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Software Engineer, ML Performance Optimization

Zoox

Salary$177k - $270k
Before you apply

Role details

The practical picture
Employment
Full-time
Role signal brief

The role, at a glance

Extracted from the source posting · 95% confidence

Zoox is hiring a Software Engineer to optimize ML training and inference performance for autonomous robotaxi models using SOTA accelerators. The role involves scaling VLM, VLA, and foundational models while collaborating with cross-functional autonomy teams.

Compensation
USD 177,000–270,000 / year

What you need

  • 4+ years of total experience
  • 2+ years of working on large-scale model training or inference platforms
  • Experience with training frameworks like PyTorch
  • Experience with GPU-accelerated inference using TensorRT or similar frameworks
  • Experience using profiling tools like NVIDIA's Nsight or PyTorch's Profiler
  • Proficiency in Python or C++

What you will own

  • Design, implement, and operate cutting-edge ML Training OR Inference performance optimization techniques to scale VLM, VLA, and Foundational models
  • Deploy ML models efficiently in Zoox robotaxis
  • Collaborate with cross-functional teams including ML researchers, software engineers, data engineers, and hardware engineers
Core skills
PyTorchTensorRTNVIDIA NsightC++PythonDistributed TrainingGPU OptimizationModel Pruning
Internal freshness window ends Oct 21, 2026
View source evidence
  • salary “min': 177000, 'max': 270000”
  • must_have “4+ years of total experience, including 2+ years of working on large-scale model training or inference platforms.”
pytorchtensorrtnvidia nsightc++
Role brief
Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible.    The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.   We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent.

In this role, you will:

  • Design, implement, and operate cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deploy them efficiently in our robotaxi.

  • Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.

  • Qualifications

    Note: You do not have to meet all the requirements below to be considered for this position:
  •  4+ years of total experience, including 2+ years of working on large-scale model training or inference platforms.
  • Experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.
  • Experience with GPU-accelerated inference using TensorRT or similar frameworks.
  • Experience using profiling tools like NVIDIA's Nsight or PyTorch's Profiler for identifying model training and serving bottlenecks.
  • Proficient in Python or C++.
  • Additional

    About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
    Follow us on LinkedIn
    AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
    A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.