Software Development Engineer (AWS ML), Machine Learning Israel (MLIL) — FLOW sub-team (Fleet Lifecycle & Operational Workflows)

Overview In this role you will design and build scalable automation, tooling, and monitoring software for next‑gen ML accelerator servers. You’ll collaborate with Hardware, Manufacturing, and EC2 teams to streamline software delivery and qualification from first silicon to fleet deployment. You will transform raw hardware test data into actionable insights and build dashboards to monitor fleet health and performance. This is an opportunity to shape production software infrastructure that enables reliable hardware validation at scale. ResponsibilitiesDesign and develop scalable software infrastructure, automation frameworks, deployment systems, and orchestration platformsCoordinate with Hardware, Manufacturing, and EC2 teams to automate software delivery and qualification workflowsDebug root-cause analysis of hardware/software interactions using data-driven automationOwn end-to-end CI/CD pipelines from code commit to production validationCreate data pipelines (ETL, aggregation, real-time reporting) to turn test results into engineering insightsDevelop monitoring dashboards and visualization tools for fleet health, yield tracking, and benchmarkingOwn features end-to-end from design through deployment and operations Key requirements3+ years of software development experienceBachelor's degree in Computer Science, Electrical Engineering, Computer Engineering or relatedProficiency with Linux and related toolsKnowledge of software engineering best practices across the development life cycle (agile, code reviews, builds, testing, operations)Cross-functional collaborationAnalytical mindset with data-driven approachProblem solving and debuggingLinux proficiencyCI/CDData pipelines, ETL, analytics (S3, Athena, Spark)