Technical Specialist- ML Data

About this job

Waymo is an autonomous driving technology company dedicated to creating the world's most trusted driver to enhance mobility and save lives. Originating as the Google Self-Driving Car Project in 2009, the organization builds the Waymo Driver technology, which powers fully autonomous ride-hail services and various vehicle platforms. In this Technical Specialist role based in Hyderabad, you serve as the operational backbone for the Labeling Policy Program. Your main mission is to accelerate Behavior ML velocity by turning complex machine learning data requirements into consistent, high-quality, and scalable labeling policies. On a typical day, you will collaborate with machine learning engineers to understand data goals, create golden datasets for labeling queues, guide vendor labeling teams, analyze pipeline data quality, and handle edge cases or regional driving rules. This is a hands-on, execution-focused position that requires driving clarity and operational excellence in labeling workflows.

Responsibilities

• Translate ambiguous machine learning requirements from model owners into precise and actionable labeling policies.
• Execute rapid policy iterations and hand-craft golden datasets to establish quality baselines for new labeling queues.
• Provide technical guidance and operational direction to vendor labeling experts to ensure smooth workflow execution.
• Address long-tail edge cases and coordinate with regional specialists to incorporate local driving rules and nuances.
• Monitor labeling pipelines, analyze data quality trends, and build automated tools to improve overall workflows.
• Act as the primary technical interface between requesters and operations to manage policy amendments and resolve escalations.

Requirements

• 6+ years of experience in data analysis, operations, or program management focused on machine learning data annotation or taxonomy design.
• 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.
• Experience conducting technical data analyses using existing tools or building simple automation scripts to diagnose issues.
• Comfort working in a dynamic environment while translating vague technical needs into clear documentation with high attention to detail.

Good to have

• Experience with scripting languages such as Python or SQL for parsing high volumes of data.
• Ability to extract, manipulate, and apply machine learning techniques to product-related data.
• Experience collaborating with engineering stakeholders to gather requirements and explain models.
• Prior experience working across multiple geographic locations and managing vendor-hosted operations.

Who should apply

This role best suits experienced professionals with a solid background in data analysis, operations, or program management tied to machine learning workflows. Candidates who excel at turning vague instructions into structured operational policies, guiding vendor teams, and handling complex edge cases will find this position a great fit. Because 6+ years of specific professional experience is required, this role is not suitable for freshers.

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