Senior Software Engineer, Neural Simulation

Applied Intuition; Sunnyvale (CA); On-site; USD 185,000 - 250,000; Full time

Job summary

Applied Intuition, Inc. in Silicon Valley is seeking senior software engineers to build Neural Simulation, turning real-world driving data into high-fidelity simulation environments.

You will design and develop distributed systems that power reconstruction, synthetic data generation, and labeled data pipelines used to train and validate autonomy systems. This role sits at the intersection of large-scale distributed systems and machine learning, requiring you to scale a state-of-the-art product

Qualifications

• 5+ years of experience shipping complex, large-scale software.
• Bachelor's degree in computer science, computer engineering, or equivalent practical experience.
• Proven track record designing, building, and operating scalable distributed systems and data pipelines.

Responsibilities

• 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: training pipelines, evaluation/validation, and model inference pipelines.
• Design and optimize storage for structured, unstructured, and multimodal data.
• Improve reliability, observability, and performance across distributed services.
• Collaborate with Infra, Autonomy, Research and product teams to deliver end-to-end solutions.
• Take ownership of critical systems and influence architecture and product decisions.

Skills

5+ years experience

Bachelor's degree

Distributed systems

Cloud platforms

Python & Go

System design

Education

Bachelor's degree in CS/CE

Tools

Docker

Kubernetes

SQL/NoSQL/Vector DB

Job description

Applied Intuition, Inc. in Silicon Valley is seeking senior software engineers to build Neural Simulation, turning real-world driving data into high-fidelity simulation environments.

You will design and develop distributed systems that power reconstruction, synthetic data generation, and labeled data pipelines used to train and validate autonomy systems. This role sits at the intersection of large-scale distributed systems and machine learning, requiring you to scale a state-of-the-art product