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Location: New York Workplace: remote ⚡️ About Merkle Science Merkle Science provides blockchain transaction monitoring and intelligence solutions for web3 companies, digital asset service providers, financial institutions, law enforcement and government agencies to detect, investigate and prevent illicit use of cryptocurrencies. Our vision is to make cryptocurrencies safe and provide infrastructure for the safe and compliant growth of cryptocurrencies. Merkle Science is headquartered in New York with offices in Singapore, Bangalore and London. The team has combined experience across Bank of America, Paypal, Luno, Thomson Reuters and Amazon. The company has raised over US$27 MM from SIG, Beco, Republic, DCG, Kenetic, GGV and several others. The Role You will design, build and run the systems behind our data products, covering ingestion, processing, analytical storage and serving. You own your work from the design document through to production. The people who design a pipeline also run it and answer for its numbers. Our stack is very wide, and we go deep in every part of it. We don't stop at "it works." We keep measuring, profiling and tuning to make systems faster, cheaper and more reliable. We want engineers who are razor sharp, pay close attention to detail, and care as much about why a query takes 800 ms as whether it returns the right answer. You don't need blockchain experience. If you're a strong data engineer who wants to learn it, we'd like to hear from you. What You'll Do Design and build scalable, high-throughput data pipelines and platform systems for blockchain data across 30+ chains. Build backend data services and loaders in Go and Python. Design and evolve data models and analytical workloads in ClickHouse, and tune them for sub-second queries. Build incremental, idempotent pipelines on Databricks over billions of rows and tens of terabytes. Keep improving the scale, reliability, freshness, performance and cost efficiency of the platform. Investigate hard performance and reliability problems and see them through to resolution. Work closely with the product, analytics and investigations teams that use the data, and turn their needs into platform designs. Help set technical direction through architecture discussions, design reviews and code reviews. Mentor engineers and help set strong engineering and operational practices. What You Bring 5+ years building and operating production data systems, including ETL and ELT pipelines. At least two of those years should be spent owning systems that other engineers depend on. Expert Python and strong SQL. You write typed, tested code, are comfortable with asyncio and concurrency, and have built incremental data models over billions of rows. Go for backend services. You have built and run high-throughput services or data loaders in Go in production. ClickHouse in production. You know MergeTree schema and sort-key design, materialised views, bulk loads and query tuning. Databricks in production. You have worked with PySpark, Delta Lake and Unity Catalog, designed incremental and idempotent tables, and kept an eye on compute cost. Large-scale data. You have hands-on experience with pipelines over billions of rows and tens of terabytes. You understand how partitioning, clustering and file sizing affect cost and latency. Kafka, Airflow and Kubernetes in production. You understand delivery semantics and idempotent writes, have handled backfills and failures, and have run data workloads with Docker and Helm. Google Cloud is preferred; AWS is fine. An operations and communication mindset. You instrument what you build, write runbooks and post-incident reviews, and can write a design document that a reviewer in another time zone can approve.   Nice to Have Blockchain data: EVM, UTXO or non-EVM chain data models, and pulling data from nodes over JSON-RPC or gRPC. Graph or distributed key-value stores: entity resolution or clustering on large graphs. Infrastructure as code, GitOps and observability: Terraform, Helm, ArgoCD, OpenTelemetry, Prometheus and Grafana, and load-test design. Experience building platforms that serve multiple data sources, datasets or product teams. AI-assisted development, and experience in fintech, compliance or AML. How We Work You'll join a small, senior team where everyone owns their work end to end. We make decisions based on measured evidence, not opinion. We keep design notes and runbooks next to the code. We test at production scale and run blameless post-incident reviews. We use AI coding tools every day, and we use judgement when reviewing what they produce. ❤️ Well Being, Compensation and Benefits We care about your well-being. Along with excellent health insurance, we offer flexible time off, learning & development initiatives and hours that are designed to provide work/life balance.  We regularly host team-building sessions and encourage discussions around mental health.   We reward talent and believe in acknowledging people for their contributions.  We offer industry-leading compensation, along with generous equity.  As a rapidly growing business, there are endless opportunities to grow your career with Merkle Science.

