Вакансии

Location: Москва Мы — core-команда, которая отвечает за ML для понимания аудио во всем Сбере. За последний год мы выложили в open source SOTA-модель для распознавания речи на русском языке — **GigaAM**, а прошлой весной первыми в России запустили **нативное понимание звука в LLM — GigaChat Audio**. Сейчас мы активно улучшаем мультимодальные возможности GigaChat: работаем над качеством на сложных аудио- и визуальных контекстах и учим модель понимать видео не только по звуковому потоку, но и по кадрам. **Цель** — совместное обучение на vision+audio и video+audio диалогах длительностью 90+ минут. _Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика вам на почту и в чат на платформе HeadHunter придет приглашение пройти первичное интервью с ГигаРекрутером в Telegram. Диалог займёт примерно 10 минут. Его задача — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. ГигаРекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным!_ Обязанности * Проводить эксперименты по обучению Vision / Audio / Video LLM: данные, стадии обучения, способы смешивания модальностей * Оптимизировать ML-инфраструктуру для обучения на длинных мультимодальных контекстах * Формулировать и проверять гипотезы о том, как улучшать качество LLM на видео. Требования * Сильный опыт в DL-инженерии, желательно в обучении LLM-моделей * Глубокое знание PyTorch, включая DDP / FSDP * Понимание distributed training и efficient deep learning: DP / TP / PP / EP / SP, mixed precision, checkpointing, offloading, профилирование и оптимизация обучения * Понимание архитектуры LLM: Transformer, attention (MHA / GQA / MLA), RoPE и другие позиционные эмбеддинги, long context, MoE * Уверенный Python на уровне production-кода: asyncio, multiprocessing, профилирование, отладка больших систем. **Будет плюсом:** * Опыт обучения мультимодальных LLM * Опыт снижения стоимости контекста при обработке видео * Опыт расширения контекста LLM * Понимание RL-подходов для обучения моделей: RLHF / RLVR, PPO / GRPO / DPO * Опыт построения бенчмарков с использованием LLM-as-a-judge. Условия * крупнейшее DS&AI community — более 600 DS-специалистов банка * дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира * возможность быть соавтором НИРов и статей для международных конференций * возможность выбрать удобный формат работы: гибрид или офис * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека выгоднее до 7% для каждого сотрудника * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Мы ищем сильного Deep Learning инженера для развития и вывода на принципиально новый уровень GigaAM — лучшей open-source модели для распознавания речи на русском языке. GigaAM — это не только исследовательский проект, но и core-модель, которая определяет качество работы многих ключевых продуктов экосистемы: GigaChat Audio, ASR, TTS, GigaChat Video и других. Сейчас мы стоим перед масштабным вызовом: кратное увеличение параметров модели, масштабирование данных на несколько порядков, расширение языкового покрытия и выход за рамки распознавания речи в сторону general audio understanding. Если вы хотите создавать state-of-the-art решения, которыми будут пользоваться миллионы, и вносить вклад в развитие мирового open-source — нам по пути! _Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика вам на почту и в чат на платформе HeadHunter придет приглашение пройти первичное интервью с ГигаРекрутером в Telegram. Диалог займёт примерно 10 минут. Его задача — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. ГигаРекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным!_ Обязанности * Масштабирование данных: увеличение объемов данных для обучения на несколько порядков, построение эффективных пайплайнов их фильтрации и подготовки. * Развитие архитектуры и метода предобучения: улучшение мультиязычных свойств модели и расширение ее возможностей в сторону анализа аудио неречевой природы. * Scaling laws: масштабирование модели по количеству параметров в несколько раз. * Research & Engineering: стабилизация процессов предобучения, проведение ML-экспериментов, проверка гипотез и доведение результатов до прода и публикаций. Требования * Уверенное владение Python и PyTorch * Distributed Training: практический опыт распределенного обучения, понимание ограничений и принципов работы под капотом (DDP, FSDP, ZeRO). * Опыт оптимизации DL-пайплайнов: профилирование и оптимизация узких инфраструктурных мест в процессе обучения (I/O bottlenecks, memory management, GPU utilization). * Экспертиза в Speech/Audio: понимание современных подходов и state-of-the-art архитектур в Speech/Audio Self-Supervised Learning. Условия * крупнейшее DS&AI community — более 600 DS-специалистов банка * дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира * возможность быть соавтором