Вакансии

Talablar: — Frontend dasturlash (HTML, CSS, JavaScript va zamonaviy frameworklar) bo‘yicha puxta bilim — Ravon nutqqa ega bo‘lgan — Uyatchang bo'lmagan — Boshqalarga bilimini erkin o'rgata oladigan — Bolalar bilan ishlashni yoqtiruvchi Ish turi: 9:00-18:00, offline 6/1

Обязанности: — Разработка и поддержка автотестов. — Поддержка и развитие тестового фреймворка. — Работа с Jenkins. — Работа с Git. — Работа с Apache Kafka. — Работа с SQL. — Работа с Selenide / Selenium. — Работа с DevTools. — Анализ и чтение логов. — Исследование и анализ возникающих проблем. — Оперативная поддержка и актуализация автотестов и тестового фреймворка. Требования: — Знание Java / Kotlin и принципов ООП. — Знание и понимание работы с коллекциями: List, Map, Set; потокобезопасные коллекции — как плюс. — Знание принципов SOLID. — Знание Maven. — Знание JUnit 4/5. — Знание теории тестирования и техник тест-дизайна. — Умение работать с DevTools и снифферами. — Умение читать и анализировать логи, работать с Kibana, Grafana. — Понимание жизненного цикла разработки ПО. — Понимание клиент-серверной архитектуры. — Знание протокола HTTP. — Умение работать с тестовой документацией. — Гибкость, коммуникативность, дружелюбие, стрессоустойчивость, самостоятельность. Условия и преимущества: — Белая зарплата, трудоустройство по ТК РФ; — 31 день оплачиваемого отпуска в год; — ИПР – Индивидуальный план развития для каждого сотрудника; — Активная корпоративная культура с Online и Offline мероприятиями; — Добровольный ДМС (50% оплата от компании); — Корпоративные внутренние курсы: автоматизация тестирования на Java, нагрузочное тестирование; — Частичная компенсация пройденных курсов на различных платформах; — Добровольная международная сертификация ISTQB с компенсацией от компании; — Корпоративные занятия английским языком; — Оборудование от компании; — Реферальная программа "Приведи друга";

