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- 298 000 $ – 378 000 $
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Tech Lead Manager ML Optimization
Waymo — лидер в области автономного вождения, предлагающий работу над передовыми технологиями с очень высокой компенсацией. Позиция сочетает в себе влияние на продукт мирового уровня и работу с новейшим оборудованием (TPU следующего поколения).
Сложность вакансии
Роль требует исключительного сочетания навыков управления командой (10+ человек) и глубокой технической экспертизы в оптимизации ML-моделей на уровне ядер (kernels) и аппаратного обеспечения. Высокая планка в 10+ лет опыта и работа с SOTA архитектурами делают эту позицию крайне сложной.
Анализ зарплаты
Предлагаемый диапазон $298k–$378k является очень конкурентоспособным для уровня Tech Lead Manager в Кремниевой долине, соответствуя верхним границам рынка для Tier-1 компаний.
Сопроводительное письмо
I am writing to express my strong interest in the Tech Lead Manager, ML Optimization position at Waymo. With over a decade of experience in software engineering and a deep specialization in ML infrastructure, I have consistently delivered high-performance solutions for large-scale models. My background in optimizing complex architectures like Diffusion and Transformers, combined with hands-on experience in hardware-software co-design for TPUs and low-latency environments, aligns perfectly with Waymo's mission to build the world's most experienced driver.
In my previous roles, I have successfully led cross-functional teams to bridge the gap between research and production, ensuring that state-of-the-art models are not only innovative but also computationally efficient. I am particularly drawn to Waymo's commitment to scale and efficiency, and I am eager to apply my expertise in roofline analysis and custom-kernel development to enhance the performance of the Waymo Driver. I am confident that my technical leadership and experience in managing high-performing engineering teams will contribute significantly to the ML Infrastructure team's success.
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Описание вакансии
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
The Waymo ML Infrastructure team accelerates Waymo’s mission, by building the best ecosystem for sustainably innovating and shipping ML powered intelligence.
Research, Production, and the Hardware teams are our primary stakeholders and our work powers the development of the state of the art models in the areas of Perception and Trajectory planning that are core to our autonomous driving software. We enable our partners by offering the best in class solutions for the entire model development lifecycle. These solutions include understanding the model business goals and platform hardware characteristics, and codesign the models for the hardwares. These solutions are developed in close collaboration with teams at different modeling teams. Scale and efficiency are core tenets our infra follows.
We are looking for an experienced senior TLM to join our team. In this critical role, you will lead the development and enable efficient deployment for large-scale machine learning models using state of the art advanced AI infrastructure. You will work cross functionally at the intersection of data engineering, model development, and Datacenter + on-device low-latency deployments, ensuring seamless integration across teams and technologies to power efficient innovation.
You will
Take ownership of improving model efficiency on different platforms and drive the model system codesign practice that meet both technical and business requirements. You will work with cutting-edge ML models that may consist of multiple billions of parameters, and apply your expertise in model optimizations and advanced algorithms toward efficient execution and deliver results on multiple hardware compute platforms.
The key responsibilities for this role include:
- Technical Leadership: Proactively study the SOTA model architectures and optimizations from the community and Google, for World Models, Diffusion + flow matching techniques, and translate them into measurable technical deliverables in Waymo’s onboard driving stack.
- Performance Analysis: Dev tooling innovation for model performance inspector in highly distributed training/inference setups, apply roofline analysis, understand the efficiency headrooms and drive work groups to deliver the optimizations and meet the system requirements.
- Strong Execution: Innovate high performance optimizations and tools for various models and large-scale training/inference including on future next-gen TPUs and low-bit precision training/inference setup, and ensure all system components align towards achieving high performance and goodput goals.
- Cross-Team Leadership: Guide efforts across multiple teams and organizations to ensure seamless integration of data generation, model development, and deployment pipelines.
- Mentorship & Management: Act as a mentor to junior engineers, helping to grow their technical expertise and foster a culture of collaboration and engineering excellence. Manage the IC performance for a medium size team of ~10 engineers.
You Have
- 10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, training, deploying, and optimizing large-scale machine learning systems.
- Experienced using ML accelerator profiling tools to uncover performance bottlenecks.
- Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, JAX, or similar frameworks.
- Deep understanding of state-of-the-art machine learning models and architectures such as autoregressive and diffusion transformers and familiarity with custom-kernels for diverse h/w compute based efficiency.
- Strong leadership skills with experience navigating cross-functional teams and providing technical leadership projects across multiple organizations.
- Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience.
- A Master’s or PhD in Computer Science, Engineering, or a related field is preferred.
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range
$298,000—$378,000 USD
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Навыки
- C++
- Python
- PyTorch
- JAX
- Diffusion Models
- Transformers
- TensorFlow
- Machine Learning Infrastructure
- Performance Analysis
- Distributed Training
- DeepSpeed
- Model Optimization
- TPU
Возможные вопросы на собеседовании
Проверка понимания аппаратных ограничений и умения оптимизировать производительность.
Расскажите о вашем опыте использования Roofline-анализа для выявления узких мест в производительности ML-моделей. Какие конкретные оптимизации вы внедряли на основе этих данных?
Оценка навыков работы с современными архитектурами, упомянутыми в вакансии.
Какие основные сложности возникают при оптимизации Diffusion-моделей и авторегрессионных трансформеров для инференса с низкой задержкой на специализированных ускорителях (TPU/GPU)?
Проверка опыта управления и разрешения конфликтов в кросс-функциональных проектах.
Опишите ситуацию, когда требования команды исследователей (Research) конфликтовали с ограничениями аппаратной платформы. Как вы, как TLM, нашли компромисс?
Оценка технических знаний в области квантования и точности вычислений.
Каков ваш опыт внедрения low-bit precision (например, INT8 или FP8) для обучения или инференса? С какими проблемами деградации точности вы сталкивались и как их решали?
Проверка лидерских качеств и развития талантов.
Как вы подходите к управлению производительностью команды из 10 инженеров и как помогаете старшим специалистам расти до уровня экспертов?
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- Страна
- США
- Зарплата
- 298 000 $ – 378 000 $