НИРов и статей для международных конференций * возможность выбрать удобный формат работы: гибрид или офис * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека выгоднее до 7% для каждого сотрудника * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Мы ищем Data Engineer, который будет отвечать за инфраструктуру, пайплайны и качество данных для обучения современных Vision-Language Models. Роль находится на стыке data engineering и ML: нужно будет работать с большими мультимодальными датасетами, понимать потребности исследователей и ML-инженеров, строить пайплайны очистки, фильтрации, категоризации и генерации данных, а также обеспечивать воспроизводимый экспорт данных в формат для обучения моделей. Обязанности * Собирать и структурировать потребности ML-команды в данных: какие данные нужны для обучения, дообучения, оценки и улучшения VLM. * Предлагать и реализовывать идеи пайплайнов очистки, фильтрации, дедупликации, категоризации и генерации данных. * Ориентироваться в современных практиках построения датасетов для Vision-Language Models: image-text pairs, synthetic data, filtering, quality scoring, data mixture design, dataset versioning. * Отвечать за инфраструктуру хранения и подготовки данных, включая: * 1. импорт данных из различных источников: production, Common Crawl, open-source datasets, generated data; 2. валидацию и контроль качества данных; 3. хранение и версионирование датасетов; 4. экспорт данных в форматы, пригодные для обучения моделей. * Проектировать и реализовывать пайплайны обработки данных на большом масштабе, включая десятки миллиардов изображений. * Разрабатывать пайплайны генерации синтетических данных для обучения и улучшения VLM. * Собирать статистику по данным, строить отчёты и визуализации для анализа состава, качества и покрытия датасетов. * Обеспечивать воспроизводимость, наблюдаемость и надёжность data-процессов. * Работать в тесной связке с ML-инженерами, исследователями и инфраструктурной командой. Требования * Сильный опыт в data engineering и построении production-grade data pipelines. * Уверенное владение Python, включая multiprocessing, multithreading и async-подходы. * Опыт работы с большими объёмами данных и распределённой обработкой. * Практический опыт с объектными хранилищами, в частности S3 или аналогами. * Опыт работы с YTsaurus или похожими системами для распределённого хранения и обработки данных. * Понимание принципов валидации, очистки, дедупликации и версионирования датасетов. * Опыт работы с DVC, Git, Docker. * Опыт работы с PostgreSQL или другими реляционными базами данных. * Умение проектировать устойчивые пайплайны: от импорта данных до финального экспорта в training-ready формат. * Способность самостоятельно разбираться в нечетко сформулированных задачах и доводить их до работающего решения. * Готовность работать на стыке engineering и ML research. Будет плюсом ------------ * Опыт работы с мультимодальными данными: изображения, текст, image-text pairs, captions, OCR, metadata. * Понимание того, как устроены современные датасеты для обучения VLM / LMM / multimodal models. * Опыт построения пайплайнов для synthetic data generation. * Опыт реализации quality scoring, filtering, semantic deduplication, clustering или data attribution. * Опыт визуализации статистики по большим датасетам и построения внутренних аналитических дашбордов. * Опыт работы с Common Crawl, LAION-подобными датасетами, open-source vision-language datasets. * Базовое понимание ML training pipeline и того, как качество данных влияет на качество модели. Условия * крупнейшее DS&AI community — более 600 DS-специалистов банка * дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира * возможность быть соавтором НИРов и статей для международных конференций * возможность выбрать удобный формат работы: гибрид или офис * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека выгоднее до 7% для каждого сотрудника * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Привет! Это GigaChat Vision — команда, которая делает полный цикл обучения VLM-моделей. Ищем сильного senior-инженера в RL-направление: человека, который будет драйвить ключевые исследования и разработки, влиять на качество моделей и доводить сложные идеи до работающих решений. _Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика вам на почту и в чат на платформе HeadHunter придет приглашение пройти первичное интервью с ГигаРекрутером в Telegram. Диалог займёт примерно 10 минут. Его задача — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. ГигаРекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным!