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