Senior Software Engineer, Autonomy Simulation & Validation

Zipline•South San Francisco, CA

1d•$180,000 - $260,000

About The Position

Zipline is seeking a deeply technical software engineer for its Autonomy Validation team. The team builds infrastructure, tools, and frameworks for validating software across the Autonomy organization, including planning, perception, control, and other decision-making logic for autonomous aircraft. Because Zipline’s autonomy stack is custom-built, this role develops internal platforms that enable simulation at scale and rigorous scenario testing so autonomy engineers can ship with confidence. This is a foundational software engineering role, not a QA position, and its systems will shape how autonomy is tested, verified, and deployed safely. The engineer will build and own validation infrastructure, simulation tools, and scenario-generation capabilities; create tools that integrate with the internal autonomy development stack; and provide scalable, reliable automation for running, tracking, and analyzing validation tasks. The role collaborates with autonomy, systems, data, flight-test, and QA teams to define evaluation approaches, codify metrics and safety thresholds, connect real-world results to test tools and CI, and establish release-validation practices. It also contributes documentation, standards, and workflows that scale across the organization.

Requirements

At least 5 years of experience building software systems for simulation, testing, or safety validation, ideally in robotics, autonomy, aerospace, or other real-time, safety-critical domains.
Strong software engineering skills and proficiency in C++, Rust, or C.
Hands-on experience building or working with simulation systems for robotics or autonomous systems, particularly for testing or validation.
Experience building tools, platforms, or infrastructure used by other engineers.
Understanding of validation methodologies, including defining metrics, evaluating system behavior, and testing complex electromechanical systems.

Nice To Haves

Python for tooling and scripting.
Experience with high-fidelity simulation or scenario-generation frameworks.
Experience with large-scale or distributed systems, such as cloud infrastructure, Kubernetes, or AWS.
Familiarity with systems engineering concepts, including requirements, safety constraints, and metrics.
Exposure to autonomy stacks, including planning, perception, and control.
Some exposure to machine-learning systems.

Responsibilities

Build and own infrastructure for validating autonomous features and system performance across planning, perception, and control.
Design and develop simulation tools and scenario generation for large-scale, high-fidelity testing under real-world and edge-case conditions.
Develop custom validation and testing tools for autonomy components that integrate with the internal autonomy development stack.
Create scalable, reliable, automated solutions for running, tracking, and analyzing thousands of validation tasks across the autonomy organization.
Collaborate with autonomy engineers to understand how system behavior should be evaluated.
Work with systems and data engineers to codify metrics, safety thresholds, and requirements in test infrastructure.
Collaborate with flight-test and QA teams to connect real-world results to test tools and CI loops.
Establish software release-validation best practices to help ensure the autonomy stack is safe, measurable, and production-ready.
Contribute to internal documentation, standards, and validation workflows that scale across the autonomy organization.
Define validation methodologies and metrics for evaluating new autonomy features in simulation.