Location: Москва Корпоративная BI-система на базе Навигатора BI, хранилища (PostgreSQL, ClickHouse, Ozone) и ETL/ELT-пайплайнов (NiFi, Airflow, Spark). На базе системы работает продукт Digital trace (Цифровые следы сотрудников – аналитический продукт для принятия управленческих решений на основе данных из система банка, для оптимизации процессов и повышения эффективности). Обязанности * организация процессов разработки (Scrum/Kanban): спринты, планирование, ретроспективы, код-ревью * построение метрик эффективности команды и качества кода * проектирование отказоустойчивых пайплайнов потоковой/пакетной обработки данных и хранилищ * обеспечение высокой доступности и производительности подсистем (СУБД, BI, ETL) * настройка мониторинга, алертинга, логирования; решение инцидентов поставки данных * коммуникация со стейкхолдерами (аналитики, продакты, безопасность), согласование SLA. Требования * опыт промышленной разработки в современной BI системе Qlik Sense, Tableau, Power BI, Superset от 5 лет * опыт промышленного использования Apache NiFi и Apache Airflow * продвинутый SQL (оконные функции, сложные JOIN, оптимизация) * опыт работы с реляционными и колоночными БД * опыт организации процессов разработки (SDLC) * понимание жизненного цикла данных в организации (Data Lifecycle Management), опыт работы в рамках процессов Data Governance. Будет плюсом: * понимание основ работы Git, CI/CD * опыт разработки на одном из современных языков программирования (в контексте обработки данных) - от 4 лет * понимание принципов работы брокеров сообщений (RabbitMQ, Kafka) * опыт работы с Docker/Kubernetes * опыт работы с картами компетенций в подразделении * опыт настройки мониторинга на базе Prometheus + Grafana * опыт внедрения и эксплуатации процессов Data Governance * опыт работы с LLM и AI-агентами. Техстек: Навигатор BI (разработка Сбера), Qlik Sense (выводится из эксплуатации), PostgreSQL, ClickHouse, Apache NiFi, Airflow, Spark, Kafka, Ozone. Условия * комфортный офис: г.Москва, проезд 2-й Южнопортовый, 12Ак1, (м.Кожуховская) * возможен гибридный формат работы после испытательного срока * ежегодный пересмотр зарплаты и годовая премия * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Chicago, Illinois Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin is transforming customer service through AI, helping businesses deliver fast, accurate, and reliable support at scale. Trust is foundational to that mission. Fin's Security Engineering team is unlike most security teams. We own and operate critical security services, build customer-facing security features, and partner with engineering teams to make secure development the default. We're engineers first; designing, building, and operating systems that protect Fin and its customers. The team owns and operates tier-zero services including authentication, SAML/SSO, teammate activity logs, malicious URL scanning, and other critical trust and security capabilities. The mission of the team is to help Fin build and operate trusted AI-powered customer service experiences by making security a natural part of how products are designed, developed, and delivered. As Fin continues to expand its capabilities and adoption, you'll help shape how security evolves alongside some of the most ambitious AI-powered products in customer service. We're taking an AI-first approach to security, exploring areas such as AI-powered detection, red-team automation, continuous monitoring, and emerging defensive capabilities to help meet an evolving threat landscape. What will I be doing? Own and engineer tier-zero security capabilities that help customers securely deploy and manage Fin. Design, build, and evolve customer-facing security features, including authentication, SAML/SSO, permissions systems, audit and activity logging, malicious URL scanning, and other enterprise security controls. Partner with engineering teams throughout the software development lifecycle to build secure products and services. Perform architecture reviews, threat modelling exercises, and security assessments for new features and systems. Build security tooling, automation, and developer-facing building blocks that make secure development easier and more scalable. Contribute to secure development standards, guidance, and best practices across Fin. Lead application security initiatives across the software development lifecycle, helping teams identify and address security risks early. Participate in a shared on-call rotation and lead security incident response, investigation, and remediation efforts. Drive security initiatives from problem definition through design, implementation, and measurable outcomes. Partner with teams building AI-powered products to assess and mitigate emerging security risks. Help shape Fin's AI-first approach to security, including AI-powered detection, red-team automation, continuous monitoring, and emerging defensive capabilities. Support the secure adoption of AI-assisted software development tools and engineering workflows. What skills do I need? Proven application security, product security, or security engineering experience within a SaaS environment. Strong software engineering skills with experience designing, building, and operating production systems. Deep understanding of modern application security threats, secure software development practices, and threat modelling. Experience designing, building, or securing authentication, authorization, identity, or enterprise security capabilities. Experience conducting architecture reviews and security assessments for complex systems. Hands-on security incident response experience, including leading investigations and remediation efforts. Strong programming skills and experience building tools, automation, or developer-focused solutions. Comfortable using modern AI-assisted development tools to improve productivity and engineering effectiveness. Ability to communicate security concepts clearly and collaborate effectively with engineering teams. A pragmatic approach to balancing security, customer impact, and engineering velocity. Bonus skills & attributes Experience building or owning authentication, SAML/SSO, identity, or access management capabilities. Experience securing AI-powered products or familiarity with security considerations for large language models, agentic systems, retrieval-based architectures, or AI tool integrations. Experience building security automation or security-focused platform capabilities at scale. Familiarity with cloud security, infrastructure security, or distributed systems. Experience working across both large-scale SaaS environments and high-growth companies. *Proof of eligibility to work in the United States is required. The base salary range for candidates within the Greater Chicago Area is [$190,000 - $210,000]. Actual base pay will depend on a variety of factors such as education, skills, experience, location, etc. The base pay range is subject to change and may be modified in the future. All regular employees may also be eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs). #LI-Hybrid Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Responsibilities: — Administer Linux infrastructure — Manage hybrid cloud and container platforms — Automate operations — Strengthen system reliability

