Lead Software Engineer — GPU HPC & Agentic AI

MACHINE LEARNING TECHNOLOGIES LLC

Irving (TX)

On-site

USD 150,000 - 210,000

Full time

2 days ago

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Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Irving, TX seeks a Lead Software Engineer to drive simulation foundation platforms, GPU computing, and agentic AI initiatives. You will optimize CUDA/C++ workloads and lead multi-GPU scaling across NVIDIA Omniverse and Isaac Sim.

The role requires 7+ years of experience, strong C++/Python, and deep CUDA expertise. You will collaborate with robotics and AI teams, manage container-based GPU workloads, and work with cloud providers like AWS/Azure.

Qualifications

7+ years of relevant software engineering experience.
Strong proficiency in CUDA, C++, and Python.
Deep expertise in CUDA programming, GPU performance optimization, and NVIDIA GPU architecture.
Strong experience with Agentic AI and autonomous agents for automated code and runtime optimization.
Hands-on experience with NVIDIA Omniverse, Isaac Sim, or equivalent simulation engines.
Practical experience with NVIDIA Nsight tools, including Nsight Systems, Nsight Compute, and Nsight Graphics.
Strong understanding of multi-GPU systems, parallel processing, and distributed computing.
Experience with Linux, Docker, Kubernetes, and Slurm.
Proven ability to benchmark, debug, and optimize compute-intensive workloads.
Experience with RTX and real-time rendering workloads.
Background in robotics, digital twins, or simulation platforms.
Knowledge of HPC environments and large-scale GPU clusters.
Experience with CI/CD pipelines and automated performance benchmarking frameworks.
Familiarity with ML infrastructure, AI training, and synthetic data generation.

Responsibilities

Analyze and optimize workloads across CPU, GPU, memory, I/O, storage, and networking using NVIDIA Nsight tools.
Refactor and optimize simulation codebases using CUDA, C++, and Python to improve hardware utilization and execution performance.
Design and implement agentic AI systems for automated code analysis and runtime performance optimization.
Optimize and scale simulation workloads using NVIDIA Omniverse and Isaac Sim across multi-GPU and distributed computing environments.
Manage and optimize containerized GPU workloads using Docker, Kubernetes, and Slurm.
Work with GPU cloud infrastructure, including CoreWeave, AWS, and Azure.
Develop automated regression testing, observability, and performance benchmarking solutions.
Collaborate with robotics, perception, and AI engineering teams to improve simulation performance and scalability.
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline.
Minimum 7+ years of relevant software engineering experience.
Strong programming proficiency in C++ and Python.
Deep expertise in CUDA programming, GPU performance optimization, and NVIDIA GPU architecture.
Strong experience with Agentic AI and autonomous agents for automated code and runtime optimization.
Hands-on experience with NVIDIA Omniverse, Isaac Sim, or equivalent simulation engines.
Practical experience with NVIDIA Nsight tools, including Nsight Systems, Nsight Compute, and Nsight Graphics.