About this role
The autonomous driving team at Waymo is developing the Waymo Driver to improve transportation access and enhance road safety across various vehicle platforms. This position functions as the operational backbone for the Labeling Policy Program in Hyderabad, where the specialist translates complex machine learning data needs into scalable labeling policies.
Day-to-day work involves accelerating Behavior ML velocity through rapid policy iteration, creating golden datasets, and guiding vendor labeling teams to ensure high data quality. The role suits an execution-focused professional with strong attention to detail who excels at bringing clarity and operational efficiency to machine learning data workflows.
What you will do
- Collaborate with machine learning engineers to translate ambiguous model requirements into precise, actionable labeling policies.
- Execute rapid policy iterations and create small-scale golden datasets to establish quality baselines before full-scale deployment.
- Direct vendor labeling experts by providing technical guidance to keep active queues running smoothly against safety and performance goals.
- Analyze long-tail edge cases and coordinate with regional specialists to incorporate local driving rules and nuances.
- Monitor labeling pipelines, conduct targeted technical analyses, and build automated tools to spot data quality trends and workflow improvements.
- Serve as the main technical interface between requesters and operations to manage policy amendments and resolve complex escalations.
What you need
- Six or more years of professional experience in data analysis, operations, or program management focused on machine learning data annotation, taxonomy design, or human-in-the-loop workflows.
- Demonstrated ability to work independently on operational workflows and manage small sub-working groups or vendor squads.
- Practical knowledge of dataset curation, labeling pipelines, data quality control metrics, and baseline model evaluation concepts.
- Experience conducting technical data analyses using pre-established tools or simple automation scripts to diagnose pipeline issues and track vendor quality.
- Comfort operating in a dynamic environment while translating vague technical needs into clear documentation with high attention to detail.
Nice to have
- Experience with scripting languages such as Python or SQL, or basic automation techniques for parsing high volumes of data.
- Demonstrated ability to extract, manipulate, and apply machine learning techniques to product-related data.
- Track record of working with engineering stakeholders to gather requirements, explain models, and iterate on improvements.
- Prior experience working across multiple geographic locations and managing vendor-hosted operations.
- Strong problem-solving and critical thinking skills suited for a changing environment.
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Company benefits program
Skills and tech stack
Questions candidates ask
What is the salary range for this role?
The expected base salary range for this full-time position is ₹3,000,000 to ₹3,570,000 INR. Actual starting pay depends on job-related factors including exact work location, experience, relevant training, education, and skill level.
Where is the position located?
This role is based in Hyderabad, India, serving as the operational backbone of the Labeling Policy Program in the region.
What kind of background is required for this position?
Candidates need six or more years of experience in data analysis, operations, or program management with a focus on machine learning data annotation, taxonomy design, or human-in-the-loop workflows.