ML-инженер в команду разработки робота доставки

Расширенная медицинская страховка начинает работать с первого месяца в Яндексе. В неё входят: В Яндексе есть всё, чтобы постоянно развиваться и учиться новому: Мы любим спорт и считаем его важной частью хорошего самочувствия каждого яндексоида. Поэтому у нас есть: Enhanced medical insurance begins from your first month at Yandex. It covers health care services at clinics and hospitals, whether for emergency care, surgeries, routine visits in your home country or abroad, medical tests and diagnostics, dental care, accident insurance, etc. At Yandex, we have everything you need for continuous growth and learning: an internal educational platform, mentoring, and programs for both beginners and experienced leaders. At Yandex's big offices, we have our own fully equipped gyms. There, you can work out independently or with a trainer. We love sports and consider it an important part of every Yandex employee's well-being. That's why we have: В подразделении автономного транспорта мы создаём и масштабируем решения, которые работают в реальном физическом мире и интегрированы в сложные логистические и операционные процессы. Внутри подразделения рободоставки запускается новое техническое направление, позволяющее качественно расширить возможность роботов доставки и их функционал. Расширение функционала требует решения существенно новых задач, разработки новых технологических подходов почти во всех областях автономного транспорта: архитектуре, ключевых алгоритмах восприятия, локализации и планирования, а также в логистике и эксплуатации. Мы ищем сильного разработчика в команду, которая пройдёт путь от первых прототипов до сформировавшегося продукта. * Разрабатывали ML-алгоритмы от сбора данных до эксплуатации в продукте * Имеете широкий кругозор в методах ML, в особенности в областях робототехники (локализация, планирование маршрута, распознавание) * Имеете опыт профилирования и адаптации нейросетевых алгоритмов под платформы с ограниченной вычислительной мощностью (квантизация, прунинг, Transfer Learning) * Умеете работать в команде * Ответственны и организованны * Знаете классические методы ML: методы агрегирования (бустинг, бэггинг), машины опорных и релевантных векторов (SVM, RVM), методы условной и выпуклой оптимизации 1:"$Sreact.fragment" 3:I[91373,[],""] 4:I[28825,[],""] 13:I[59536,["5144","static/chunks/5144-ab34660025cf6f7f.js?dpl=5_22_2","3467","static/chunks/3467-[contact omitted]b1673.js?dpl=5_22_2","4219","static/chunks/app/global-error-23401ec313d1fac8.js?dpl=5_22_2"],"default"] 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