Staff Motion Planning Software Engineer
Compensation
$230k – $270k /yr
Employment type
Full-time
Work setting
On-site
Location
South San Francisco, CA
Schedule
Day shift
Posted
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Job overview
The Staff Motion Planning Software Engineer role is onsite in South San Francisco, CA, and pays $230,000–$270,000 annually as a starting cash range. The role supports Zipline’s Autonomy Motion Planning team. Zipline operates an autonomous drone delivery system for food, medicine, and other essential goods. The engineer develops real-time decision-making and trajectory-planning software for autonomous flight, balancing safety, energy, time, and reliability while extending the autonomy stack and validating performance through simulation and fleet data.
What you'll do
- Build real-time trajectory generation and decision-making for autonomous flight
- optimize safety, energy, time, and reliability
- plan in uncertain environments
- develop safety-critical obstacle-avoidance software
- extend autonomy systems for aircraft and payloads
- validate through simulation, SIL/HIL, log replay, and fault injection
- analyze fleet data to improve safety metrics and address failure modes.
What we're looking for
- Skills & competencies
- staff software engineermotion planningsouth san francisco caziplineautonomous flightdrone deliverytrajectory planningdecision-makingsafety-critical softwarerustc++$230k–$270k annuallysimulation and hil
- Work arrangement
- Weekend coverage required
Benefits & perks
- The total compensation package may include equity, discretionary annual or performance bonuses, sales incentives, medical, dental, and vision insurance, and paid time off.
Why this role
Staff-level autonomy role shaping motion-planning approaches and future architectures for a large-scale drone delivery system.
About the employer
Zipline is hiring for this role. Industry: Custom Computer Programming Services. Sector: 54.
Additional details
- Industry sector
- 54
- Industry
- Custom Computer Programming Services
- Occupation code
- 15-1252.00
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Listing ID: 4349de0c-f756-4bf0-9c2c-7b00074b8988