Престижная роль в мировом лидере беспилотного вождения с фокусом на передовые VLM-модели и доступом к уникальным массивам данных.
Передовой стек
Трендовый домен
Огромный потенциал
Понятный scope
?Ориентир по зарплате
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Machine Learning Engineer (Perception LLM/VLM): Developing and optimizing large-scale continual pre-training pipelines for cutting-edge VLM foundation models with an accent on multimodal data integration and autonomous driving perception. Focus on designing novel pre-training techniques, evaluating model performance at scale, and translating research into production-ready systems for the Waymo Driver.
Location: Must be based in Mountain View or San Francisco, California
Salary: $170,000–$216,000 USD
Company
Waymo is an autonomous driving technology company dedicated to building the world's most trusted driver to improve mobility and safety.
What you will do
Design, implement, and optimize large-scale continual pre-training pipelines for VLM foundation models.
Conduct research on novel pre-training techniques to integrate diverse, multimodal sensor data.
Develop and evaluate metrics for measuring foundation model performance in autonomous driving contexts.
Collaborate with downstream teams on system integration and optimization for onboard and offboard hardware.
Translate cutting-edge research in LLMs, VLMs, and continual learning into production-ready systems.
Requirements
5+ years of experience in Machine Learning with a focus on large-scale foundation models.
Proven expertise in LLM/VLM pre-training and continual learning with large datasets.
Strong coding proficiency in Python and deep learning frameworks like Jax, TensorFlow, or PyTorch.
Hands-on experience with model training, evaluation, and deployment in production environments.
Master's degree in Computer Science, Electrical Engineering, or a related field.
Nice to have
Experience in fine-tuning foundation models for autonomous driving or robotics.
Background in autonomous vehicle perception, motion planning, or decision-making.
PhD in a relevant field.
Publications in top-tier ML or computer vision conferences (e.g., NeurIPS, CVPR).
Culture & Benefits
Participation in a discretionary annual bonus program.
Equity incentive plan eligibility.
Comprehensive company benefits program.
Opportunity to work with millions of miles of real-world driving data.
Collaborative environment with research teams at Alphabet.
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