Location: San Francisco, CA | New York City, NY 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 The Account Abuse team is tasked with ensuring Anthropic's computing capacity is allocated fairly, minimizing resources available to bad actors and preventing them from coming back. As a software engineer on this team, you will build the machine learning systems that help us detect and stop abuse at scale. The ideal candidate can see things from opponents' perspectives, understand their means and motives, and anticipate their responses to countermeasures. We're looking for full stack machine learning engineers with experience across model training, productionization, and evaluation. You'll also look for ways to use Claude to speed up how these models get built and maintained. This is classical ML on structured and behavioral data. You do not need a deep learning background or knowledge of LLM internals. What matters is that you have trained and shipped models where the stakes are real, and that you care about building robust production systems as much as the model itself. A false positive here is a legitimate customer locked out, so measurement, precision, and safe rollout are part of the job. Key responsibilities Build and operate a feature computation platform that serves both model training and real-time scoring, with point-in-time correct training data and low-latency online retrieval Train, evaluate, and deploy models that detect account-level abuse and fraud, running them both offline and online Build tooling that automates more of the model development lifecycle, including using Claude to speed up feature development, training, and evaluation Make backtesting, shadow deployment, and staged rollout the default path to production, with monitoring for training / serving skew, drift, and adversarial adaptation Work with our data scientists and our Policy & Enforcement team to improve label coverage and quality Partner with product and platform teams to gather signals and integrate model decisions with minimal impact on their systems' latency, stability, or overall architecture Minimum qualifications Proficiency in Python and SQL Experience training machine learning models and deploying them to production Experience building data pipelines with a batch processing engine (e.g., Spark, Beam) and a workflow scheduler (e.g., Airflow) Working understanding of point-in-time correctness and training / serving skew, and how to prevent both Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders Preferred qualifications Experience building or operating a feature platform such as Chronon, Feast, or Tecton Experience with stream processing engines such as Flink, Beam / Dataflow, or Kafka Streams Experience training ML models in a production setting with demanding serving requirements, such as fraud, risk, or ranking Experience with tree-based models on tabular data Experience building unsupervised, clustering-based or graph-based detection systems to surface coordinated account abuse Experience in integrity, spam, fraud, or abuse detection Experience working with scarce, delayed, or noisy labels Experience with AutoML or other approaches to automating the ML workflow Care about the societal impacts of AI and want your work to make powerful systems safer 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: United States Workplace: Remote About Cantina: Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning. If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future! About the Role: Cantina is a place where people create AI characters and the videos those characters star in, and the catalog grows far faster than anyone can browse. Search and recommendations are what turn that catalog into a product: they decide which characters a new user meets in their first minute, which creators get discovered, and what appears in every feed, leaderboard, and discovery surface we ship. We are hiring a Senior Staff Software Engineer to own that area end to end — retrieval, ranking, relevance quality, and the roadmap for all three. This is the first dedicated hire for search and recommendations, so you will inherit a real production system serving live traffic along with a large amount of unclaimed ground, and you will set the technical direction rather than execute someone else’s. What you'll do: - Own the architecture and roadmap for search and recommendations end to end — query understanding, retrieval, ranking, and the surfaces they feed: search, discovery, the home feed, and our trending and creator leaderboards. - Make relevance a measured discipline rather than an opinion: define the quality metrics per surface, build the offline evaluation and golden-set tooling, and run the online experiments that decide whether a ranking change ships. - Design and evolve the ranking stack — engagement signal pipelines, decay and freshness models, and the pattern we use to combine pre-computed index-time signals with live re-ranking at query time. - Own OpenSearch in production: index and mapping design, reindex and cutover safety, query performance, cost, and the operational headroom of the clusters behind every discovery surface. - Build candidate generation and personalization for recommendation surfaces, and partner with data and ML on the feature pipelines and models behind them. - Work directly with Product and Trust & Safety on what “good” means for each surface — quality gates, cold-start behavior for brand-new creators and characters, and what must never be recommended. - Set the engineering standard for the area: instrumentation, flag-gated rollouts, and runbooks that let other teams change ranking behavior without breaking it. - Act as the technical point of contact for discovery across backend teams, and mentor the engineers whose work touches it. What you'll bring: - 10+ years building production software, with substantial depth in search, ranking, recommendations, or ML-driven relevance on a consumer-scale product. - Hands-on expertise with a production search engine — OpenSearch, Elasticsearch, Lucene, Vespa, or similar — covering index and analyzer design, relevance tuning, and operating the cluster, not only querying it. - A rigorous approach to relevance measurement: you have owned offline evaluation, golden sets, and A/B or interleaving frameworks, and you can explain what moved a metric and why. - Fluency across the recommender stack — candidate generation, feature pipelines, embedding retrieval, re-ranking — and a working understanding of the serving constraints that make an offline win fail online. - Strong distributed systems and backend fundamentals, with production experience in Go or a comparable systems language, and comfort in the data layer behind it (SQL warehouses, streaming and batch pipelines). - Demonstrated ownership of an ambiguous area: you have picked up something with no dedicated owner, decided what mattered, and can show the result. - Clear written communication and the judgment to work with Product on real tradeoffs between relevance, freshness, safety, and latency. - Preferred: experience with AI-generated or rapidly growing content catalogs, severe cold-start conditions, or ranking under trust-and-safety constraints. Compensation: The anticipated annual base salary range for this role is between $250,000 - $320,000 (USD). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.   Benefits: - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!

