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XIn accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
Health, dental, vision, life, disability insurance
Retirement Benefits: 401(k) with company match
Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
Baby Bonding Leave: 18 weeks
Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Kirkland, WA, USA.
Minimum qualifications:
Bachelor's degree in Computer Engineering,
Electrical Engineering, Computer Science, or IT-related field, or equivalent practical experience.
8 years of experience with Linux/Unix systems and experience in debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
5 years of experience in technical leadership.
3 years of experience with technical infrastructure (e.g., deployment, maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
3 years of debug or validation experience with CPU, GPU, or TPU.
Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).
Preferred qualifications:
Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
Experience with systems automation, and with systems design and debug.
Experience with ML frameworks (e.g., TensorFlow, PyTorch), with the understanding of the AI/ML training and inference life-cycle.
Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-premises or cloud environment.
Understanding of memory and high-speed IO technologies.