Senior Deep Learning and Computer Vision Engineer, Autonomous Vehicles

Nvidia

Quick summary

Work type
On-site
Location
Santa Clara, CARedmond, WASeattle, WA
Salary
$152,000–$241,500 / yr
Posted
3 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $223k
This role $197k
$138k most similar roles pay here $279k

This role pays less than 68% of similar roles. Most pay $196,750–$249,750 — the shaded band above. At the midpoint, this role pays about $197k versus about $223k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 942 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 931 roles with salary data.

Most-posted roles

View all roles at Nvidia

At a glance

TL;DR · Senior Deep Learning and Computer Vision Engineer, Autonomous Vehicles

Role Posting Log in to save

Join NVIDIA’s Autonomous Vehicles team as a Deep Learning and Computer Vision engineer, where you’ll apply cutting-edge techniques to build ground truth for autonomous vehicles, working closely with top researchers to deliver impactful solutions globally. Your day-to-day will involve staying current with deep learning advancements, implementing new ideas, collaborating on innovative research projects, defining training datasets, and building robust software pipelines using PyTorch, TensorFlow, TensorRT, Python, and C++. Ideal candidates have a PhD or MS in Computer Science or related fields, along with experience in deep learning, computer vision, planning/control, and programming skills in C++/Python. You should be passionate about AI for robotics and autonomous navigation, capable of solving complex problems, and experienced in unsupervised/self-supervised learning, sensor data fusion, and architecture optimization.

Skills

PyTorch TensorFlow TensorRT Python C++ NVIDIA GPUs Deep Learning Computer Vision Machine Learning Unsupervised Learning Self-supervised Learning Sensor Fusion LIDAR Pruning Curriculum Training Multi-task Training CI/CD

What you'll do

  • Implement and experiment with state-of-the-art deep learning techniques for autonomous vehicles.
  • Define and collect large-scale training datasets for machine learning models.
  • Build end-to-end training pipelines and real-time inference systems using PyTorch or TensorFlow.
  • Collaborate on transforming innovative research into industrial-strength machine learning solutions.
  • Fuse data from multiple sensor modalities to enhance perception and decision-making in autonomous vehicles.

What we're looking for

  • PhD with 1+ year or MS with 5+ years in Computer Science/Engineering.
  • Proven experience building robust software for AI applications.
  • Expertise in Deep Learning/Machine Learning and Computer Vision.
  • Strong programming skills in C++ and Python.
  • Experience in unsupervised/self-supervised learning methods.
  • Background in fusing data from multiple sensor modalities.
  • Ability to work collaboratively with researchers and engineers.

Related searches

More Senior Deep Learning and Computer Vision Engineer jobs Senior Deep Learning and Computer Vision Engineer jobs in Santa Clara All jobs at Nvidia

More like this

Similar roles

Principal Deep Learning Engineer, Perception, Autonomous Driving

Nvidia

Santa Clara, CA 5 days ago $272,000–$431,250
Python PyTorch C++ TensorRT NVIDIA DRIVE Deep Learning Computer Vision Object Detection Semantic Segmentation Multi-Object Tracking Data Labeling Quality Control Metrics Model Optimization Quantization Embedded Platforms CVPR ICCV ECCV NeurIPS Autonomous Driving Robotics
Save

Senior Machine Learning Engineer, Perception

Nvidia

Remote 24 days ago $184,000–$287,500
Python C++ PyTorch Deep Learning Data-Driven Development Transformers BEV Architectures Embedded Platforms Real-Time Applications GPU NVIDIA GPUs
Remote
Save