Senior Simulation Platform Architect (Cloud AI)

Booster; Austin, Northern (TX, KY); Hybrid; USD 180,000 - 230,000; Full time

Job summary

Apptronik seeks a Staff Software Architect for the Core Simulation Platform to own the architecture of the fast, scalable simulation stack used for RL training and policy validation.

You will define abstractions, APIs, and platform standards, partnering with domain experts in physics, robotics, and ML to scale millions of experiences daily. This role emphasizes distributed systems, performance and cloud-native design in a robotics context.

Qualifications

• 7+ years of software engineering, including architecture/leadership on complex systems.
• Bachelor's/Master's/PhD in CS, Engineering, or related field (or equivalent).
• Strong track record architecting distributed, high-throughput, or real-time software systems.
• Experience with cloud platforms (AWS, GCP, Azure) and distributed frameworks.
• Proficiency in CI/CD, automated testing, and code quality practices.
• Comfort translating physics, robotics, and ML needs into system design.

Responsibilities

• Own the architecture of the core simulation platform — distributed systems for policy training and validation.
• Build cloud-native pipelines to scale millions of experience hours per day.
• Define core abstractions and APIs to accommodate new physics, sensors, and rendering capabilities.
• Set direction on performance, reliability, and scalability of a large system.
• Drive platform roadmap and review designs to reduce RL and perception iteration time.
• Collaborate with Controls, AI Research, and Perception leadership to align platform needs.
• Mentor engineers on system design and architectural trade-offs.

Skills

C++

Python

Distributed systems

Cloud platforms

CI/CD

Performance optimization

Leadership/architecture

Education

Bachelor's/Master's/PhD in CS or Engineering

Tools

Isaac Lab

MuJoCo

Ray

Kubernetes

AWS

GCP

Azure

Job description

Apptronik seeks a Staff Software Architect for the Core Simulation Platform to own the architecture of the fast, scalable simulation stack used for RL training and policy validation.

You will define abstractions, APIs, and platform standards, partnering with domain experts in physics, robotics, and ML to scale millions of experiences daily. This role emphasizes distributed systems, performance and cloud-native design in a robotics context.