SDE II: ML Diagnostics & Fleet Analytics

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

Benefits offered by this job

Health insurance

RSUs

Sign-on bonus

401(k) matching

Parental leave

Job summary

Amazon MLA Vetting seeks a Software Development Engineer II to build data pipelines ingesting diagnostic results from thousands of servers, dashboards for test behavior, and metrics that indicate when tests flag failures before capacity loss. You will own alarms, production code, and anomaly detection, collaborating with hardware, firmware, and data-center teams.

You will use Python and SQL to produce scalable solutions, leveraging Redshift, Spark, and BI tools to deliver actionable insights and

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.

Skills

Python

SQL

Data pipelines

Education

Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field

Tools

Amazon Redshift

Apache Spark

Grafana

QuickSight

Job description

Amazon MLA Vetting seeks a Software Development Engineer II to build data pipelines ingesting diagnostic results from thousands of servers, dashboards for test behavior, and metrics that indicate when tests flag failures before capacity loss. You will own alarms, production code, and anomaly detection, collaborating with hardware, firmware, and data-center teams.

You will use Python and SQL to produce scalable solutions, leveraging Redshift, Spark, and BI tools to deliver actionable insights and