_ Обязанности * Разрабатывать и улучшать RL-подходы для обучения VLM/LLM-моделей: выбор алгоритмов, постановка экспериментов и анализ результатов; * Проектировать reward-функции и пайплайны обучения, выстраивать стратегии масштабирования под разные домены и сценарии, напрямую влияя на метрики качества; * Определять требования к данным для RL: участвовать в построении пайплайнов сбора, фильтрации и подготовки датасетов; * Развивать систему оценки reasoning-качества: внедрять и улучшать метрики в существующем eval-фреймворке, предлагать новые способы измерения качества под новые возможности модели; * Работать на стыке с Pretrain / SFT / Infra: обеспечивать согласованность решений и перенос экспериментов в продакшн-пайплайн; * Следить за состоянием области и переводить свежие идеи из статей в проверяемые эксперименты и инженерные решения; * Глубоко погружаться в технические задачи: дебажить эксперименты, разбирать аномалии в обучении, находить узкие места и доводить решения до результата; * Делиться экспертизой с командой: участвовать в код-ревью, помогать улучшать качество решений и подходы к экспериментам; * Развивать инфраструктуру для RL. Требования * Глубокое понимание RL для LLM/VLM (RLHF, GRPO, PPO) и практический опыт; * Понимание полного цикла обучения VLM/LLM (pretrain → SFT → RL) и того, как решения на каждом этапе влияют на финальные метрики; * Опыт с распределённым обучением (DeepSpeed, FSDP) и inference-фреймворками. * Сильный практический опыт постановки, проведения и анализа RL-экспериментов; * Умение работать в условиях неопределённости и самостоятельно двигать сложные технические задачи; * Умение выстраивать процессы в условиях неопределённости; * Опыт взаимодействия со смежными командами и стейкхолдерами; * Системное мышление: способность видеть картину целиком — от данных и reward-дизайна до eval и продакшн-метрик. **Будет плюсом:** * Опыт менторинга или технического лидерства в рамках отдельных проектов; * Публикации или open-source вклад в области RL/LLM/VLM; * Опыт вывода RL-обученных моделей в продакшн и поддержки их качества. Условия * крупнейшее DS&AI community — более 600 DS-специалистов банка * дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира * возможность быть соавтором НИРов и статей для международных конференций * возможность выбрать удобный формат работы: гибрид или офис * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека выгоднее до 7% для каждого сотрудника * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Привет! Это GigaChat Vision — команда, которая делает полный цикл обучения VLM моделей, включающий в себя стадии pre-training, SFT и DPO/RL. Мы ищем сильных инженеров и исследователей, которые будут двигать вперед качество мультимодального GigaChat. _Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика вам на почту и в чат на платформе HeadHunter придет приглашение пройти первичное интервью с ГигаРекрутером в Telegram. Диалог займёт примерно 10 минут. Его задача — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. ГигаРекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным!_ Обязанности * Самостоятельная работа в рамках заданного направления развития качества VLM: от планирования, до выкатки в прод; * Планирование и работа над исследовательскими задачами по архитектуре модели, стратегии и данным обучения; * Формирование гипотез по улучшению качества модели, самостоятельное планирование экспериментов по их подтверждению и постановка multi-node обучений на большом количестве GPU (тысячи A100/H100); * Решение сложных инженерных задач, развитие и оптимизация кодовой базы обучения и эвала VLM, написание чистого кода и проведение code review; * Анализ точек роста и определение способов их закрытия. Требования * Сильный технический бэкграунд в modern ML: понимание того, как данные, архитектура и стратегии обучения влияют на итоговое качество модели; * Опыт полного цикла обучения VLM или LLM; * Глубокие знания или опыт работы в области computer vision; * Понимание принципов работы распределенного обучения (FSDP) или опыт обучения моделей на больших GPU кластерах; * Наличие навыков технического лидерства: проведение code-review, помощь и менторинг младших сотрудников; * Умение работать, принимать решения и выстраивать процессы в условиях неопределенности; * Умение и желание взаимодействовать с коллегами, вносить собственные идеи и предлагать пути достижения общих целей. **Будет плюсом:** * Опыт полного цикла обучения VLM; * Наличие публикаций в области NLP или CV; * Опыт решения задач по оптимизации обучения; * Опыт участия в соревнованиях по машинному обучению или программированию. Условия * крупнейшее DS&AI community — более 600 DS-специалистов банка * дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира * возможность быть соавтором НИРов и статей для международных конференций * возможность выбрать удобный формат работы: гибрид или офис * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека