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Cisco ML Tech Lead 
United States, Georgia, Atlanta 
386150730

18.11.2024

The deadline for applications for this role is expected to be Monday, October 21.

Together we build for the futureby designing simple solutions for complex problems.


What You’ll do:

As a Machine Learning Engineering Tech Lead on the Duo AI and Security Research team, you will design and build systems to handle our ML-powered applications. You will collaborate with teams in the Data Science & Engineering organization to support our existing Duo Trust Monitor and Risk-based Authentication systems, develop new data-powered products, and improve our Zero Trust product offering. By joining our team, you’ll help build the next generation of our machine learning applications. Responsibilities include:

  • Work with researchers, engineers and product teams tackling technical problems of high complexity to deliver machine learning based solutions in areas such as threat detection, policy recommendation, and text-based AI assistants
  • Design, develop and extend our machine learning infrastructure capabilities (job orchestration, feature engineering, model monitoring etc.) and support our running models in production
  • Collaborate with engineering teams throughout Duo to improve and communicate our engineering & infrastructure standard methodologies
Minimum Qualifications for this role:
  • 4+ years professional Python development experience
  • 3+ years experience working with cloud infrastructure, including AWS
  • Experience developing and maintaining large-scale machine learning and/or data processing systems
  • Experience leading software development within a team and/or experience mentoring junior engineers
Preferred Skills and Experience:
  • Experience supporting and operating high-availability, customer-facing software products
  • Experience with data processing and storage frameworks such as Spark, Delta Lake, or Athena
  • Familiarity with Feature Store concepts and operations
  • Experience with machine learning model serving frameworks like Sagemaker or Seldon
  • Experience with infrastructure-as-code tools like Terraform
  • Familiarity with Kubernetes and its ecosystem
  • Experience prioritizing and planning engineering work in collaboration with external stakeholders