Zipline

Embedded Software Engineer (Data Platform), Autonomy

South San Francisco, California, USAFull-TimeMid-levelSoftware Engineering

Skills

Rust C++AWS GCP Azure Linux Machine learning Documentation Ownership

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ABOUT ZIPLINE

Do you want to change the world? Zipline is on a mission to transform the way goods move. Our aim is to solve the world’s most urgent and complex access challenges by building, manufacturing and operating the first instant delivery and logistics system that serves all humans equally, wherever they are. From powering Rwanda’s national blood delivery network and Ghana’s COVID-19 vaccine distribution, to providing on-demand home delivery for Walmart, to enabling healthcare providers to bring care directly to U.S. homes, we are transforming the way things move for businesses, governments and consumers. The technology is complex but the idea is simple: a teleportation service that delivers what you need, when you need it. Through our technology that includes robotics and autonomy, we are decarbonizing delivery, decreasing road congestion, and reducing fossil fuel consumption and air pollution, while providing equitable access to billions of people and building a more resilient global supply chain.
Join Zipline and help us to make good on our promise to build an equitable and more resilient global supply chain for billions of people.

ABOUT THE ROLE

As an embedded software engineer on the Data Platform team at Zipline, you will be responsible for building the platform that enables our engineering teams to collect, process, and leverage data from our drone fleet. You will work at the intersection of embedded systems and data engineering, creating robust infrastructure that runs onboard our aircraft to handle the vast streams of telemetry, sensor, and operational data they generate.
Your work will focus on building reusable data processing primitives and tools that other engineering teams depend on—from autonomy engineers who need high-fidelity sensor data, to systems engineers who monitor fleet health, to data scientists who train the next generation of ML models. You will make critical architectural decisions about how data flows through our system, from collection on embedded hardware to cloud storage and beyond.
Our technical stack spans embedded Linux systems running Rust, microcontrollers with real-time firmware, and cloud-based data services. We are hiring for engineers who bring embedded systems expertise combined with strong data engineering fundamentals.

Build the Embedded Data Platform

Design and implement core data platform infrastructure that runs onboard our drone fleet, providing reliable APIs and tools for engineering teams to instrument their systems
Build high-performance data collection and processing pipelines on resource-constrained embedded Linux systems
Create reusable frameworks and platforms that make it easy for engineering teams to collect data vital to improving their systems
Design intelligent data management systems that prioritize critical telemetry data, efficiently process sensor data, and make real-time decisions about what data to store
Design data protocols and formats that enable seamless integration with cloud processing and ML pipelines

Optimize for Scale and Reliability

Optimize data pipelines for resource-constrained compute nodes and reduce the need for processing data offboard entirely
Implement onboard data retention policies that balance storage constraints with debugging and compliance requirements
Build monitoring and observability into the platform itself to detect issues, track usage patterns, and enable troubleshooting
Design systems that gracefully handle edge cases, network failures, and resource constraints while maintaining data integrity

Cross-Cutting Responsibilities

Work closely with avionics, autonomy, and systems engineers to understand data requirements and build platform features that serve their needs
Collaborate with backend data teams to ensure telemetry handoff meets requirements for fleet analytics, data processing, and model training
Develop tools for analyzing data flow characteristics, identifying bottlenecks, and troubleshooting platform issues
Build hardware-in-the-loop test infrastructure to validate the data platform under realistic conditions
Participate in and lead design reviews to ensure data observability and platform integration are considered in new features

WHAT YOU'LL BRING

We're looking for engineers with strong backend and data infrastructure experience who are excited to work closer to the hardware and embedded systems.

Required

5+ years of professional software engineering experience with strong proficiency in Rust or similar systems languages
Proven experience building backend services, APIs, and data infrastructure at scale, preferably with exposure to high-throughput data pipelines or streaming systems
Strong foundation in data systems architecture: serialization formats, message queues, distributed systems concepts, and real-time data processing
Experience designing platform infrastructure or developer tools that other engineering teams depend on, with clear APIs and comprehensive documentation
Track record of diagnosing and resolving complex technical issues in production: performance bottlenecks, race conditions, data inconsistencies, or system reliability problems
Demonstrated ability to learn new technical domains quickly and apply engineering principles to novel problem spaces
Strong technical communication skills with examples of design documents, RFCs, or technical proposals that influenced system architecture

Strongly Preferred

Experience with embedded Linux, IoT systems, edge computing, or other resource-constrained environments
Background in robotics, autonomous systems, hardware integration, or other domains bridging software and physical systems
Familiarity with real-time systems concepts, performance profiling, memory management, or low-level optimization
Experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code
Track record working on safety-critical, highly regulated, or mission-critical systems where reliability is paramount.

