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Position Details: Lead Software Engineer AI/ML - 1189715Z

Location: Beaverton, OR
Openings: 1
Job Number:



As a Lead Software Engineer in AI/ML Platforms, you will be part of a fast pace engineering team developing services and platform that drive AI/ML at Client. AI/ML is used in Client to accelerate its digital transformation and real-time data-based decision making capabilities. The focus is to leverage AI/ML technology to improve the user experience by using personalization, recommendation, smart search, digital demand sensing and scheduling techniques. These enhancements will be used to power, Client App, Client SNKRS App, NTC and NRC.

We are looking for a Lead Software Engineer to design and implement core components of our data science services and platform and scale it to serve Client globally. You will work collaboratively with the data science and analytics teams to ship scalable, performant and reliable solutions.

The successful candidate will:

Advance and improve development practices with the engineering team through participation in architecture, technical design and code reviews

Work with the user community to anticipate services and platform needs required to support algorithm development, model training, model management, data engineering and model serving

Develop and/or implement services to enable data scientists and ML engineers at Client. These services will include model training, model serving and model management

Evaluate new AI/ML Frameworks for possible long-term approaches

Develop proof-of-concept (PoC) projects designed to evaluate the feasibility of new data science projects, vendor supplied machine learning and/or AI platforms

Facilitate deep technical discussions with end-users and partners

Basic Qualifications

  • Strong Computer Science fundamentals
  • 4+ years of non-internship professional software development experience
  • Programming experience with at least one modern language such as Java, Python, Golang including object oriented design
  • Experience with Kubernetes and the broader container ecosystem
  • Experience with container-native machine learning ecosystem such as Kubeflow
  • Experience with AWS services (EC2, S3, DynamoBD, EMR)
  • Experience using open source machine learning and statistical frameworks such as TensorFlow, PyTorch, R etc.
  • Knowledgeable about machine learning (concepts and application)
  • Excellent written and oral communication skills on both technical and non-technical topics

Additional Qualifications

  • Experience with Big Data technologies (e. g. Spark)
  • Experience with Databricks ecosystem
  • Experience with SageMaker ecosystem
  • Experience with workflow orchestration systems such as Airflow
  • Experience with Infrastructure as Code practices and technologies like Terraform
  • Experience with source code control systems like GIT, Subversion.
  • Experience developing and using RESTful APIs (preferably micro services)


  • EC2


  • AWS

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