Amazon
MAC Automation & Analytics Engineer, Leo MAC
$144K–$194K
Redmond, WA · Full-time · Posted May 20, 2026
- Experience
- 3+ years non-internship professional software development; 2+ years non-internship design or architecture; 1+ years software development engineer or related occupational experience; 1+ years designing and developing large-scale software applications; 1+ years Object Oriented Design. Preferred: 3+ years full software development life cycle.
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
- Visa sponsorship
- Candidates must be a U.S. citizen or national, U.S. permanent resident (current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
About the job
Build and own a MAC analytics tool and feature automation framework that analyzes telemetry, automates diagnostics, and validates MAC features across releases.
What you'll do
- Develop ML-based MAC diagnostics and analytical pipelines using SDN and telemetry data.
- Build and maintain automated MAC feature tests, including scenario-based and regression testing integrated into release qualification.
- Create accessible diagnostic interfaces and collaborate with domain experts and release teams.
What they ask for
- 3+ years of non-internship professional software development experience.
- 2+ years of non-internship design or architecture experience.
- 1+ years of experience developing large-scale software applications using C#, C++, Java, or Perl; and 1+ years of Object Oriented Design experience.
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field; experience programming with at least one software programming language.
Nice to have
- 3+ years of full software development life cycle experience.
- Background in wireless/MAC systems, telemetry pipelines, anomaly detection, forecasting, or release qualification and CI/CD.
Pay
143,700.00 - 194,400.00 USD annually (base salary)
Tools
C#, C++, Java, Perl, SDN, telemetry, ML
AI focus
Develop ML-based anomaly detection and predictive capabilities, and self-improving analytical pipelines for triage, root cause analysis, and reporting.
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