Software Engineer, Machine Learning Performance

Nimbus Data Systems is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Nimbus Data Systems has focused on building the Nimbus Data Systems Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Nimbus Data Systems Driver powers Nimbus Data Systems’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Nimbus Data Systems Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Nimbus Data Systems's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle’s software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms. This role follows a hybrid work schedule, and you will report to the Tech Lead Manager of the Machine Learning Performance team. You will: Design and implement technical solutions for performance optimization of individual ML models Execute end-to-end tasks consistently and in a timely manner, contributing directly to larger performance goals for ML accelerators Collect, trace, and analyze application/ML model performance data to identify specific optimization opportunities, and prototype solutions at the application or compiler Collaborate with infrastructure teams (e.g., compiler, runtime) to implement and land performance-critical optimizations. Uphold engineering quality by contributing to design documents, participating in timely code reviews, and writing comprehensive unit tests for your work products Proactively spot and suggest areas of future performance work within the team's scope You have: BS degree in Computer Science/Electrical Engineering or equivalent, or equivalent practical experience 3+ years of experience writing complex C++ code 3+ years of experience writing code in Python 1+ years experience in optimizing compute performance for ML applications Experience in compute architectures and performance analysis optimization methodologies We prefer: Experience in ML compiler design and implementation Experience in performance tools, simulators, HW/SW codesign Experience in robotic application development/optimizations Proficiency in collaboration with application teams and infrastructure teams The expected base salary range for this full-time position is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Nimbus Data Systems employees are also eligible to participate in Nimbus Data Systems’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $2,600,000 — $3,150,000 TWD