выгоднее до 7% для каждого сотрудника * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: San Francisco, California Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE Notion is building the operating system for knowledge work, and we want people to be able to do substantive knowledge work from their phone. A great native app is what makes that possible. On Android, that means Notion should feel like it was built for the platform: fast to open, smooth to scroll, and reliable offline or on a spotty connection. We’re investing in a more native foundation for how people read, write, and edit in Notion. That lets users capture ideas in the moment, find answers across their workspace, manage tasks and projects, and work with teammates, with the speed, polish, and dependability people expect from the best apps on their phone. As an Android engineer, you’ll help build that native foundation, from how pages render and how people write and edit, to the navigation and app chrome people use every day, like Home, Search, and Inbox, along with the shared frameworks the rest of the app is built on. You’ll work across the Android stack, with chances to dig into our shared Rust layer and the AI tools we use for mobile development. Along the way, you’ll pair with experienced product and mobile AI engineers to find what slows the team down, try new Android capabilities, and help decide what ships in the app. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. WHAT YOU'LL ACHIEVE - Ship the core Notion experience on Android: Build and polish the surfaces people use every day—opening and reading pages, writing and editing, navigating the app, and the Home, Search, and Inbox tabs—on a native Kotlin and Jetpack Compose stack that is fast to open, smooth to scroll, and dependable offline. - Build with product and design, and iterate fast: Partner with product managers and designers to turn ideas into shipped features, then use feedback and data to make them better. Use AI coding tools and agents to build, test, and investigate faster, while you stay accountable for review, validation, and quality. - By the end of your first year, own a core product area: Take a core part of the Android app, like Home, Inbox, or a piece of the editor, from idea to launch, and shape it into an experience that helps people do their life’s work from their phone. - Make the app feel fast and reliable: Find and fix issues in startup time, scrolling, typing latency, crashes, and memory use across the surfaces you own, and add the tests and monitoring that catch regressions before users do.   SKILLS YOU'LL NEED TO BRING - Solid Android fundamentals: You’ve built and shipped Android apps, through work, internships, or your own projects, and you’re comfortable with modern Android—Kotlin, Jetpack Compose, Coroutines/Flow, and Gradle. Experience with a large, modular codebase is a plus. - Care for native UI and performance: You enjoy making UI feel fast and smooth, and you’re curious about things like custom text rendering, complex lazy lists, or rich-text editing. Experience with performance profiling, realtime collaboration, or offline sync is a plus. - Product instincts: You care about how the app feels to use, not just how it works. You sweat the details of interactions and polish, and you use feedback and data to decide what to build next. - Thoughtful problem-solving and clear communication: You build a clear picture of the problem before jumping to a fix, you can explain trade-offs in writing, and you ask for help early when you’re stuck. Experience moving a hybrid or web-based surface to native, or building something from 0→1, is a plus. - AI-native, end-to-end engineering practice: You use AI tools and agents as real collaborators, framing tasks clearly, reviewing generated changes, testing behavior, and designing workflows that make the broader team more effective. Web experience (TypeScript, React, Node) is welcome but not required. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco, the estimated base salary range for this role is $150,000 - $168,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy https://notion.notion.site/Notion-Global-Recruiting-Privacy-Policy-fc3eb4e829354a26a2bb6fd5e289b550. https://dev.notion.so/a3ce416456924276a59de91bca740028?pvs=21   #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Responsibilities Design and develop scalable backend services and APIs. Drive architecture decisions and ensure high engineering standards.

3+ years of professional AI/ML Engineering experience. Strong Python, SQL, NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow.

Оплачиваемое тестовое задание. Выплаты 2 раза в месяц (криптовалюта или карта). Старт работы через 2 недели.

