Machine Learning Engineer (Runtime & Optimization)

TL;DR

Machine Learning Engineer (Runtime & Optimization): Improve compute performance for ML workloads on cloud and self-driving cars with an accent on efficient deep learning models, model compression, and ML software stack. Focus on analyzing and optimizing system workloads, deploying models on limited resources, and leading collaborations with perception, planner, research, and simulation teams.

Location: Hybrid in Mountain View, California

Salary: $204,000—$259,000 USD

Company

Autonomous driving technology company building the hirify.global Driver for fully autonomous ride-hail service and vehicle platforms.

What you will do

• Lead collaboration with hirify.global ML scientists in perception, planner, research, and simulation to identify performance opportunities in systems and models.
• Lead projects from proposals to execution, developing junior engineers.
• Analyze and improve ML workloads on cloud and self-driving cars.
• Apply model optimization, efficient deep learning techniques, and ML software improvements to hirify.global's ML systems.

Requirements

• M.S. in CS, EE, Deep Learning or related field
• 2+ years as technical lead, including project plans, customer engagement, mentoring, goals execution, and status reporting
• 5+ years developing ML systems or software stack (Pytorch/JAX/TF, runtime libraries, ML compiler)
• Deep understanding of ML system architecture, performance analysis, and tools
• Strong Python or C++ programming skills

Nice to have

• PhD in CS, EE, Deep Learning or related field
• Familiarity with HW architecture of ML accelerators (GPU/TPU)
• Deep knowledge of model optimization or efficient deep learning for foundation models or LLMs
• Experience with GPU/TPU hardware and related system software

Culture & Benefits

• Discretionary annual bonus program
• Equity incentive plan
• Generous company benefits program