Location: Global Remote Workplace: Remote Hi! This is the Flipper team. We are the creators of Flipper Zero https://flipper.net/ — a portable device for tech enthusiasts and engineers. It's a gadget with an awesome community that brings together millions of people around the world. We are currently developing a new product — the BUSY Bar https://busy.app/ productivity multitool. It's a smart device that helps you stay focused and minimize distractions. We're looking for a Senior QA Engineer (IoT / Embedded & Cloud) to design and own test coverage for complex E2E scenarios spanning firmware, cloud services, and mobile applications, ensuring reliable interaction between devices, backend systems, and apps. Responsibilities - Design E2E test coverage across firmware, cloud, and mobile applications to verify device state, data consistency, and end-to-end behavior - Test device-to-cloud communication, including network failures, reconnections, timeouts, offline operation, and OTA update and rollback scenarios - Test cloud and local APIs, business logic, data validation, and error handling to ensure reliable behavior across integration scenarios - Analyze device and cloud logs to diagnose issues, verify command execution, and identify anomalies across system components - Build test data and configuration strategies for different device types, users, environments, and complex scenarios involving multiple devices - Identify and prioritize E2E scenarios for automation, define test specifications for automation engineers, and maintain stable smoke and regression testing processes Requirements - Strong QA experience with complex software products and the ability to design test coverage across firmware, backend APIs, and mobile applications - Strong requirements analysis and systems thinking, with the ability to identify dependencies and integration points across devices, cloud services, and applications - Hands-on experience testing REST or gRPC APIs using tools such as Postman, Swagger, or existing automated tests - Experience analyzing device logs such as UART or syslog and cloud logs using tools such as Kibana or Sentry, with a basic understanding of embedded systems architecture - Experience testing native or cross-platform mobile applications that interact with devices via BLE or Wi-Fi and cloud services - Experience working in Agile/Scrum environments, building QA processes, managing test artifacts in Jira, Confluence, TestRail, Qase, or TestOps, and defining scenarios for test automation - English proficiency sufficient for reading technical documentation and communicating with an international team Nice-to-haves - Experience testing IoT or smart devices, including OTA updates, connectivity loss and recovery, and offline operation - Basic Python or JavaScript skills for creating simple test utilities, generating test data, parsing logs, or understanding automated tests - Experience with device simulators or emulators, network traffic analysis tools such as Wireshark or tcpdump, or security testing of device-to-cloud integrations What we offer - Choose your work format: office, hybrid, or fully remote from anywhere in the world - You will be provided with all the necessary equipment for a comfortable working environment - Benefits such as VHI, corporate sports, foreign language courses, and therapy sessions - A five-day workweek with a flexible start of the working day

You Will: — Develop an understanding of Roblox moderation rules and guidelines — Identify and engage with potential partners within the developer community to build and maintain a strong partnership pipeline — Plan and execute online and offline community events, workshops, and initiatives that inspire and connect developers across regions — Manage programs from initial concept through successful completion, setting clear goals, tracking milestones, and measuring outcomes — Support translation and localization efforts to ensure programs, communications, and resources are accessible and culturally relevant to global audiences — Follow established team processes while identifying opportunities to refine and improve workflows You Have: — Great understanding of Roblox and the Roblox community — Good standing regarding Roblox moderation history — Excellent speaking and writing skills in both English and Tagalog — Excellent communication and relationship-building abilities, both online and offline — A proactive and adaptable mindset with a passion for supporting and growing a global developer ecosystem — Ability to work cross-functionally and manage multiple priorities in a fast-paced environment with a team-first mentality — Believe that helping the community is crucial to the success of the company — A desire to help empower and encourage our developer community — Knowledge and understanding of community processes, methodologies and best practices — Experience with gaming communities, game jams, or virtual/hybrid event planning is a plus — Early career / fresh grad preferred