Responsibilities: — Build alerting, recovery, telemetry, and incident-management systems for inference fleets. Technologies and practices involved include site reliability engineering, Kubernetes, SLO, PCIe, incident management, Grafana, BMC, Prometheus, Redfish, Infrastructure-as-Code, Go, PagerDuty, Terraform, networking, Rust, firmware, Python, Ansible, error budget, and debugging.

Responsibilities: — Build agentic tools — Develop evaluation systems — Create engineering workflow infrastructure The role involves working with infrastructure, data pipelines, LLMs, failure analysis, multi-agent orchestration, RAG, tool calling, evaluation, MCP, software engineering, DevOps, chip development, fine-tuning, agents, GPU kernels, and context management. Location: San Jose, CA, onsite.

Պարտականություններ: — Պատասխանատվություն կրել բջջային հեռախոսների բազային կայանների, գլխամասային գրասենյակների և ընկերության այլ շինարարական նախագծերի կառուցման հետ կապված աշխատանքների պլանավորման, կազմակերպման, հսկողության և ընդունման համար։ Պահանջներ: — Բարձրագույն կրթություն։ — Առնվազն 2 տարվա աշխատանքային փորձ։ — Անգլերեն, հայերեն և ռուսերեն լեզուների տիրապետում։

Задачи: — Руководство инженерной командой в приложении для знакомств с более чем 17 миллионами пользователей по всему миру. Требования: — Опыт разработки бэкенда не менее 8 лет в продакшн-среде; — Наличие реальной ответственности на уровне Director of Engineering, Head of Engineering или CTO в небольшой компании; — Обязательный опыт работы в стартапах; — Владение английским языком на уровне C1; — Кандидаты из России не рассматриваются. Условия: — Удалённая работа.

