ML Systems Integration Engineer
Build and debug software infrastructure for bringing up, validating, and qualifying distributed AI hardware systems. The role requires strong Python or C++ skills, Linux and operating systems knowledge, and the ability to diagnose complex hardware-software integration issues.
About the job
Responsibilities
- Participate in bring-up of next-generation AI hardware systems and supporting software infrastructure.
- Debug complex system-level issues spanning hardware and software interactions.
- Investigate system bring-up failures and identify root causes using logs, telemetry, and diagnostic tools.
- Build automation frameworks and internal tooling to improve system validation and debugging workflows.
- Develop software to test, validate, and stress distributed hardware systems during development and production cycles.
- Collaborate with hardware engineers to isolate and resolve system integration issues.
- Improve system observability by building tools that surface failures quickly and accelerate debugging.
- Reproduce, triage, and diagnose difficult issues during early hardware deployment.
- Support validation and qualification of new hardware generations as systems move toward production readiness.
- Improve internal engineering workflows related to debugging, testing, and automation.
Requirements
- BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
- Strong programming skills in Python and/or C++.
- Excellent debugging and problem-solving skills.
- Understanding of operating system fundamentals, including processes, threads, memory management, concurrency, and IPC.
- Experience working in Linux development environments.
- Understanding of computer architecture and hardware-software interactions.
- Strong analytical and communication skills, with the ability to work through ambiguous technical problems and collaborate across engineering teams.
Nice-to-haves
- Experience building automation frameworks, internal tooling, or test infrastructure.
- Familiarity with distributed systems concepts.
- Experience debugging large-scale systems or complex infrastructure environments.
- Understanding of networking fundamentals and communication between distributed systems.
- Experience with hardware-adjacent software or system integration environments.
- Familiarity with performance analysis, system telemetry, and log analysis.
- Exposure to production systems validation or infrastructure reliability engineering.
Skills
Python, C++, Linux, Operating Systems, Computer Architecture, Distributed Systems, Networking, Test Automation, System Telemetry, Log Analysis, Performance Analysis, Interprocess Communication
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