Software Development Engineer – Infrastructure and Automation
Develop production software for validating, deploying, monitoring, and qualifying machine-learning accelerator servers across manufacturing and fleet environments.
Responsibilities
- Design and develop scalable automation frameworks, deployment systems, and test orchestration platforms.
- Build and own CI/CD pipelines from code commit through build, testing, deployment, and production validation.
- Create data pipelines and analytics systems that transform hardware test results into engineering insights.
- Develop monitoring dashboards, alerting systems, and visualization tools for fleet health, yield, and performance benchmarking.
- Debug and root-cause hardware and software interaction failures through data analysis and automated triage.
- Collaborate with hardware, manufacturing, and cloud infrastructure teams on software delivery and qualification workflows.
- Own features through design, implementation, testing, deployment, and operational support.
Requirements
- At least 3 years of software development engineering or related experience.
- Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related discipline, or equivalent experience.
- Proficiency with Linux and associated tools or languages.
- Knowledge of software engineering practices across the development lifecycle, including agile methods, coding standards, code reviews, source management, build processes, testing, and operations.
- Ability to work proactively and independently, meet deadlines, and deliver projects and tasks.
Nice to have
- Experience with monitoring dashboards and data visualization tools such as Grafana, CloudWatch, or QuickSight.
- Experience with data pipelines, ETL, or analytics technologies such as S3, Athena, or Spark.
- Experience with C, C++, or Rust.
- Familiarity with PCIe, memory hierarchy, and power management.
- Experience with hardware bring-up, ASIC or FPGA validation, or manufacturing test development.