Senior Manager Data Operations & Annotations, Autonomy Data

Zipline; South San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Zipline, the world’s largest drone delivery service, is seeking a leader to build and scale data operations for ML and autonomy. You will shape how real-world data is collected, annotated, validated, and delivered, while aligning with engineering, ML, and field operations.

This role spans data engineering, operations, and governance. You will develop managers, establish ownership, and drive programs that improve quality, coverage, speed, and cost as Zipline grows its autonomous logistics

Qualifications

• Experience leading operational or technical teams.
• Experience owning technically complex operational systems and improving their performance at scale.
• Strong systems thinking across people, process, hardware, software, and infrastructure.

Responsibilities

• Lead the organization and end-to-end operations for high-quality data collection, annotation, validation, and delivery.
• Partner with ML and autonomy teams to translate model needs into data requirements and strategies.
• Design and improve annotation, validation, and quality-control workflows with tooling and automation.
• Develop managers and teams, establish clear ownership, and foster accountability and continuous improvement.
• Lead cross-functional programs and drive decisions across operations, engineering, ML, and autonomy.
• Identify bottlenecks with data insights and drive automation to scale without proportional cost.

Skills

Leadership

People management

Cross-functional

Data operations

Automation

Tools

SQL

Python

Job description

About Zipline

Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products.

Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.

About You and the Role

You will lead the team responsible for turning real-world data into high-quality, cost-effective datasets for Zipline’s machine learning and autonomy teams.

This role spans field operations, autonomy, ML, engineering, and data infrastructure. You will set the strategy for how data is collected, annotated, and validated, while building an operation that continuously improves its quality, coverage, speed, and economics.

You will also lead and develop the organization behind these systems, while partnering closely with technical teams to ensure data operations evolve with the needs of our autonomy stack.

What You’ll Do

• Lead the organization and end-to-end operations that collect, annotate, validate, and deliver high-quality real-world data at the scale, speed, and cost required for ML and autonomy development.

• Partner with ML and autonomy teams to translate model needs into data requirements, collection strategies, and operational priorities.

• Design and improve annotation, validation, and quality-control workflows, using tooling, automation, and metrics to optimize quality, coverage, speed, and cost.

• Develop managers and teams, establish clear ownership, and build a culture of accountability and continuous improvement.

• Lead cross-functional programs and drive decisions across operations, engineering, ML, and autonomy.

• Use operational data and feedback to identify bottlenecks and drive automation or engineering improvements that increase scale without proportional growth in manual effort or cost.

What You’ll Bring

• Experience leading and scaling operational or technical teams, including developing managers.

• Experience owning technically complex operational systems and improving their performance at scale.

• Strong systems thinking and technical judgment across people, process, hardware, software, and infrastructure.

• Experience leading ambiguous, cross-functional work from problem definition through sustained operation.

• Strong judgment in balancing quality, throughput, cost, and reliability.

• A track record of using metrics, tooling, and automation to drive measurable operational improvements.

• Clear communication and the ability to drive alignment and decisions across technical and operational teams.

What Will Make You Stand Out

• Experience designing or operating large-scale data labeling or annotation programs.

• Experience managing external vendors or distributed workforces supporting data operations.

• Experience with machine learning, autonomy, robotics, aerospace, or other sensor-rich physical systems.

• Familiarity with the ML data lifecycle, including data collection, sampling, annotation, validation, dataset generation, and model feedback loops.

• Experience translating model performance gaps into targeted real-world data collection.

• Familiarity with multimodal datasets, sensor data, telemetry, or logging systems.

What Success Looks Like

The right data reaches ML teams faster, at higher quality and lower cost. Data collection becomes increasingly deliberate, annotation and processing scale efficiently, and model needs translate quickly into action in the field.Ultimately, you will own a critical part of how Zipline learns from the real world.

What Else You Need To Know

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit,

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Zipline ’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.