Задачи: — Участие в проектах по внедрению и развитию решений на платформе 1С (1С: Управление холдингом) по направлениям «Нормативно-справочная информация (НСИ)» и «Миграция данных» — Разработка и ведение реестра НСИ: определение состава справочников, их атрибутивного состава, мэппингов и классификаторов — Подготовка шаблонов миграции данных: формирование структуры загрузочных файлов, правил приведения данных к единому формату (нормализация), контроль качества выгрузки/загрузки — Разработка методологии и регламентов управления НСИ (порядок ведения справочников, маршруты согласования, ролевая модель) — Подготовка бизнес-процессов в области управления НСИ (в нотациях BPMN / EPC) — Написание технических заданий на доработку системы (в части НСИ и интеграции), постановка задач разработчикам — Поддержка заказчика по вопросам классификации и нормализации НСИ (номенклатура, контрагенты) — Формирование модели данных НСИ — Участие в тестировании: формирование концепции и сценариев тестирования (функционального, интеграционного), проведение приёмо-сдаточных испытаний — Проведение миграции данных (НСИ и транзакционных данных), проверка результатов миграции, формирование протоколов миграции — Подготовка пользовательских инструкций и обучение пользователей работе с НСИ. Требования: — Опыт работы на проектах по внедрению 1С от 3-х лет — Обязательный опыт работы с 1С: Управление холдингом (1С:УХ) — Практический опыт формирования реестра НСИ (определение состава справочников, атрибутов, классификаторов) — Опыт подготовки шаблонов миграции данных — Опыт проведения миграции, в том числе транзакционных данных — Понимание процессов ведения справочников Номенклатура, Контрагенты, Договоры и Основные средства в системе 1С — Знание бизнес-процессов в области управления данными — Опыт подготовки методических документов и регламентов по управлению НСИ — Умение работать в нотациях BPMN / EPC Будет преимуществом: — Наличие сертификатов 1С: Специалист-консультант — Знания РСБУ/МСФО — Опыт работы в консалтинге Условия: — Возможность узнавать изнутри работу крупнейших российских и международных компаний из различных отраслей — Гибридный формат работы и дополнительные дни оплачиваемого отпуска — Конкурентоспособный уровень дохода, возможность ежегодного повышения по результатам Performance Review — Культура наставничества и непрерывного обучения: менторство в профессиональном развитии, online и offline обучение в корпоративной академии — Широкая программа корпоративных привилегий — Участие в корпоративных спортивных и развлекательных мероприятиях.

Команда «Мотивационный профиль» создает новый подход к работе с клиентом, который позволит перейти от классической персонализации к более глубокому пониманию человека на основе психологии. Мы извлекаем из данных психометрические характеристики — ценности, страхи, особенности характера и принятия решений — и используем их в продуктах банка и экосистемы. Для построения мотивационного профиля мы используем анкеты, подробные интервью, поведенческие и транзакционные данные. Работаем с известными психометрическими методиками и подходами, разработанными исследовательской командой. Одна из ключевых задач — научиться надежно определять психометрические характеристики на ограниченных выборках, масштабировать их на широкую клиентскую базу и использовать в рекомендательных сценариях и моделировании клиентских реакций. Задачи: — работать с таргетами, полученными из анкет и интервью с помощью экспертной и LLM-разметки — подбирать постановку задачи в зависимости от объема и качества данных: supervised learning, weak supervision, few-shot и другие подходы — сравнивать методы моделирования — от rule-based решений и классического ML до моделей на основе embeddings и LLM — обучать модели для предсказания психометрических и поведенческих характеристик клиента — масштабировать характеристики, доступные для ограниченной выборки клиентов, на широкую клиентскую базу — оценивать модели как по стандартным ML-метрикам, так и по тому, насколько хорошо их результаты работают в прикладных сценариях - сегментации, персонализации и моделировании поведения клиента — работать с неструктурированными данными, в том числе с текстами глубинных интервью — строить пайплайны обработки текста: чанкинг, построение эмбеддингов, кластеризация и извлечение признаков — сопоставлять информацию из текстов с поведенческими и транзакционными данными — проверять качество разметки и данных, анализировать смещения выборки и устойчивость полученных признаков — оценивать репрезентативность обучающей выборки и возможность переноса результатов на широкую клиентскую базу. Требования: — опыт работы Data Scientist / ML Engineer от 2–3 лет — уверенное знание Python и стандартного DS/ML-стека: pandas, numpy, scikit-learn, CatBoost / LightGBM / XGBoost — опыт построения supervised ML-моделей для табличных данных — хорошее понимание задач классификации, регрессии и ранжирования — опыт работы с текстовыми данными и NLP: embeddings, sentence-transformers, кластеризация, классификация текстов, семантический поиск — понимание основных подходов к работе с LLM: prompting, few-shot, zero-shot, LLM-разметка и оценка качества LLM-ответов — умение проектировать метрики и схемы offline-валидации для нестандартных задач — умение работать с неоднозначными таргетами, шумной разметкой и неполными данными — уверенная работа с большими данными — способность переводить бизнес-гипотезу в ML-задачу: формализовать постановку, определить требования к данным и метрикам, учесть ограничения и сформулировать критерии успешности — умение понятно объяснять результаты как ML-специалистам, так и продуктовой команде. Условия: — комфортный современный офис рядом с м. — Кутузовская — возможность выбрать удобный график – офис/гибрид — ежегодный пересмотр зарплаты, годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте — расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа — гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ — подписка Прайм с возможностью совместного использования на трёх близких — вознаграждение за рекомендацию друзей в команду Сбера.