Location: San Francisco Perplexity is continuing to rapidly scale our Enterprise Engineering Organization and seeking Engineering Managers with deep expertise across the Enterprise domain to help lead the next wave of growth. As an Enterprise Engineering Manager, you will combine technical judgment, product intuition, and people leadership to help large organizations adopt AI at scale. We are hiring across the enterprise control plane, enterprise data plane, and connector marketplace and activation. Depending on your area of focus, you will lead and grow a team in one of these areas, addressing challenges such as: Enterprise Control Plane: Building the identity, security, and governance foundations that enable large organizations to deploy Perplexity confidently, including SSO, SCIM, role-based access, customer-managed encryption keys (BYOK), admin APIs, and enforceable policies governing access to data, models, and tools. Supporting regulated-industry requirements, including SOC 2, HIPAA, data governance, and residency, with audit logs and analytics that give administrators visibility into how Perplexity is used. Enterprise Data Plane: Building the connector platform and semantic data layer that give Computer reliable, permission-aware access to enterprise systems and knowledge, including managed authorization, private-system access, and data freshness. Connector Marketplace and Activation: Building discovery, recommendations, onboarding, and marketplace experiences that help customers find and adopt integrations, while working with partners to expand the connector ecosystem. Across these areas, you will translate enterprise customer needs into scalable technical solutions across Perplexity’s products. RESPONSIBILITIES - Set technical direction for your team and guide architecture decisions across the enterprise platform. - Build the foundational systems that enable large organizations to deploy Perplexity broadly and confidently. - Shape roadmaps with product and design, applying strong technical judgment and product intuition. - Set a high bar for reliability, code quality, testing, and maintenance. Lead incident response and ensure platform changes and connector migrations are rolled out safely. - Partner with engineering teams across the company to ensure the platforms we build are extensible and easy to adopt. - Represent engineering in strategic enterprise customer conversations, partnering with sales and customer success to understand requirements and remove barriers to adoption. - Oversee hiring, onboarding, and mentorship for a rapidly growing team. Develop rigorous interview pipelines and work closely with recruiting to source candidates. - Work with Perplexity’s co-founders to deliver enterprise engineering priorities. QUALIFICATIONS - Strong technical judgment and experience building enterprise platforms or products, with an understanding of the reliability, security, and usability requirements of enterprise customers. - Domain expertise in at least one of the following areas: - Enterprise control plane: identity and access management, SSO/SCIM, role-based access, key management, admin APIs, policy enforcement, audit logging, data governance, or compliance and residency requirements for regulated industries. - Enterprise data plane: connector and integration platforms, including authentication, source-system permissions, data synchronization, and reliability at scale; or semantic data layers and knowledge platforms that make enterprise data accessible and useful to AI. - Connector marketplace and activation: discovery and recommendation systems, integration onboarding, marketplace product UX, or technology partner ecosystems. - Ability to deliver in a fast-moving environment while balancing customer needs, technical quality, and long-term maintainability. - Detail-oriented and quality-focused - our customers run critical workflows on Perplexity, and our product needs to stay robust and reliable. - Ability to translate enterprise customer needs into clear technical priorities and communicate tradeoffs effectively. - Experience building and managing high-performing engineering teams, with a strong management practice grounded in clear feedback, effective 1:1s, career development, and recruiting and retaining high-caliber talent. - Ability to lead parallel technical initiatives, align strong technical perspectives, and make clear prioritization and tradeoff decisions. - Experience with AI/ML products, enterprise AI adoption, or scaling enterprise platforms at a startup is a plus. - 8+ years of engineering experience, with at least 4 of those years as an engineering manager.

What you'll be working on: Participating in the development and improvement of recommendation systems, including user-item, item-item, and cross-platform recommendations. Optimizing recommendations on category, channel, and tag pages.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. As a Senior RF Engineer on the WHOOP Hardware team, you will support the development, integration, validation, and delivery of the wireless systems that power WHOOP's wearable products. Working closely with Electrical, Firmware, Mechanical, Manufacturing, and Product teams, you will independently drive RF development and validation activities from early prototypes through production. WHOOP products rely on highly integrated wireless systems operating within compact and challenging wearable form factors. You will bring strong hands-on RF test and debugging experience to characterize system performance, identify root causes of wireless issues, develop robust validation methodologies, and ensure designs meet performance, regulatory, and manufacturing requirements.   