SDE II: ML Acceleration Data Pipelines & Analytics

Amazon Inc.; Austin (TX); On-site; USD 144,000 - 194,000; Full time

Job summary

Amazon’s MLA Vetting team seeks a Software Development Engineer II to build data pipelines, dashboards, and analytics that expose test results across the Trainium and Inferentia fleet. You will ingest diagnostic data, define metrics, and develop production code that scales with tens of thousands of servers.

You will collaborate with hardware, firmware, and operations teams, and you should be fluent in Python and SQL, with experience in Redshift, Spark, and Grafana/QuickSight.

Qualifications

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems 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

Responsibilities

• Design, build, and operate production data pipelines that ingest diagnostic, telemetry, and repair-ticket data from the Trainium and Inferentia fleet into a warehouse other teams query with confidence.
• Build and own the metrics, alarms, and anomaly detection that surface test regressions, failure-rate shifts, and new failure signatures across hardware generations without a human going looking for them.
• Build dashboards and visualizations that make fleet and test health legible to engineers, hardware partners, and leadership, covering failure rates, failure-signature breakdowns, first pass yield, and repair latency.
• Analyze large-scale fleet data to find root cause behind failure trends, and separate genuine hardware faults from software defects and test noise — a distinction that decides whether a failure reaches a technician or an engineer.
• Define the evidence standard that gates operational decisions, including whether a diagnostic has soaked long enough and cleanly enough in the fleet to move from observation mode into blocking production.
• Improve data quality and pipeline reliability so downstream consumers trust the numbers without re-deriving them.
• Write clear analyses and design documents for technical and non-technical readers, including leadership.

Job description

Amazon’s MLA Vetting team seeks a Software Development Engineer II to build data pipelines, dashboards, and analytics that expose test results across the Trainium and Inferentia fleet. You will ingest diagnostic data, define metrics, and develop production code that scales with tens of thousands of servers.

You will collaborate with hardware, firmware, and operations teams, and you should be fluent in Python and SQL, with experience in Redshift, Spark, and Grafana/QuickSight.