Senior Software Engineer (Neural Simulation)
Posted
Summary
Senior Software Engineer (Neural Simulation) at Applied Intuition designs and builds distributed systems that convert real-world driving data into high-fidelity simulation environments, including ML pipelines, large-scale storage, and infrastructure for autonomous driving. Core technologies include Python, Go, cloud platforms, Kubernetes, and ML training/serving infrastructure.
- We are looking for senior software engineers to build the backbone of Neural Simulation, our state-of-the-art product for turning real-world driving data into high-fidelity simulation environments
- As part of this team, you will design and develop the systems that power large-scale reconstruction, synthetic data generation, and log augmentation, along with the ML pipelines used to train and validate autonomy systems
- You will work on highly distributed systems that transform real-world data into simulation environments and generate high-quality labeled data at scale, where careful system design across compute, storage, and data pipelines is essential
- Design and build scalable closed loop simulation systems using Neural Reconstruction
- Architect systems that process and manage large-scale data
- Develop infrastructure for ML workflows, including:
- Training pipelines
- Evaluation and validation systems
- Model inference pipelines
- Design 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
- Take ownership of critical systems and influence architecture and product decisions
- This role is ideal for engineers who thrive at the intersection of large-scale distributed systems and machine learning, and who are excited to scale a state-of-the-art product while building new capabilities that solve the hardest data and platform gaps in Physical AI
- Experience with backend development in languages such as Python and Go
- A proven track record of designing, building, and operating scalable distributed systems, data pipelines, and data storage solutions (such as SQL, NoSQL, vector databases, or data lakes)
- Strong system design and problem-solving skills
- Experience with cloud platforms (AWS, GCP, or Azure) and containerized systems (Docker, Kubernetes)
- 5+ years of experience shipping complex, large-scale software
- A minimum of a Bachelor’s degree in computer science, computer engineering, or equivalent practical experience
- Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway
- Experience with GPU workloads and large-scale batch orchestration (e.g., Kubernetes jobs, Ray, Airflow)
- Experience building or supporting ML training and serving infrastructure
- 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