Senior Machine Learning Engineer

Job Overview

Nike is seeking a Senior Machine Learning Engineer to join our dynamic team. This role is pivotal in developing and programming integrated software algorithms to structure, analyze, and leverage data in product and systems applications across both structured and unstructured environments. You will be responsible for designing and communicating descriptive, diagnostic, predictive, and prescriptive insights/algorithms.

Key Responsibilities

• Develop and implement machine learning (ML) and statistical modeling techniques such as decision trees, logistic regression, and Bayesian analysis to enhance product/system performance, quality, data management, and accuracy.
• Translate algorithms and technical specifications into code using Python and other current programming languages and technologies.
• Implement, test, debug, and optimize algorithms, ensuring efficiency and accuracy.
• Complete documentation and procedures for software installation, maintenance, and updates.
• Apply deep learning technologies to enable visualization, learning, and response to complex scenarios.
• Adapt ML to applications in virtual reality, augmented reality, artificial intelligence, robotics, and interactive user experiences.
• Work with large-scale computing frameworks, data analysis systems, and modeling environments.

What You Bring

• Proficiency in Python and Spark, with experience in high-performance, parallel, and distributed computing to scale Machine Learning solutions.
• Familiarity with cloud platforms such as AWS, GCP, and Azure, and experience in deploying Machine Learning models using these platforms.
• Experience with data science platforms like SageMaker and similar offerings from other providers.
• Skilled in building and maintaining Machine Learning pipelines using tools like Airflow or Kubeflow, and tracking experiments with tools such as mlflow, TensorBoard, and SageMaker Experiments.
• Understanding of model explainability and monitoring, and proficiency in scaling machine learning models to handle large datasets and high-dimensional feature spaces.
• Experience with distributed computing frameworks like Apache Spark and GPU acceleration tools like CUDA for efficient model training and inference.
• Knowledge of techniques for model compression, quantization, and optimization for deployment in resource-constrained environments.
• Proficiency in using data visualization libraries like Matplotlib, Seaborn, Plotly, and tools like Tableau, Splunk, and SignalFX for analyzing logs, metrics, and creating dashboards.
• Familiarity with different API architectural styles like REST, Websocket, gRPC, SOAP, etc.
• Experience with continuous integration/continuous deployment (CI/CD) tools such as Jenkins.
• Familiarity with Infrastructure as Code (IaC) tools such as Terraform for creating, updating, and versioning infrastructure safely and efficiently.
• Experience with version control systems like Git for tracking changes in source code during software development.
• Hands-on experience with secure model deployment tools like Docker and Kubernetes, understanding of network security for data transit, and knowledge of secure data storage and handling practices.

Qualifications

• Typically requires a Bachelor's Degree and a minimum of 9 years of directly relevant work experience.
• Alternatively, a PhD or Law degree with 6 years of experience, a Master's degree with 7 years of experience, or an Associate's degree with 9 years of experience may be accepted.

Join Nike and contribute to a world-class team where you can explore potential, obliterate boundaries, and push the edges of what can be. Embrace diversity and reward imagination in a challenging and constantly evolving environment.