Talablar: — High-load backend servislar bilan ishlash — Katta hajmdagi ma’lumotlar bilan ishlash — Davlat tizimlari bilan integratsiya qila olish — AI/ML va RAG/LLM servislar, monitoring va testlar qila olish — Kamida 4 yil commercial tajriba, shundan 2 yil Go bilan production tajribasi talab qilinadi Shartlar: — Ish turi: 9:00-18:00, offline 5/2 Kompaniya haqida: — Milliy statistika qo‘mitasi huzuridagi Raqamli statistika markazi

Location: Berlin Workplace: Hybrid adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world's smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem. Next-Gen Machine Intelligence for Scalable Discovery & Engagement The Data Science Research team builds foundational ML representations and advanced AI capabilities that enhance both Playtime and adjoe Ads. Operating as a horizontal deep-tech layer, the team leverages advanced AI and deep learning approaches—specifically generative approaches —to deliver critical systems such as high-dimensional user embeddings, general content understanding and sequential recommendation. These frameworks scale adjoe's products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users. The team operates at the intersection of bleeding-edge R&D and high-scale production engineering, acting as the company’s internal science bar raiser and primary consulting layer for complex ML bottlenecks. The stack is optimized for deep learning and heavy data throughput: PyTorch and [Ray/Hugging Face] for training and fine-tuning foundation models, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure for heavy workloads. The full lifecycle of these AI capabilities is owned by the team—from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain high-throughput, realtime production environments. Your Mission & Who We Are Looking For: - PhD or equivalent research depth, with a production track record. You have a PhD in CS, Statistics, Math, or Physics, or an MSc with extensive industry research, and publications in top-tier venues like SIGIR, KDD, NeurIPS, or ICLR. You've spent 4+ years building large-scale recommender systems in high-throughput environments: AdTech, e-commerce, or social. - You translate research into production, not just prototypes. You distill SOTA research into robust, production-ready code optimized for sub-millisecond latency. At adjoe, that means architecting multi-stage recommendation pipelines, Generative Retrieval, Deep Ranking, and Re-ranking, serving millions of requests across a stack built on 770 million users' behavioral data. - Deep expertise in PyTorch and large-scale model optimization. You have hands-on experience with high-concurrency optimization, model quantization, and distillation, the engineering side of getting large generative models to run under extreme production constraints, not just in research environments. - Content understanding and embeddings are core to your work. You research and develop information-rich user and ad embeddings using unsupervised and generative approaches, directly improving the quality of predictions across both Playtime and adjoe Ads. - Raises the technical bar around them. You lead architectural debates, mentor junior scientists, and drive the team's research direction without needing a roadmap handed to you. 🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

