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Sunday is developing personal robots to reclaim time lost to repetitive household tasks, with a mission to make generalized robots broadly accessible. The company has spent 18 months building a talented team, securing capital, and validating its technology, and is now scaling into the next growth phase.
You will join the Data team as Technical Program Manager for the Data Engine, owning the project management side of either data annotation or data collection operations. This role bridges Machine Learning, Software Engineering, and Data teams to design and roll out tasks to data operators that deliver high-quality, high-quantity, and diverse datasets.
Key responsibilities include:
- Owning task creation and ontology design for data annotation/collection
- Managing the project side of data annotation or collection workflows
- Creating and maintaining documentation for processes and guidelines
- Hands-on participation: annotating data yourself when new designs are being tested
- Designing and implementing data annotation or collection processes
- Ensuring data operators are aligned with annotation/collection guidance
- Coordinating with ML and engineering teams to ensure they receive the data needed for successful experiments
You will need strong written and verbal communication skills to guide data operators, the ability to manage unexpected challenges, and ownership mentality across key stakeholder relationships (operators, engineering, support). You should be excited about AI data growth, adept at prioritizing competing requests, able to move quickly while staying organized, and maintain a balance between high standards and treating people well. An intermediate-level understanding of machine learning is required.
Nice-to-have qualifications include previous experience as a strategic projects lead or data program manager at AI labs or data vendors, technical skills to build data annotation/collection tools, and ability to leverage AI to improve productivity.
Requirements:
- Clear written and verbal communication
- Ability to manage unexpected challenges and competing priorities
- Ownership mentality with data operators, engineering, and support teams
- Intermediate-level understanding of machine learning
- Excitement for AI data growth and development
- Ability to move quickly and stay organized
- Hands-on willingness to annotate data and work in the weeds
