Neural Simulation Engineer: Build Scalable ML Pipelines

Decisive Point; Sunnyvale (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Applied Intuition, Inc. is building the backbone of Neural Simulation in Sunnyvale, CA, where engineers design scalable backend services and data pipelines powering large-scale reconstruction and synthetic data generation for autonomous systems.

You will work with distributed systems, ML pipelines, and storage solutions while collaborating with cross-functional teams. The role emphasizes end-to-end ownership, reliability, and performance improvements in production environments, with in-office

Qualifications

• 2+ years of experience shipping production software.
• 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.

Responsibilities

• Build and maintain scalable backend services for Neural Simulation.
• Develop data pipelines and storage solutions for large-scale data.
• Contribute to infrastructure for ML workflows, including training, evaluation, and inference pipelines.
• Improve reliability, observability, and performance across distributed services.
• Collaborate with Infra, Autonomy, Research and product teams to deliver end-to-end solutions.
• Own features end-to-end from design through deployment.

Skills

Production software

Education

Bachelor's degree in CS/CE

Tools

Docker

Kubernetes

AWS

GCP

Azure

Python

Go

Job description

Applied Intuition, Inc. is building the backbone of Neural Simulation in Sunnyvale, CA, where engineers design scalable backend services and data pipelines powering large-scale reconstruction and synthetic data generation for autonomous systems.

You will work with distributed systems, ML pipelines, and storage solutions while collaborating with cross-functional teams. The role emphasizes end-to-end ownership, reliability, and performance improvements in production environments, with in-office