About the Role

Zipline operates the world’s largest autonomous logistics system (ground or air) — and in the coming year, we will be hyper-scaling from thousands to tens of thousands of carefully coordinated drone deliveries in several dense, dynamic U.S. metros. Our Autonomy Motion Planning team is looking for a Senior/Staff Software Engineer who is passionate about developing autonomous systems for the real world. This role will explore cutting-edge approaches to decision making and trajectory planning that will enable more accurate and timely deliveries, putting you in the position to make critical product decisions that will shape our future architectures.

What You'll Do

Build real-time trajectory generation and decision-making for autonomous flight (search-based, sampling, MPC, convex/non-convex optimization).
Design collision avoidance and large-scale multi-agent planning (fleet deconfliction, airspace rules, traffic management) that scales to 10,000+ flights/day.
Tackle joint optimization across safety, energy, time, and reliability—balancing mission goals with vehicle/airspace constraints.
Plan in uncertain environments with complex dynamics: chance-constraints, robustness to wind/turbulence, degraded sensors, and partial observability.
Extend the autonomy stack for new aircraft and payloads; define clean interfaces with perception and controls.
Prove it before flight: scenario libraries, SIL/HIL, large-scale sim, log replay, and fault-injection.
Mine real fleet data to validate safety metrics (separation, risk, intervention rate), improve models, and burn down long-tail failure modes.
Continuously reduce cost/latency (vectorization, warm starts, smart heuristics) while raising reliability.
Build real-time trajectory generation and decision-making for autonomous flight (search-based, sampling, MPC, convex/non-convex optimization).
Design collision avoidance and large-scale multi-agent planning (fleet deconfliction, airspace rules, traffic management) that scales to 10,000+ flights/day.
Tackle joint optimization across safety, energy, time, and reliability—balancing mission goals with vehicle/airspace constraints.
Plan in uncertain environments with complex dynamics: chance-constraints, robustness to wind/turbulence, degraded sensors, and partial observability.
Extend the autonomy stack for new aircraft and payloads; define clean interfaces with perception and controls.
Prove it before flight: scenario libraries, SIL/HIL, large-scale sim, log replay, and fault-injection.
Mine real fleet data to validate safety metrics (separation, risk, intervention rate), improve models, and burn down long-tail failure modes.
Continuously reduce cost/latency (vectorization, warm starts, smart heuristics) while raising reliability.

What You'll Bring

Master's degree in Computer Science or related field and 3+ years of experience building software for safety-critical systems (aerospace/AV/robotics/medical).
Strong in Rust/C++/C for real-time, fault-tolerant code on embedded/Linux.
Depth in planning & search (A*/ anytime / RRT*/sampling), trajectory optimization/MPC, or multi-agent deconfliction—shipped on real robots/vehicles.
Hands-on with simulation at scale, SIL/HIL, log replay, and metrics-driven validation.
Evidence of shipping production-grade autonomy through ambiguous, noisy conditions—owning the last mile to reliability.
Systems thinker who collaborates tightly with perception, controls, and flight ops; crisp docs and design reviews.
Strong in Rust/C++/C for real-time, fault-tolerant code on embedded/Linux.
Depth in planning & search (A*/ anytime / RRT*/sampling), trajectory optimization/MPC, or multi-agent deconfliction—shipped on real robots/vehicles.
Hands-on with simulation at scale, SIL/HIL, log replay, and metrics-driven validation.
Evidence of shipping production-grade autonomy through ambiguous, noisy conditions—owning the last mile to reliability.
Systems thinker who collaborates tightly with perception, controls, and flight ops; crisp docs and design reviews.

Why Join Now?

Impact at scale: Your planner won’t benchmark in isolation—it will fly thousands of missions/day delivering essential goods.
Technical frontier: Real-time multi-agent autonomy, joint optimization, and robustness under uncertainty at a scale few have seen.
Ownership: High-leverage IC role—your decisions shape Zipline’s flight stack and the behavior of a global fleet.
Category leadership: Help define the standard for safe, reliable autonomous flight in the real world.
Impact at scale: Your planner won’t benchmark in isolation—it will fly thousands of missions/day delivering essential goods.
Technical frontier: Real-time multi-agent autonomy, joint optimization, and robustness under uncertainty at a scale few have seen.
Ownership: High-leverage IC role—your decisions shape Zipline’s flight stack and the behavior of a global fleet.
Category leadership: Help define the standard for safe, reliable autonomous flight in the real world.