RESPONSIBILITIES - Own RF system characterization, validation, and debugging from early prototypes through production. - Define validation plans, test methods, and acceptance criteria for conducted, radiated, and system-level wireless performance. - Characterize transmitter, receiver, antenna, coexistence, interference, desense, and OTA performance, including return loss, antenna efficiency, TRP/TIS, and on-body performance as applicable. - Develop repeatable test setups, fixtures, scripts, and automated measurement methods to improve validation coverage, efficiency, and data quality. - Analyze RF performance data, identify failure modes and root causes, and drive corrective actions with Electrical, Firmware, Mechanical, and Manufacturing teams. - Guide RF-critical schematic and PCB design, including matching networks, grounding, shielding, routing, component selection, and antenna integration. - Apply RF circuit, electromagnetic, and system analysis using tools such as CST, HFSS, MATLAB, Python, or similar tools. - Establish production test methods, limits, and correlation studies while supporting manufacturing troubleshooting and wireless regulatory certification. - Advance next-generation RF architectures, antenna technologies, validation methods, and manufacturing techniques while communicating technical risks and recommendations across engineering teams. - Travel up to 15%, domestically and internationally. QUALIFICATIONS - BS or higher in Electrical Engineering or related field. - 5+ years of relevant RF or wireless engineering experience. - Demonstrated expertise in RF system characterization, validation, debugging, and root-cause analysis. - Background in conducted and radiated wireless testing, including transmitter performance, receiver sensitivity, antenna performance, coexistence, and desense. - Hands-on proficiency with RF lab equipment, including spectrum analyzers, signal generators, VNAs, oscilloscopes, wireless communication testers, and calibration tools. - Familiarity with antenna and OTA measurements, including return loss, efficiency, radiation performance, TRP, and TIS. - Strong command of RF and electrical engineering principles, including impedance matching, transmission lines, circuit design, PCB layout, grounding, shielding, and antenna integration. - Working knowledge of RF test automation, data analysis, or electromagnetic simulation using tools such as Python, MATLAB, LabVIEW, CST, or HFSS. - Excellent communication skills, with experience supporting product validation, manufacturing, and wireless regulatory certification. - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibilityThe WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $140,000 - $195,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile industry. Helix is our flagship Ad-Network team of around 60 top-tier engineers and data scientists spanning backend, mobile SDKs, data engineering, infrastructure, and AI. Helix has evolved beyond powering Voodoo's own gaming portfolio—our technology is now directly integrated into games from external, third-party publishers worldwide. Operating across millions of third-party devices in real-time bidding environments creates unique technical challenges around SDK performance, ultra-low latency, and intelligent automation. Within Helix, you’ll join the AdExperience squad—a focused team of Senior Product Managers, QA/Release Engineers, and five exceptional Senior Engineers specialized in backend and mobile SDK development. Together, you will push the boundaries of iOS SDK architecture and champion modern, agentic AI workflows to set new industry standards. ROLE We’re looking for a visionary and talented Senior iOS Engineer to join our dynamic, passionate, and committed to excellence team at the forefront of advertising technology! As a Senior iOS Engineer, you will drive the development of cutting-edge SDKs, influencing the experience of millions of users across diverse devices. A pivotal member of our engineering team, you will help shape the direction of our iOS technical efforts while serving as a high-impact, hands-on individual contributor. - Technical Vision & Code Standards: Guide the technical direction for our iOS projects. Drive innovation, establish architectural best practices, and ensure the highest standards of code craftsmanship across our codebase. - AI Usage & Agentic Workflows: Raise the bar in AI adoption across the team—actively integrating agentic workflows, LLMs, and AI-driven automation tools to solve complex challenges and elevate developer productivity. - Code Excellence: Craft robust, maintainable, and high-performance code that sets industry benchmarks as a senior hands-on individual contributor. - Collaborative Code Reviews: Actively participate in thorough code reviews, fostering a culture of continuous technical improvement and knowledge sharing within the engineering team. - Architectural Decisions: Make critical decisions regarding the architecture and technical stack of our iOS SDKs and applications to ensure long-term stability and scalability. - Quality Assurance: Guarantee the enduring quality and reliability of our iOS projects through rigorous testing, performance profiling, and continuous integration practices. PROFILE - 6/7+ years of experience in mobile software development. - 5 years minimum in Swift. - Strong proficiency and proactive mindset towards leveraging AI technologies (e.g., agentic AI, LLMs, AI coding assistants) to enhance software development efficiency and code