Autonomous Driving Simulation

Autonomous Driving Simulation Engineer Jobs

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Today

Senior Machine Learning Engineer, Perception - Autonomous Driving

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$184k - $357k/yr Full time Artificial Intelligence Autonomous Driving Perception Autonomous Driving Simulation

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Job Description

NVIDIA is seeking a Senior Machine Learning Engineer specializing in perception for autonomous driving. The role focuses on developing and productizing traffic signal understanding solutions that do not rely on HD maps, with emphasis on end-to-end perception, deep learning model development, and performance improvements across robustness, accuracy, and efficiency.

Responsibilities

Design end-to-end solutions spanning Perception and the AV stack to support traffic signal detections across varied driving environments, from complex intersections to rural roads and highways.
Conduct applied research and development of deep learning models for traffic light detection, traffic sign recognition, road marking detection, construction object detection, text recognition, and other traffic signal tasks.
Develop generalizable methods to support diverse operational design domains (ODDs) and enable country or region expansion.
Lead data-driven development efforts by partnering with large data collection and labeling teams to prioritize collection and labeling, optimize labeling efficiency, and maximize the value of high-impact data to improve perception system accuracy.
Use data simulation and augmentation to address extreme scenarios.
Productize perception solutions by aligning with product requirements for safety, latency, and software robustness.

Requirements

Minimum qualification: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years in Computer Science, Computer Engineering, or a related technical field.
2+ years of technical leadership demonstrating high technical and organizational complexity is a plus.
Hands-on experience building deep learning and algorithmic solutions for sophisticated real-world problems, including proficiency with deep learning frameworks such as PyTorch.
Experience with data-driven development and collaboration with data and ground truth teams.
Strong programming skills in Python and/or C++.
Outstanding communication and teamwork skills in a tightly-knit team focused on ongoing discussion and learning.

Key Technologies

PyTorch
Python
C++
Deep learning frameworks
Transformers
BEV architectures
Visual Language Models

Benefits

You will also be eligible for equity and benefits.

How to Stand Out

Proven expertise developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras.
Hands-on experience developing and deploying DNN-based solutions to embedded platforms for real-time applications.
Proven deep learning expertise supported by technical publications in leading conferences and journals.
Expertise with Visual Language Models, Transformers, BEV architectures, and modern traffic signal perception techniques, including strong performance on complex object detection and recognition problems.

Job Details

Location: Santa Clara, CA (onsite)
Salary Range: USD 184,000 - 356,500 per year
Minimum Experience: 4 years
Education: PhD

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Today

Senior Synthetic Data Engineer - Autonomous Driving

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$184k - $357k/yr Full time Senior Autonomous Driving Simulation Cloud Data Engineering

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Job Description

NVIDIA is building simulation-driven capabilities for autonomous driving, and this role focuses on turning reconstructed driving worlds into high-quality synthetic data at production scale. As a Senior Synthetic Data Engineer, you will design simulation environments and synthetic data pipelines using NVIDIA Omniverse NuRec and Cosmos, with an emphasis on multi-sensor realism, dataset quality assessment, and robust pipeline operations.

This position is based in Santa Clara, CA on an onsite basis, with an expected compensation range of USD 184,000 - 356,500 per year. Experience requirements include 8+ years in relevant engineering and technical domains.

What you’ll do

Build, implement, and optimize tools to generate synthetic data for training different DRIVE deep learning networks, including simulated lidar, radar, camera/RGB-D, bounding boxes, object tracks, world models, segmentation, depth, scene semantics, and sensor metadata.
Develop lidar and radar sensor simulation workflows that run on NuRec reconstructed driving worlds and Cosmos-generated environments, covering sensor placement, calibration, material response, geometry handling, noise modeling, and scenario variation.
Develop a Cosmos world model to improve world generation, including controllable scenario generation, novel view synthesis, trajectory extrapolation, scene completion, quality triage, regression detection, and controllability evaluation.
Gather perception, planning, and deep learning DRIVE network requirements, then map them to existing synthetic data and sensor simulation features, adding new tools or improving performance when gaps are found.
Create dataset quality assessments and synthetic-real comparison procedures to evaluate sensor realism, annotation quality, distribution coverage, scenario diversity, and sim-to-real transfer for autonomous driving.
Set up, profile, and oversee large-scale NuRec, Cosmos, and sensor simulation pipelines in data center or cloud environments.
Debug end-to-end, cross-stack systems spanning sensors, reconstruction models, world models, simulation runtime, GPU workloads, distributed data services, and downstream autonomous-driving workloads.

Required qualifications

B.S. or M.S. in Computer Science, Electrical Engineering, Computer Engineering, Applied Math, Physics, or a related field (or equivalent experience).
8+ years of experience in computer graphics, computer vision, autonomous driving, sensor simulation, neural rendering, or physically-based sensor modeling, synthetic data generation, or closely related software engineering roles.
Strong skills in Python and C++, including experience building, debugging, profiling, and maintaining production-quality systems on Linux.
Solid mathematical foundation in linear algebra, geometry, and probability.
Familiarity with synthetic data annotations, data formats, dataset curation, data augmentation, and evaluation workflows for perception model training and validation.
Familiarity with deep learning workflows and modern ML tooling, with enough practical depth to translate network needs into synthetic data requirements and measurable quality criteria.
Experience with scalable engineering workflows, including Git, Docker, Kubernetes, CI/CD, distributed storage, and deployment in data centers or cloud environments.

Technologies

Python, C++, Linux, Git, Docker, Kubernetes, CI/CD
NuRec, Cosmos, NVIDIA Omniverse
Distributed storage, cloud, data center

Equity and benefits

You will also be eligible for equity and benefits.

Ways to stand out

Practical experience working directly with NVIDIA NuRec, Cosmos, world foundation models, Real2Sim systems, or autonomous-driving simulation and validation pipelines.
Experience in NuRec world reconstruction, neural rendering, including 3D Gaussian Splatting, NeRFs, or occupancy networks.
Deep lidar or radar simulation expertise, including ray tracing or ray casting, reflectance and intensity modeling, Doppler, radar cross-section, weather effects, occlusion, and sensor-specific noise models.
Experience developing synthetic data pipelines for autonomous driving, including closed-loop simulation, domain randomization, long-tail scenario mining, or sim-to-real transfer.
Familiarity with autonomous vehicle data pipelines and formats such as OpenDRIVE, HD maps, scenario formats, vehicle dynamics, or AV safety validation.

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Autonomous Driving Simulation Engineer Jobs

Senior Machine Learning Engineer, Perception - Autonomous Driving

Senior Synthetic Data Engineer - Autonomous Driving

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