Lead Machine Learning Engineer R-62501

Nike; Beaverton (OR); Remote; USD 110,000 - 150,000; Full time

Job summary

Nike is seeking a Lead Machine Learning Engineer to develop and implement integrated software solutions that leverage data across product and systems applications. The ideal candidate will possess a Master's degree in Computer Science or Statistics, with a strong background in machine learning techniques, programming languages, and cloud architecture. This role offers the opportunity to work with cutting-edge technologies in a collaborative environment, driving innovation and delivering high-impact solutions.

Benefits

Flexible work hours

Telecommuting options

Accessibility accommodations for applicants

Qualifications

• Experience developing production code in Python, Golang, Java, and Scala.
• Knowledge of AI/ML techniques and recommendation algorithms.
• Experience with data and ML pipelines using Scikit-learn and Spark ML.

Responsibilities

• Develop and program integrated software algorithms for data analysis.
• Adapt machine learning for various applications including virtual and augmented reality.
• Architect and deliver cloud solutions and ML systems for real-time performance.

Skills

Machine Learning

Statistical Modeling

Data Analysis

Programming in Python

Cloud Solutions

Education

Master’s degree in Computer Science or Statistics

Tools

Python

TensorFlow

Spark

AWS

Google Cloud

SQL

OpenCV

Job description

Lead Machine Learning Engineer- NIKE USA INC- Beaverton, OR.Develop and program integrated software algorithms to structure, analyze and leverage data in product and systems applications in both structured and unstructured environments; develop and communicate descriptive, diagnostic, predictive and prescriptive insights/algorithms; use machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis and others; develop and evaluate algorithms to improve product system performance, quality, data management and accuracy; use current programming language, technologies to translate algorithms and technical specifications into code; complete programming and implement efficiencies, perform testing and debugging; complete documentation and procedures for installation and maintenance; apply deep learning technologies to give computers the capability to visualize, learn and respond to complex situations; adapt machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience; and work with large scale computing frameworks, data analysis systems and modeling environments. Telecommuting is available from anywhere in the U.S., except from SD, VT, and WV.

Employer will accept a Master’s degree in Computer Science or Statistics and two (2) years of experience in the job offered or in a computer-related occupation.

Experience must in the following:

• Developing and delivering production code in languages such as Python, Golang, Java, and Scala

• Frameworks including Spark and Hadoop

• AI/ML techniques such as neural networks, tree ensembles, regressions, and hypothesis testing

• Building Data and ML pipelines using Scikit-learn, Tensorflow, spark ML (MLlib), and OpenCV

• SQL

• Architecting and delivering cloud solutions using Google Cloud and AWS

• Recommendation and search algorithms including ALS, Neural Nets, Clustering, personalization techniques, time series, NLP, and image modeling

• A/B testing

• End-to-end lifecycle of ML systems including ML engineering development and designing and building low latency real-time systems

• Delivering and supporting high impact solutions across large datasets to production;

• Spark streaming

• MLOps and the lifecycle of model development from experimentation to production and measurement and visualization

Apply at www.Nike.com/Careers (Job # R-62501)

#LI-DNI

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.