О проекте: VK AI Space — платформа для создания и эксплуатации AI-агентов и LLM-решений корпоративного уровня. Продукт внедряется как в облаке, так и в закрытых контурах заказчиков (on-premise, air-gapped). Задачи: — Разворачивать и эксплуатировать Kubernetes-кластеры в production, в том числе с нуля через Kubespray. — Работать в закрытых (air-gapped) контурах без доступа к интернету: самостоятельно готовить пакеты, образы, чарты и зависимости для offline-развёртывания. — Устанавливать и настраивать сервисы в Kubernetes через Helm, дебажить и дорабатывать чарты «на лету» в процессе внедрения. — Настраивать и сопровождать сопутствующий стек: БД и сервисы в Kubernetes, Kafka, ClickHouse, Postgres, Qdrant, Traefik, OpenSearch, NATS, NACK. — Обеспечивать работу GPU-нагрузок: KubeRay Operator, NVIDIA Device Plugin. — Диагностировать и устранять проблемы на уровнях Kubernetes, Helm, Linux. — Самостоятельно вести внедрение от подготовки инфраструктуры до запуска и передачи в эксплуатацию. — Выезжать к заказчикам в Москве и регионах для работ в закрытых контурах (примерно 40% проектов — onsite, 60% — удалённо). Требования: — Готовность к очным выездам к заказчикам в Москве и на площадки заказчиков для внедрения продукта в закрытых контурах. — Практический опыт развёртывания и эксплуатации Kubernetes в production. — Уверенное владение Kubespray: самостоятельное развёртывание кластера с нуля, понимание архитектурных компонентов и их взаимодействия. — Опыт работы в закрытых (air-gapped) контурах без доступа к интернету. — Умение самостоятельно подготовить все необходимые пакеты, образы и зависимости для offline-развёртывания. — Опыт установки и настройки сервисов в Kubernetes через Helm. — Умение дебажить и дорабатывать Helm-чарты в процессе внедрения. — Уверенное знание Linux, Ansible, Terraform, Docker / Container Registry. — Навыки диагностики и устранения проблем Kubernetes, Helm, Linux. — Опыт внедрения решений у заказчиков. — Способность самостоятельно доводить внедрение от подготовки инфраструктуры до запуска и эксплуатации продукта. Условия: — Заработная плата до 250 000 руб. (окончательный размер обсуждается по результатам собеседования). — Гибридный формат работы. — График работы 5/2 с гибким началом рабочего дня. — Оформление на выбор — по ТК РФ, ИП или как самозанятый. — Статус аккредитованной IT-компании. — Амбициозные проекты и профессионально интересные задачи. — Возможность для карьерного и профессионального роста в динамичной компании.

Задачи: — Ведение переговоров с клиентами (Online, Offline) — Подбор объектов — Презентация и показ объектов потенциальным клиентам Требования: — Опыт работы в продажах — Умение вести переговоры (Online, Offline) — Знание компьютера (CRM) — Грамотная речь — Знание грузинского языка — Знание английского языка — Знание русского языка

Talablar: • Python + FastAPI — ishonchli darajada, 2 yildan ortiq tijoriy (amaliy) tajriba; • MySQL / PostgreSQL — sxemalarni loyihalash, indekslar, sekin so‘rovlarni (slow query) o‘qiy olish va tahlil qilish; • Linux va tarmoqlar — asosiy darajada: SSH, Nginx, loglar, ularning ishlash prinsipini tushunish; • Git — jamoaviy ishlash, tarmoqlar (branches), kod tekshiruvi (code review). Ish turi: To'liq ish kunida, offline 5/2.

