ML Systems Integration Engineer

Cerebras Cerebras · Semiconductors · Headquarters +1 · Software

The ML Systems Integration Engineer at Cerebras will focus on bringing up and debugging next-generation AI hardware systems and their supporting software infrastructure. This involves developing automation frameworks, internal tooling, and software for testing and validation of distributed hardware systems, with a strong emphasis on system-level issue resolution spanning hardware and software interactions, and improving system observability.

What you'd actually do

  1. Participate in bring-up of next-generation AI hardware systems and supporting software infrastructure.
  2. Debug complex system-level issues spanning hardware and software interactions.
  3. Investigate failures occurring during system bring-up and identify root causes using logs, telemetry, and diagnostic tools.
  4. Build automation frameworks and internal tooling that improve system validation and debugging workflows.
  5. Develop software used to test, validate, and stress distributed hardware systems during development and production cycles.

Skills

Required

  • Python
  • C++
  • debugging
  • problem-solving
  • operating systems fundamentals
  • Linux development environments
  • computer architecture
  • hardware and software systems interactions
  • analytical thinking
  • collaboration

Nice to have

  • automation frameworks
  • internal tooling
  • test infrastructure
  • distributed systems concepts
  • large-scale systems debugging
  • networking fundamentals
  • hardware-adjacent software
  • system integration
  • performance analysis
  • system telemetry
  • log analysis
  • production systems validation
  • infrastructure reliability engineering

What the JD emphasized

  • complex system-level issues
  • system integration issues
  • ambiguous technical problems

Other signals

  • AI chip
  • inference speeds
  • agentic computation
  • OpenAI partnership
  • 750 megawatts of scale
  • ultra high-speed inference