Nuro · 3 months ago
Tech Lead Manager, ML Training Infrastructure
Mountain View, CA
Full-time
Onsite
Senior Level, Lead/Staff
$235K/yr - $352K/yr
6+ years expNuro is a self-driving technology company on a mission to make autonomy accessible to all. They are seeking an experienced Technical Lead Manager to drive the adoption of quantization techniques and lead a team in optimizing ML infrastructure for autonomous vehicles.
Artificial Intelligence (AI)Autonomous VehiclesRoboticsTransportation
Responsibilities
Setting technical direction for the Training Infrastructure team
Staying ahead of emerging research and evaluating new methods
Establishing telemetry to root-cause quality regressions in lower precision training
Driving the adoption of quantized training methods (e.g., AWQ, AQT, GPTQ) across Nuro’s ML infrastructure to accelerate model training and inference
Leading the design and implementation of efficiency initiatives for model training, including low-bit quantization, pruning, and knowledge distillation, for both research and production workloads
Collaborating cross-functionally with research, infrastructure, and product teams balancing accuracy, latency, and resource constraints
Mentoring and growing a high-performing team of engineers and researchers
Qualification
Required
6+ years of professional or research experience in ML infrastructure, distributed training, or ML systems engineering
Hands-on experience with quantization methods, including Activation-Aware Weight Quantization (AWQ), Accurate Quantized Training (AQT), FP-8 training, or related methods
Knowledge of broader model compression techniques, such as structured/unstructured pruning and knowledge distillation
Experience building or maintaining quantization libraries (e.g., AQT, bitsandbytes, NVIDIA Transformer Engine, DeepSpeed Compression)
Understanding of calibration and scaling strategies for quantized models to minimize accuracy loss
Setting technical direction for the Training Infrastructure team
Staying ahead of emerging research and evaluating new methods
Establishing telemetry to root-cause quality regressions in lower precision training
Driving the adoption of quantized training methods (e.g., AWQ, AQT, GPTQ) across Nuro's ML infrastructure to accelerate model training and inference
Leading the design and implementation of efficiency initiatives for model training, including low-bit quantization, pruning, and knowledge distillation, for both research and production workloads
Collaborating cross-functionally with research, infrastructure, and product teams balancing accuracy, latency, and resource constraints
Mentoring and growing a high-performing team of engineers and researchers
Preferred
Advanced degree (Ph.D. or strong M.Sc. with research experience) in Computer Science, Electrical Engineering, or related fields
Knowledge of sparse networks and complementary model compression techniques (e.g., AdaRound, BRECQ, structured pruning)
Published work or open-source contributions in quantization methods (e.g., AWQ, AQT, GPTQ, SmoothQuant, ZeroQuant)
Benefits
Annual performance bonus
Equity
Competitive benefits package
Company
Nuro
Nuro is a robotics company specializing in the development of autonomous driving technologies.
501-1000 employees
H1B Sponsorship
Nuro has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (50)
2024 (67)
2023 (91)
2022 (91)
2021 (68)
2020 (55)
Funding
Current Stage
Late StageTotal Funding
$2.34BKey Investors
Disney AcceleratorTiger Global ManagementT. Rowe Price
2025-08-21Series E· $97M
2025-04-09Series E· $106M
2024-04-06Secondary Market
Leadership Team
Jiajun Zhu
Co-Founder and Co-CEO
Dave Ferguson
Co-Founder
Recent News
Business Insider
2026-01-07
2026-01-07
Business – Baltimore Sun
2026-01-07
Company data provided by crunchbase