Требования: — Master data boshqaruvini qila olish; — Ma’lumotlarni tozalash va avtomatlashtirish; — ETL, API integratsiyasi, analitika va hisobotlar, katta hajmdagi ma’lumotlarda xatolarni aniqlash; — Ishga o'z vaqtida kelish va mas'uliyat bilan yondashish Условия: — To'liq ish kuni, offline 5/2

Location: United Kingdom; Brazil; United Arab Emirates; Ireland; Peru; Sweden; Colombia; Argentina; Romania; Cyprus; Switzerland; Portugal; Lithuania; South Africa; Czech Republic; Canada; Hungary; Mexico; Chile; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   Consumer Trading is a full-stack team behind the Consumer experience in Kraken mobile and web applications. Our flagship product allows our clients to instantly buy, sell, convert any combination of stocks, cryptocurrencies and cash. We are constantly working on extending the product suite with new features and improvements. THE OPPORTUNITY - Own the connective tissue between marketing and product at Kraken Consumer — a remit with real scope to shape how millions of people discover and return to our products. - Build something from the ground up: the roadmap, the intake model and the standards for how marketing and product work together are all yours to define. - Sit at the centre of the acquisition funnel, where small improvements in conversion compound into meaningful growth. - Unlock new acquisition channels by building the product surfaces they depend on — paid social, search, affiliates and offline campaigns. - Shape a fast-growing mobile acquisition motion, including in-product social, creator partnerships, community and friend-referral mechanics. - Own both halves of the lifecycle: bringing new users in, and giving existing users compelling reasons to come back. - Work in one of the most competitive corners of consumer fintech, where conversion craft and product quality genuinely decide who wins.     WHAT YOU BRING - Own the marketing product roadmap end to end, and build the process that turns campaign ideas into shipped product work. - Design and launch tailored campaign experiences — the in-app and web journeys users land in from push, email, social and paid. - Raise the bar on lifecycle messaging so push and email feel useful rather than noisy, and convert accordingly. - Own the incentives layer for new and returning users: offers, referral mechanics, recurring deposits and earn-led campaigns. - Apply user psychology and sharp UX thinking to find where the funnel leaks, then run the experiments that close the gaps. - Improve landing page and search performance, and build the product foundations that make paid and offline channels measurable and worth the spend. - Partner with marketing, design, engineering and data as the single point of ownership for growth enablement. - Define the acquisition and reactivation metrics that matter, and report on them honestly — including when an experiment doesn't land.           Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   Consumer Trading is a full-stack team behind the Consumer experience in Kraken mobile and web applications. Our flagship product allows our clients to instantly buy, sell, convert any combination of stocks, cryptocurrencies and cash. We are constantly working on extending the product suite with new features and improvements.   THE OPPORTUNITY - Own the connective tissue between marketing and product at Kraken Consumer — a remit with real scope to shape how millions of people discover and return to our products. - Build something from the ground up: the roadmap, the intake model and the standards for how marketing and product work together are all yours to define. - Sit at the centre of the acquisition funnel, where small improvements in conversion compound into meaningful growth. - Unlock new acquisition channels by building the product surfaces they depend on — paid social, search, affiliates and offline campaigns. - Shape a fast-growing mobile acquisition motion, including in-product social, creator partnerships, community and friend-referral mechanics. - Own both halves of the lifecycle: bringing new users in, and giving existing users compelling reasons to come back. - Work in one of the most competitive corners of consumer fintech, where conversion craft and product quality genuinely decide who wins.     WHAT YOU BRING - Own the marketing product roadmap end to end, and build the process that turns campaign ideas into shipped product work. - Design and launch tailored campaign experiences — the in-app and web journeys users land in from push, email, social and paid. - Raise the bar on lifecycle messaging so push and email feel useful rather than noisy, and convert accordingly. - Own the incentives layer for new and returning users: offers, referral mechanics, recurring deposits and earn-led campaigns. - Apply user psychology and sharp UX thinking to find where the funnel leaks, then run the experiments that close the gaps. - Improve landing page and search performance, and build the product foundations that make paid and offline channels measurable and worth the spend. - Partner with marketing, design, engineering and data as the single point of ownership for growth enablement. - Define the acquisition and reactivation metrics that matter, and report on them honestly — including when an experiment doesn't land.           Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Workplace: fully Role Overview The Senior Product Designer is a hands on IC who’ll set the craft bar for our new flagship mobile money app, Ethena Pay. Ethena Pay is live on iOS with Android on the way. The app still needs more features and moments of delight that make the best apps a joy to use. Your core job is closing that gap. You'll hold Ethena Pay to the standard of the best-designed consumer products, in money and beyond. You'll own a share of the product end to end, the design system and the brand outright. About 80% of your time goes to product design and the system. The other 20% goes to complementing marketing design, so the quality people see in the app also shows up where we meet them, in launch content, X and on the store pages. You'll report to the Head of Product and work as a peer to our existing Product Designer. Role Responsibilities Review the whole app and design system on iOS and Android. Turn what you find into a ranked plan for what to keep, fix or rebuild. Set and ship a new design standard with engineering: a component library, a motion and interaction language (timing, springs, haptics, transitions) and rules for layout, type and states. Build it into the system so every screen gets it by default. Design every state, not just the happy path: loading, pending, failed, limit reached, offline and "we don't know yet". Own the display rules for money so balances, rounding and pending vs settled amounts are always clear. Create the voice of the app. Terminology, error copy that says what happened and what to do next. Own the brand: write guidelines GTM can use without a designer, build partner co-branding and card artwork, and turn the app's best moments into X content, launch videos and store pages. Bring Android up to the same bar. Put both apps on the same components, tokens, motion and states, and decide where Material applies and where the brand wins. Raise the team's craft through critique and pairing, run lightweight research yourself, and help build the design practice as the team grows. Required Skills and Experience A track record and portfolio of world-class mobile app design: Not “I can do it”, but “I have done it and know how to do it better”! Several years designing shipped native apps whose design is a reason people use them. Motion and interaction design at a high level: transitions, springs, gestures, haptics and micro-interactions, shown as prototypes or recordings and specified precisely enough for engineers to build to the frame. Senior product design experience on a live neobank, payments, card or crypto money app where design is a competitive advantage (e.g. Revolut, Monzo, Wise, Nubank, Cash App, Plasma One), or other consumer mobile apps that stand out for their design (e.g. AirBnB). A portfolio that shows states, not just hero screens, plus an honest account of what shipped compared with what was designed. Evidence that you've raised a team's craft, not only your own: designers you critiqued or engineers you paired with got visibly better. Great if you've reviewed and rebuilt an existing app and its design system Real brand and marketing work you made yourself, such as an identity or a significant extension of one, card artwork, or launch and social content built from the product. Motion work for marketing content will set you apart. Agent-native design: you use AI tools (Figma MCP, Claude Code or equivalent) to speed up your work while holding the craft bar, and you know where they fail.

