Waymo is an autonomous driving technology company creating a new way forward in mobility.
Technical Specialist, ML Data
Location
United States
Posted
17 days ago
Salary
$159K - $202K / year
Seniority
Mid Level
Job Description
Technical Specialist, ML Data
Waymo
Role Description As a Program Manager in the Labeling Data Program Org, you will be the operational backbone of our machine learning initiatives. You will own and drive the complex, cross-functional programs that deliver high-quality data—the lifeblood of our models. This is a high-impact role for a technical, detail-oriented leader who thrives on turning ambiguous data needs into tangible, scalable solutions. - Drive the ML Flywheel: Lead the end-to-end lifecycle of ML data, from initial mining and curation to labeling policy definition, validation, and model evaluation. Work cross-functionally to ensure coordination and alignment on objectives and key results. - Translate Policy to Code: Lead the development of sophisticated labeling policies for complex AV domains (e.g., behavior prediction, long-tail edge cases). Convert ambiguous ML quality problems into precise, scalable annotation policies and data taxonomies. - Build Evals & Metrics: Design and implement ML evaluation frameworks. Identify key data-centric drivers of model performance and create the metrics that track ML quality at the data level. - Cross-Functional Leadership: Communicate effectively with technical and non-technical audiences at various levels of seniority, including producing analytical write-ups, dashboards, and data visualizations to convey your findings and recommendations to our team and cross-functional stakeholders. - Influence ML data selection strategies (active learning, hard-mining) to ensure we are labeling the most impactful data to maximize ROI from the labeling effort. Qualifications - 8+ years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. - Deep understanding of the ML data lifecycle: labeling, taxonomy design, quality control, and data curation. - Experience with ML Data Flywheel and working understanding of ML development life cycle (e.g., model deployment, model evaluation, data processing, debugging, fine-tuning). - Background in leading and managing complex programs that span across organizations and functions, with specific experience in Machine Learning data annotation or Human-in-the-Loop initiatives. - Strong ability to thrive in a dynamic environment, demonstrating comfort and effectiveness when dealing with ambiguity. - Ability to quickly learn and implement new concepts and utilize proprietary tools. Strong understanding of driving rules and regulations. Requirements - Experience with scripting language, machine learning tools, techniques and systems (including prompt engineering and fine-tuning LLMs) is a strong plus. - Demonstrated ability to extract, manipulate, and apply machine learning techniques to high volumes of critical, product-related data. - Demonstrated ability in working with a variety of engineering stakeholders to gather requirements, explain models, and iterate to make improvements. - Excellent written and verbal communication and ability to describe technical implementations or analyses to a non-tech audience in an effective manner. - Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment. - A greater focus on using your subject matter expertise for results analysis and direct customer consultation in the development of new and improved solutions. Benefits - Waymo employees are eligible to participate in Waymo’s discretionary annual bonus program. - Equity incentive plan. - Generous Company benefits program, subject to eligibility requirements. Salary Range The expected base salary range for this full-time position across US locations is $159,000 — $202,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level.
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