quality. - Excellent problem-solving, critical thinking, and communication skills. - Demonstrated ability to make critical technical decisions independently. - Extensive experience in writing robust, maintainable, and high-performance Swift code. - Writing efficient unit tests, integration tests, and UI tests. - In-depth knowledge of iOS development tools, frameworks (SwiftUI, Combine, and CoreData), and best practices (MVVM, Protocols, Delegates). - Excellent level of spoken English. NICE TO HAVE - Previous experience in the AdTech industry or in mobile ads integration. - Experience with SDK development and a deep understanding of the challenges and opportunities in this space. - Experience in Objective-C, Kotlin, Node. - Practical experience setting up or customizing AI developer agents and automated AI workflows. - Experience in optimizing App performance, reducing memory footprint, and decreasing package size. - Experience in deploying iOS frameworks on CocoaPods. - Experience in deploying iOS applications with CircleCI and Fastlane. - Working knowledge of remote APIs, concurrency, layouts, transitions, animations. OUR STACK ⧫ Xcode ⧫ Swift ⧫ Objective-C ⧫ SwiftUI ⧫ Combine ⧫ CoreData ⧫ GitHub ⧫ CocoaPods ⧫ CircleCI ⧫ AWS ⧫ AI Coding Tools & Agentic Workflows BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office - Remote Fridays

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote Little more about the team: The Storage Team at Honeycomb is the backbone of our platform, responsible for the performance, reliability, and scalability of storing and querying billions of events. We design and own the architecture that powers correct and dependable query results — enabling every product experience from Metrics to Triggers and SLOs. As a senior engineer on Storage, you’ll work on high-impact systems where our customers may never see your code directly, but they’ll rely on it every time they use Honeycomb. What you’ll do in the role: Build and deliver high-quality solutions. You will design and implement solutions that power Honeycomb’s query and data storage infrastructure. Whether it’s improving query performance, evolving the Retriever service, or making our storage layer more reliable, you’re eager to jump in and add value where the team needs it most. Scope and deliver projects independently. You’re comfortable breaking down complex storage and querying problems into achievable steps, surfacing trade-offs, and pulling in teammates when needed. You take ownership end-to-end — from design to production support — reducing toil and ensuring our systems deliver measurable customer and business impact. Collaborate with cross-functional partners. You’ll work closely with Product Management and other engineering teams to connect technical solutions to product needs, from problem discovery through solution design and delivery. Much of our work is behind the scenes, but it enables every Honeycomb product experience, from Metrics to Triggers and SLOs. Support our services in production. We believe in owning the software we build. Every engineer on Storage participates in on-call rotations, helps define team KPIs and SLOs, and proactively reduces toil by addressing reliability challenges before they reach customers. Learn new ways to solve complex problems. As Honeycomb grows, so do the challenges of scaling our systems. You will explore new technologies, data storage techniques, and query optimization strategies to keep performance and reliability strong at scale. Thrive on collaboration. You enjoy pairing, reviewing code, and offering constructive feedback. You model strong ownership and help your teammates grow, while keeping conversations forward-looking and focused on business value. What you’ll bring to the role: Technical leadership in storage and querying. You’ve led the design of patterns and guidelines that improve performance and reliability, and you bring expertise in writing Go along with experience working on high-throughput or complex systems. Prior experience with database engineering is a plus, as is comfort with Kubernetes. Curiosity and experimentation. You learn by digging in — individually, in pairs, or as a team. You ask questions to better understand complex systems, explore trade-offs, and believe in learning from incidents as a way to improve both technology and practices. Focus on business outcomes. You tie technical decisions to customer and company impact, weighing whether work is necessary now or later, and considering how projects affect the broader business. Strength in mentorship and teamwork. You guide engineers through code reviews and help spread knowledge across a team with diverse skillsets so that ownership of critical paths is shared, not siloed. Resilience in collaboration. You thrive in a senior-heavy team, giving and receiving feedback with grace, and contributing to a culture where tough problems and hard conversations lead to better outcomes. Execution with impact. You can scope and deliver complex, multi-team projects while balancing production realities, proactively reducing toil, and ensuring systems deliver measurable customer value. Deep debugging expertise. You’re trusted to diagnose and resolve the toughest production issues across the stack, restoring reliability where others may be stuck. Influence beyond your team. You multiply impact by sharing knowledge, guiding adoption of new technologies, and driving foundational work that benefits Honeycomb engineering as a whole. Base Salary based on level of experience $250,000 — $280,000 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Задачи: — Администрировать и поддерживать телефонию на базе Asterisk — Настраивать dialplan, SIP trunks, endpoints и маршрутизацию звонков — Подключать и управлять SIP-провайдерами — Поддерживать входящие и исходящие звонки — Интегрировать Asterisk с backend-системами через ARI / AMI и CRM — Диагностировать SIP/RTP-трафик и проблемы с качеством связи — Работать с Asterisk Realtime и MariaDB/MySQL — Управлять CDR и записями звонков — Мониторить инфраструктуру и самостоятельно устранять инциденты Требования: — 2+ года практического опыта с Asterisk — Уверенное знание SIP, VoIP, NAT, RTP, codecs — Практический опыт работы с ARI и/или AMI — Уверенное администрирование Linux — Опыт работы с MariaDB/MySQL и базовые знания SQL — Опыт с firewall, fail2ban и VoIP security — Умение самостоятельно диагностировать и решать проблемы телефонии — Будет плюсом: Redis, Nginx, monitoring tools Условия: — Полностью удалённая работа — $3000 fixed / month — График: Пн–Пт, 09:00–18:00 (UTC+3) — 1 час на обед + 3 перерыва по 15 минут — Формат работы — онлайн-офис

Требования: — Высшее образование (бакалавр, BE/B.Tech) со специализацией в области электротехники (VLSI, микроэлектроника и смежные направления) — Опыт работы от 0 до 2 лет

О вакансии Мы ищем высококвалифицированных специалистов по Machine Learning для участия в проекте по обучению AI-моделей. Работа включает разработку и обучение моделей, системы инференса, численные вычисления, оптимизацию производительности и программирование на Python.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Every time Claude runs code, uses a computer, or works as an agent, it does so inside a sandbox. Our Sandboxing team builds the isolation layer behind that work. The same systems run the code Claude writes for users, the environments we train and evaluate models in, and the agents our customers deploy. These workloads are untrusted by design, and there are a lot of them. Sandboxes need to start in milliseconds, hold up under adversarial code, and scale to a very large number of concurrent sessions. You will work at the boundary between the Linux kernel, virtualization, and the container ecosystem. You will partner with research, product, and security teams to make sure that safe and fast do not trade off against each other. Key responsibilities Design, build, and operate the sandboxing infrastructure that runs untrusted, model-generated code and agent workloads at scale Improve sandbox startup time, density, and throughput, including snapshot and restore, checkpointing, and warm pools Strengthen isolation across compute, filesystem, and network, including egress controls and per-session credential handling Investigate and fix performance, reliability, and security issues at the kernel, hypervisor, and container runtime level Build the monitoring, tracing, and debugging tools that show where time and resources go inside a sandbox Work with researchers to support reinforcement learning environments and evaluations that need fast, reproducible, isolated execution Work with product and platform engineers to expose sandboxes as a dependable, well-designed capability for Claude products and customers Partner with security teams to threat-model the platform and to test, harden, and respond to escape and abuse scenarios Work with cloud providers on the hardware and platform features that our workloads depend on Share knowledge on systems programming and Linux internals, and help set technical standards for the team Minimum qualifications Software engineering experience in Linux systems programming, kernel development, or another low-level area Strong programming skills in at least one systems language such as Rust, C, C++, or Go Working knowledge of virtualization or container isolation technologies such as KVM, QEMU, Firecracker, gVisor, or runc Understanding of Linux resource management, including namespaces, cgroups, scheduling, and memory management Experience profiling and debugging performance issues at the system level Ability to work in unfamiliar codebases and technical areas, and to ship practical solutions with measurable results Strong communication skills and a commitment to building safe, reliable systems Preferred qualifications Experience building or operating a multi-tenant sandbox, serverless, or code execution platform Experience with microVMs, user-space kernels, or lightweight virtualization, including snapshot and restore Experience with OS-level security hardening, including seccomp, LSMs, and threat modeling of untrusted code Experience with eBPF and kernel tracing tools Experience with Kubernetes and cloud infrastructure at scale (AWS, GCP) Experience with network isolation, high-performance networking, or building egress proxies and policy layers Experience with sandboxes for AI agents, computer use, or reinforcement learning environments Experience with GPU virtualization, accelerators, or performance work on machine learning workloads Prior experience as a technical lead or mentor Representative projects Cutting sandbox cold start from seconds to milliseconds with snapshot-based restore and pre-warmed pools Designing a network egress policy layer so agents can reach approved services without exposing secrets Running many thousands of parallel reinforcement learning environments with strong isolation between them Building tracing tools that attribute latency and resource use inside a running sandbox Reducing per-sandbox memory overhead to raise density on each host Hardening the runtime against escape attempts found in internal red-team exercises The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.