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Localization and Place Recognition DL Research Engineer

Sber • Russian: C1 • LLM & Generative AI • Cloud Platforms (IaaS & PaaS) • Python • C++ • Bash • 6 days ago
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Location
In office (Moscow)

Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 18, 2026. Sber scores A on the Alion truth index.

Overview
Company
Impact
Profile match

Sber

Sber is Russia's largest bank and the centre of one of the country's biggest technology ecosystems, tracing its origins to savings institutions established in 1841. It serves over a hundred million retail customers and several million businesses through branch, mobile and web channels, and holds a dominant share of the national deposit, lending and payment markets. Over the past decade the group has built out an ecosystem well beyond banking, spanning e-commerce, food delivery, streaming media, cloud infrastructure, devices and the GigaChat family of large language models developed by its own AI research teams.
sber.ru • HQ: Moscow, Russia • Cloud Platforms (IaaS & PaaS) • LLM & Generative AI • Investment Banking & M&A Advisory • Wealth Management & Financial Advisors • Commercial & Retail Banks • 5000+ employees • Est. 1841
Tech stack of Sber
Backed by Sber500

Будете подбирать и внедрять алгоритмы Global Pose Estimation - чтобы робот ориентировался в пространстве после включения или потери трекинга, indoor и outdoor.

Обязанности

Чем предстоит заниматься:

  • мультимодальный indoor/outdoor модуль локализации: Place Recognition, Pose Estimation, kidnapping problem, map optimization (images/point clouds/odometry).
  • эксперименты и гипотезы
  • автотюнинг гиперпараметров (Optuna)
  • сбор данных из симуляции и реальных датасетов
  • метрики качества, баланс скорость/ресурсы/качество
  • документирование, CI/CD, Docker
  • тестирование через TILT на роботах
  • участие в архитектуре системы.

Требования

Кого ищем:

  • разбираетесь в современных нейросетевых архитектурах, горите разработкой, ресёчем, математикой, робототехникой
  • уверенный Python (PEP - не догма, SOLID, ООП, без лишних for), умеете читать и править C++
  • умеете превращать статьи в гипотезы → эксперименты → результат для команды
  • математика на уровне «вспомню и применю»
  • наш стек: Linux, Git, Bash, Docker, ROS2; numpy, scipy, opencv, cupy, pytorch, ONNX, TensorRT, pcl, eigen
  • будет плюсом: опыт в Place Recognition/SLAM/Sensor Calibration/Legged Robots, статьи, Factor Graph, работа с сенсорами, работа c Nvidia Jetson, AI-агенты и context engineering, ROS2, Jetson, k3s

Условия

  • офисный формат в Москве (Автозаводская 23а к2)
  • ежегодный пересмотр зарплаты и годовая премия
  • расширенный ДМС и льготное страхование для семьи
  • уникальная система обучения Сбера для профессионального и карьерного развития
  • выгодная ипотека для сотрудников
  • подписка Прайм с возможностью совместного использования на трёх близких
  • вознаграждение за рекомендацию друзей в команду Сбера
  • корпоративная пенсионная программа.
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