries that facilitate the adoption of models in production. You will be expected to stay ahead of industry trends, recommending relevant technologies and products in the areas of Analytics, Machine Learning, Artificial Intelligence, and Data Science tools. Given the rapid pace of change in technology and machine learning, you will be encouraged to push the boundaries of what is possible and maintain a proactive approach to innovation. Additionally, you will embody Nike's core values in your work, effectively communicating and building trust with peers and stakeholders.

Responsibilities

  • Develop advanced analytics systems that impact business decisions.
  • Collaborate with cross-disciplinary teams to enable data-driven decision making.
  • Create high-quality solutions at the intersection of machine learning and software engineering (MLOps).
  • Analyze and profile data to uncover insights for scalable solutions.
  • Clean, prepare, and verify the integrity of data for analysis and model creation.
  • Track model accuracy, performance, relevance, and reliability.
  • Apply machine learning and collaborative filtering methods to data sets.
  • Build APIs and software libraries to support model adoption in production.
  • Stay ahead of industry trends and recommend relevant technologies and products.
  • Communicate effectively and build strong relationships across the company.

Requirements

  • Bachelor Degree or a combination of relevant education, training, and experience.
  • 3+ years of experience in ML Engineering or Software Engineering.
  • Understanding of Machine Learning applications and lifecycle in production.
  • Ability to articulate the role of MLOps in model development.
  • Strong communication skills to convey technical topics effectively.
  • Experience working in or collaborating with distributed teams.
  • Strong understanding of data structures, algorithms, and data solutions.
  • Experience with Python (or similar languages) and SQL for ML and data engineering tasks.
  • Familiarity with ETL, ML, or analytics technologies such as Scikit-learn, TensorFlow, or Spark.
  • Awareness of data science platforms and CI/CD pipelines.

Nice-to-haves

  • Interest in Generative AI for accelerating development and data science tasks.
  • Experience with deploying Generative AI solutions in the enterprise.

Benefits

  • Generous total rewards package.
  • Casual work environment.
  • Diverse and inclusive culture.
  • Professional development opportunities.
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