Software Engineer - Neural Simulation

Applied Intuition • Sunnyvale, CA

17h • Onsite

About The Position

Applied Intuition, Inc. is seeking software engineers to build the backbone of Neural Simulation, a state-of-the-art product for transforming real-world driving data into high-fidelity simulation environments. The team designs and develops systems for large-scale reconstruction, synthetic data generation, and log augmentation, along with ML pipelines for training and validating autonomy systems. This role involves working on distributed systems that process real-world data into simulation environments and generate high-quality labeled data at scale, collaborating with senior engineers on system design across compute, storage, and data pipelines. It's an ideal position for engineers interested in the intersection of large-scale distributed systems and machine learning, aiming to scale a cutting-edge product and address critical data and platform gaps in Physical AI.

Requirements

• 2+ years of experience shipping production software
• A minimum of a Bachelor's degree in computer science, computer engineering, or equivalent practical experience
• Experience building backend services or data pipelines, and working with data storage systems (such as SQL, NoSQL, or data lakes)
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized systems (Docker, Kubernetes)
• Experience with backend development in languages such as Python and Go
• Solid software engineering fundamentals and strong problem-solving skills

Nice To Haves

• Experience with distributed systems at scale
• Experience building or supporting ML training and serving infrastructure
• Experience with GPU workloads and batch orchestration (e.g., Kubernetes jobs, Ray, Airflow)
• Experience with synthetic data generation or data augmentation for ML
• Familiarity with computer vision, 3D reconstruction (e.g., Gaussian Splatting), or sensor simulation (camera, LiDAR, radar)
• Experience with autonomous driving or robotics systems

Responsibilities

• Build and maintain scalable systems for Neural Simulation, including closed loop simulation and log augmentation workflows
• Develop services and data pipelines that process and manage large-scale data
• Contribute to infrastructure for ML workflows, including training pipelines, evaluation and validation systems, and model inference pipelines
• Implement and optimize storage solutions for structured, unstructured, and multimodal data (e.g., sensor, 3D, logs)
• Improve system reliability, observability, and performance across distributed services
• Collaborate closely with Infra, Autonomy, Research and other product teams to deliver end-to-end solutions
• Own features and components end to end, from design through deployment, and contribute to architecture discussions

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree