below marketmost similar roles pay hereabove market
This role pays less than
63%
of similar roles. Most pay
$168,620–$235,750
— the blue band above.
At the midpoint, this role pays about
$194k
versus about
$202k
for comparable roles.
Based on 240 similar postings.
Employer
About Qualcomm
Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.
Qualcomm currently has
575 open roles
on FindRole.
Listed pay typically runs
$147,900–$221,900
across 550 roles with salary data.
The Software Engineer, Robotics Simulation & AI Infrastructure joins the Multimedia Systems team to develop an in-house simulation platform for general-purpose robots. You will design and build core simulator subsystems, including scene representation, physics backends, and sensor models for tasks like legged locomotion and tabletop manipulation. Key responsibilities include optimizing training workloads, integrating open engines like USD and Hydra, and building high-throughput paths for synthetic data generation and hardware-in-the-loop configurations. You will utilize technologies such as CUDA, PyTorch, ROS 2, and Kubernetes-native workflows like Argo Workflows. This role solves the challenge of closing the sim-to-real gap by creating a first-class simulation environment that enables on-device AI training and deployment across various robot form factors, ensuring software reliability before moving to physical hardware.
What does a Software Engineer earn in California?
Median $214500 from 1193 postings across 76 companies.
Design and build core simulator subsystems including scene representation, physics backends, sensor models, and rendering.
Profile and optimize simulation and training workloads to maintain high throughput for interactive and cloud sessions.
Integrate and extend open engines for GPU physics, USD/Hydra rendering, and offline path tracing behind clean interfaces.
Build high-throughput paths for policy training and synthetic data generation using vectorized environments and domain randomization.
Create simulation-based regression suites, deterministic replays, and benchmarks to gate software releases before hardware deployment.
Stand up hardware-in-the-loop configurations to run robotics software on Qualcomm silicon against a host-based simulator.
Model high-fidelity sensor behavior using real characterization and calibration data from internal sensor teams.
Develop continuous learning pipelines that integrate simulation into data generation, training, evaluation, and deployment workflows.
What we're looking for
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
Strong software engineering fundamentals with the ability to discuss production code in depth.
Working grasp of robotics simulation including rigid-body dynamics, kinematics, coordinate frames, numerical integration, or sensor models.
Experience with robotics simulators or real-time 3D engines like MuJoCo, Isaac Sim, PhysX, Gazebo, or Unreal Engine (preferred).
Proficiency in GPU programming and performance engineering including CUDA, Warp, Vulkan, or compute shaders (preferred).
Experience with machine learning for robotics, reinforcement learning, PyTorch, or 3D graphics pipelines like OpenUSD (preferred).
Robotics Simulation
NVIDIA Isaac Sim
Gazebo
MuJoCo
Webots
Unreal Engine
ROS
ROS2
PyTorch
TensorFlow
Isaac Lab
Digital Twin
Sim-to-Real
SIL
HIL
Reinforcement Learning
Synthetic Data Generation
NVIDIA Omniverse
Isaac Sim
Unreal Engine
C++
Python
OpenUSD
PhysX
CUDA
Kubernetes
Ray
gRPC
Protocol Buffers
CI/CD
Bazel
CMake
Reinforcement Learning
LiDAR
Radar
GNSS
Sim-to-Real
SIL
HIL
Slurm