Autonomous Vehicle Software Engineers design and implement the algorithms that allow cars, trucks, and shuttles to sense their environment, make decisions, and navigate without constant human input. Their work spans sensor fusion (cameras, LiDAR, radar), computer vision, machine learning-based perception, path planning, and real-time control systems. They collaborate closely with hardware engineers, data scientists, and safety validation teams to ensure the vehicle behaves reliably across countless real-world scenarios.
| Entry level | $105,000 |
| Median | $155,000 |
| Senior | $210,000 |
| Top 10% | $290,000 |
| Job growth | +23% |
| Professionals in the USA | 0.08 million |
| Typical hours/week | 45 hrs |
| Remote work share | 25% |
| Annual job openings | 6,500/yr |
| Demand | High |
AI is a core tool and subject matter of this career rather than a replacement for it, since AV engineers build the very systems that automate driving. Demand remains strong as companies need skilled engineers to design, train, and validate perception, prediction, and planning models. Routine coding tasks are increasingly assisted by AI copilots, shifting engineers toward higher-level system design and safety validation.
Automation exposure: AI coding assistants can automate boilerplate code generation, unit test creation, data labeling, simulation scenario generation, and some debugging tasks.
The human edge: Humans remain essential for safety-critical decision-making, ethical judgment in edge cases, systems-level architecture design, regulatory compliance, and integrating hardware-software tradeoffs that require real-world contextual reasoning.
Figures are estimates for exploration — verify current data with BLS.gov.