Remote Lead ML Engineer | End-to-End ML & AI Platform

Nike Inc; Beaverton (OR); Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Remote interview accommodations

Job summary

Lead Machine Learning Engineer at Nike Inc in Beaverton, OR, develops robust analytics and ML solutions with end-to-end ownership from concept to operationalization. You will provide technical vision to teammates within Nike's AI/ML teams in Portland, Boston, and Poland, collaborating on scalable ML problems at scale.

Role requires strong Python, AWS, ML/MLOps, Docker, CI/CD, SQL/ETL, Spark, Kubernetes, Databricks, Terraform, Snowflake, PostgreSQL tech.

Qualifications

• Master’s degree in Information Systems or Computer Science plus 2 years of experience in engineering-related occupation.

Responsibilities

• Develop robust analytics and machine learning solutions with end-to-end ownership from conception to operation.
• Provide technical vision and guidance to teammates within Nike’s AI/ML teams across locations.
• Design and implement scalable applications leveraging prediction models and optimization programs to deliver data-driven decisions.
• Contribute to core analytics platforms and share knowledge with the analytics and engineering communities.

Skills

Python

AWS

ML Ops

SQL

Data Modeling

Software Architecture

CI/CD

Data Structures

Spark

Kubernetes

Databricks

Terraform

PostgreSQL

Snowflake

Docker

Jenkins

Education

Master’s degree in Information Systems or Computer Science

Tools

Python

AWS

Docker

CI/CD

Jenkins

Apache Spark

Kubernetes

Databricks

Terraform

Snowflake

PostgreSQL

Job description

Lead Machine Learning Engineer at Nike Inc in Beaverton, OR, develops robust analytics and ML solutions with end-to-end ownership from concept to operationalization. You will provide technical vision to teammates within Nike's AI/ML teams in Portland, Boston, and Poland, collaborating on scalable ML problems at scale.

Role requires strong Python, AWS, ML/MLOps, Docker, CI/CD, SQL/ETL, Spark, Kubernetes, Databricks, Terraform, Snowflake, PostgreSQL tech.