ML Data Operations Engineer

Quick Facts

• Role: ML Data Operations Engineer

• Focus: Internal ML data collection studies to support consumer machine learning features

Description

The ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts powering next-generation consumer machine learning features. In this role, you will work closely with ML scientists and engineers, taking ownership of the hands-on bring-up, execution, and quality oversight of internal data collection studies in a cross-functional environment.

Responsibilities

• Plan, execute, and track internal ML data collection studies with researchers, engineers, and scientists

• Learn the ML experiments you support, including objectives, data requirements, labeling, and evaluation criteria

• Bring up and maintain pre-release hardware and software platforms for data collection, troubleshooting and triaging issues

• Create and maintain technical documentation for platform setup, study protocols, and data handling procedures

• Manage day-to-day logistics for study sessions (scheduling participants, configuring setups, ensuring smooth session flow)

• Coordinate with algorithm, infrastructure, and hardware/software teams to gather and validate data collection requirements

• Track and communicate progress, blockers, participant throughput, and dataset status to cross-functional partners and stakeholders

• Identify workflow gaps and define, document, and socialize process improvements

Requirements

• Bachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent combination of education and relevant experience

• Experience supporting or executing human user studies, behavioral research, or data collection operations

• Track record partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications

Benefits

Opportunity to help deliver next-generation consumer ML features by enabling high-quality internal datasets through hands-on technical operations.