Autonomous Driving Simulation

Autonomous Driving Simulation Developer Jobs

2 jobs found

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

Build and productize autonomous driving perception systems for traffic signal understanding with solutions designed to work without reliance on HD maps.

Responsibilities

Design end-to-end perception and AV stack solutions for traffic signal detections across diverse driving environments, from complex intersections to rural roads and highways
Conduct applied research and development of deep learning models for traffic signal tasks, including:
- Traffic light detection
- Traffic sign recognition
- Road marking detection
- Construction object detection
- Text recognition
- Other traffic signal-related tasks
Develop generalizable methods to support diverse ODDs and enable country or region expansion
Drive data-driven development by partnering with large data collection and labeling teams to prioritize high-value data:
- Data collection prioritization and planning
- Labeling prioritization
- Labeling efficiency optimization
- Maximize the value of data to improve perception accuracy
Use data simulation and augmentation to address extreme and rare scenarios
Productize perception solutions by meeting product requirements for safety, latency, and software robustness

Requirements

Minimum education and experience:
- PhD with 4+ years, or
- 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 with high technical and organizational complexity is a plus
Hands-on experience building deep learning models and algorithms to solve complex real-world problems
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++
Strong communication and teamwork skills in a collaborative, learning-focused environment

Technologies

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

Benefits

Eligible for equity and benefits

Ways to Stand Out

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

Location: Santa Clara, CA (onsite)

Compensation: USD 184,000 - 356,500 per year

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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 the next generation of simulation and synthetic data workflows through NVIDIA DRIVE, with a focus on producing high-quality multi-sensor datasets for autonomous driving training. In this role, you will design and develop simulation environments and synthetic data pipelines using NVIDIA Omniverse NuRec and Cosmos, supporting both sensor simulation and dataset evaluation at scale. The work spans reconstruction-driven worlds, controllable scenario generation, and the engineering needed to run production-grade pipelines in data center or cloud environments.

What you’ll do

Build, implement, and optimize tools that generate synthetic data for training different DRIVE deep learning networks, covering 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 operate on NuRec reconstructed driving worlds and Cosmos-generated environments, including 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 DRIVE network requirements, then align them with current synthetic data and sensor simulation capabilities, creating new tools or improving existing performance when gaps appear.
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 cross-stack systems across sensors, reconstruction models, world models, simulation runtime, GPU workloads, distributed data services, and downstream autonomous-driving workloads.

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 Python and C++ skills, with 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, including the ability to translate network needs into synthetic data requirements and measurable quality criteria.
Experience with scalable engineering workflows such as 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

Compensation and eligibility

Salary: USD 184,000 - 356,500 per year. 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, 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 such as OpenDRIVE, HD maps, scenario formats, vehicle dynamics, or AV safety validation.

Location: Santa Clara, CA (onsite).

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Autonomous Driving Simulation Developer Jobs

Senior Machine Learning Engineer, Perception - Autonomous Driving

Senior Synthetic Data Engineer - Autonomous Driving

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