Job Overview
Location
South San Francisco - Hybrid
Job Type
Full-time
Category
Software Engineering
Date Posted
June 4, 2026
Full Job Description
đź“‹ Description
- • Serve as the senior-most individual contributor in the Autonomy organization, with deepest technical ownership of Perception, Prediction, and/or Planning modules, and cross-stack influence across the entire autonomy system.
- • Own the design and evolution of the perception stack, including detection, classification, tracking, and multi-modal sensor fusion across all available modalities, ensuring robustness across the long tail of real-world operating conditions.
- • Define the strategic direction for deep learning application within the perception pipeline, determining where and how neural networks deliver the greatest value in safety-critical scenarios.
- • Lead the development of the prediction stack, designing models for intent inference, behavior forecasting, and handling occlusions and edge cases unique to ground service equipment (GSE) operations.
- • Establish how prediction integrates upstream with perception and downstream with planning, ensuring coherent data flow and decision-making across the autonomy stack.
- • Design the planning and decision-making stack, from structured driving behaviors to domain-specific maneuvers required for autonomous ground service equipment in airport environments.
- • Determine where learned components are appropriate within the planner, balancing rule-based systems with data-driven approaches for safety and reliability.
- • Set technical direction at the interfaces between your primary autonomy module and adjacent systems, partnering with other senior engineers to maintain end-to-end system coherence.
- • Own the functional and software architecture of the autonomy stack, collaborating with neighboring teams to ensure seamless implementation and integration.
- • Write or review production-grade C++ and Python code that other senior engineers trust and extend, with strict adherence to safety-critical software standards.
- • Apply modern deep learning practices in autonomy, including practical realities of model training, evaluation, deployment, and lifecycle management in real-world environments.
- • Work with ROS / ROS 2 and navigate distributed-systems challenges on-vehicle, including real-time constraints, inter-process communication (IPC), and fault containment.
- • Maintain a strong bias for execution: convert ambiguity into actionable plans and deliver running code on physical vehicles, not just simulations or prototypes.
- • Ship autonomy components that have operated at non-trivial scale in production on real vehicles, with demonstrable impact on commercial operations.
- • Mentor and guide staff and senior engineers without direct managerial authority, setting technical standards and direction that the team follows.
- • Operate within an Operational Design Domain (ODD) involving heavy human interaction, mixed traffic, and unstructured environments — specifically airport ground handling operations.
- • Contribute to simulation-driven verification and integrate simulation into CI/CD pipelines for autonomy validation and regression testing.
🎯 Requirements
- • 15+ years of hands-on experience building production autonomy systems with technical depth across multiple modules (localization, perception, prediction, planning, controls)
- • Demonstrated track record of shipping autonomy components that have run in production on real vehicles at non-trivial scale
- • Prior experience as the most senior individual contributor in an autonomy organization, setting technical direction without managing a team
- • Deepest technical depth in perception, prediction, or planning (ideally more than one)
- • Strong software engineering fundamentals in C++ and Python, with experience writing safety-relevant code
- • Fluency with modern deep learning for autonomy, including training, evaluation, deployment, and lifecycle management in real-world conditions
🏖️ Benefits
- • Opportunity to work in a real, commercially viable Operational Design Domain (airports) with a concrete path to removing safety drivers
- • Senior autonomy IC role with cross-stack influence and technical leadership across Perception, Prediction, and Planning
- • Defined path to scale — work on a commercial deployment with a clear roadmap to fleet expansion
- • Collaborate with top-tier venture-backed aviation and autonomous driving investors
Skills & Technologies
Python
REST
Senior
Hybrid
About AeroVect Inc.
AeroVect Inc. builds autonomous ground vehicles and management software for airport cargo and baggage handling. Its electric tractors and tow-tugs automate loading, unloading, and transport of luggage and freight on tarmacs and in terminals, integrating with existing baggage systems and aircraft operations. The company combines AI perception, path planning, and fleet orchestration to reduce delays, labor costs, and emissions while improving ramp safety and throughput for airlines and ground-handling partners.
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