Manager, Data Operations and Annotations

🕒 September 1

🚗 Michigan – Remote

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💵 $150k - $180k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

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👻 Ghost score 4%

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Logo of Zipline

Zipline

1001 - 5000 employees

Founded 2014

🍽️ Food & Beverage

📣 Marketing

✈️ Travel

💰 $330M Series F on 2023-04

Food & Beverage • Marketing • Travel

Zipline is a leading provider of autonomous drone delivery services, revolutionizing logistics for various sectors including healthcare, restaurants, and retail. Their innovative technology allows for rapid and emission-free deliveries, significantly reducing the time required to transport goods such as food, medical supplies, and everyday essentials. Since their inception, Zipline has completed over a million deliveries across multiple countries, showcasing their commitment to improving delivery experiences and enhancing access to critical supplies.

📋 Description

• 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. • Own a critical part of how Zipline learns from the real world.

🎯 Requirements

• 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. • 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.

🏖️ Benefits

• Equity compensation • Overtime pay • Discretionary annual or performance bonuses • Sales incentives • Medical, dental and vision insurance • Paid time off

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