Location: New York; Stockholm; San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: - Self-serve AI analytics tools (Hex, Snowflake) - Embedding with teams as a “data adviser,” providing strategic analysis and consulting WHAT YOU'LL WORK ON: - Contribute to building the most modern analytics stack https://modal.com/blog/analytics-stack in data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting - Influence work on new products like LLM Inference Endpoints https://modal.com/blog/qwen3-8-2-4t-a95b-now-available-on-modal through product analytics tracking - Identify millions of dollars of cost savings and optimization across our tools and financial operations - Write data pipelines that power the operations of our business, such as our cloud compute economics or sales comp - Create foundational datasets that can be used by people and AI tools to answer questions around product use cases, financial reporting, and marketing campaigns YOU MAY BE A FIT IF: - You’re fluent in SQL and proficient in Python - You have professional experience with at least 2 of the following tools: Snowflake, dbt, dlt, Modal, Hex, PostHog - You extend your work beyond just data reporting and into action and impact - You have high attention to detail - You’re an excellent and precise communicator - You’re personable and great at building relationships NICE-TO-HAVE: - Experience with AI products, especially LLM inference and sandboxes - Experience in fin ops, fraud, sales ops, or risk, especially in the context of AI (e.g. token cost optimization) - Project management skills - Strong presence in the data community online and offline