Location: Москва Мы занимаемся pretrain'ом больших языковых моделей в GigaChat: проектируем архитектуру, подбираем рецепт обучения и поддерживаем весь инженерный контур вокруг него. Недавно мы обучили MoE-модель на 700 миллиардов параметров — и на этом не собираемся останавливаться. Обучение идёт на кластерах H100 и B200. GigaChat — самый быстрорастущий проект Сбера, и pretrain — его ядро. **Чем занимается команда** * Архитектура и законы масштабирования. * Рецепт обучения: оптимизаторы, расписание learning rate, нормализация, точность вычислений. * Устойчивость больших прогонов и ускорение сходимости. * Диагностика обучения и оценка изменений с опорой на математический аппарат. * Инженерный контур: воспроизводимость, тесты, CI/CD. * Роль с акцентом на модель, оптимизацию и инфраструктуру обучения, а не на данные. Главная цель — делать обучение быстрее, надёжнее и предсказуемее. **Какие задачи стоят перед командой** * Ускорение цикла «идея → эксперимент → вывод → внедрение». * Снижение количества ручных прогонов и неочевидных сбоев, повышение воспроизводимости и прозрачности результатов. * Повышение надёжности больших прогонов. * Ранняя диагностика деградаций и отделение реальных улучшений от ложных сигналов (расхождение, NaN, коллапс энтропии, артефакты маршрутизации, ложное снижение функции потерь). * Обеспечение безопасного масштабирования при внедрении крупных архитектурных изменений. * Анализ влияния сложных архитектур (например, mixture of experts и маршрутизация) на качество, стабильность и скорость обучения. * Определение и развитие метрик, корректно отражающих изменения в обучении моделей. **Почему мы** Масштаб - 700B MoE уже обучена, дальше — больше. Кластеры на H100 и B200. Публикации. Можно и нужно писать статьи по результатам своей работы — это не ограничивается. Команда - в России нет другой команды, которая занимается pretrain'ом на таком масштабе. Коллеги — люди, которые глубоко разбираются в теме. Влияние. Вы берёте направление целиком. Это не «выполнять задачи из бэклога», а самостоятельно определять, что важно, и доводить до результата. Обязанности * Взять на себя целое направление внутри pretrain'а и развивать его: от постановки задач и планирования экспериментов до внедрения результатов в основное обучение. * Проектировать и проводить эксперименты: формулировать гипотезы, запускать абляции, сравнивать подходы, разбираться в результатах и превращать выводы в решения для основного обучения. * Разбираться с нестабильностью на больших прогонах: искать причины деградаций, строить диагностические метрики, предлагать изменения в оптимизаторе, расписании lr, нормализациях, инициализации, клиппинге, точности вычислений и маршрутизации. * Работать с архитектурой смеси экспертов (MoE): маршрутизатор, балансировка нагрузки, переполнение, артефакты маршрутизации, влияние на качество и производительность. * * Поддерживать большие прогоны и продолжения обучения с чекпоинтов: следить за дрейфом, проверять изменения в коде и конфигурации, снижать риск регрессий. * Улучшать инженерное качество контура обучения: ревью критичных изменений, стратегия тестирования, воспроизводимость экспериментов, профилирование и устранение узких мест. Требования * Глубокое понимание устройства обучения нейросетей: не на уровне обзоров и пересказов, а на уровне, где вы можете объяснить, почему конкретный прогон расходится, глядя на кривые функции потерь, нормы градиентов и энтропии. * Способность самостоятельно взять направление и довести его до результата: от чтения статей и постановки гипотез до внедрения в основной трейн. * Практический опыт с PyTorch и именно с обучением моделей, а не только с инференсом. * Умение доводить исследовательские идеи до надёжного инженерного решения: воспроизводимость, конфиги, тесты, автоматизация, понятные критерии качества. * Хорошую инженерную культуру: аккуратные PR, профилирование, внимание к качеству кода, понятные отчёты об экспериментах. Будет плюсом * Опыт со смешанной точностью и распределённым обучением. * Опыт построения систем оценки моделей или инфраструктуры для экспериментов. Условия * Удалённо. * Возможность оформления в аккредитованную IT-компанию. * Годовая премия по итогам работы до 6 окладов. * Регулярный пересмотр зарплат. * Корпоративный спортзал и зоны отдыха. * Более 400 программ СберУниверситета для роста. * Программа адаптации и помощь руководителя на старте. * Крупнейшее DS&AI community — более 600 DS банка, регулярный обмен знаниями, опытом и лучшими практиками, интерактивные лекции и мастер-классы от ведущих ВУЗов и экспертов технологических компаний, дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира, регулярные внутренние митапы. * Расширенный ДМС, льготное страхование для семьи, корпоративная пенсионная программа. * Ипотека для сотрудников по дисконтной программе. * СберПрайм+ и скидки у партнёров. * Бонус за рекомендации в команду

Location: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. Key Responsibilities Develop and optimize recommendation models for Bybit’s trading products, content, and community. Leverage large-scale behavioral data to understand user interests and improve recommendation performance and user experience. Explore cross-domain transfer learning and cold-start strategies tailored to different business scenarios, improving recommendation effectiveness and coverage across domains. Optimize multi-objective ranking models for CTR, CVR, LTV, and other outcomes. Design approaches to combine ranking objectives and balance clicks, conversions, and long-term value under scenario-specific constraints. Model cross-scenario user behavior sequences, short- and long-term interests, and changes in intent. Build reusable user representations to address domain transfer, sparse feedback, and cold-start challenges. Explore generative recommendation approaches, including semantic IDs and generative candidate generation, and integrate them with discriminative recommendation pipelines. Requirements At least four years of experience developing search, advertising, or recommendation algorithms at a consumer-facing internet company, with a deep understanding of candidate retrieval, ranking, and multi-objective modeling. Strong computer science fundamentals and proficiency in at least one of Python, Java, or C++. Strong software design and coding practices, with a passion for solving challenging technical problems. Strong analytical and logical thinking skills, with the ability to identify problems and opportunities through data. A keen interest in emerging technologies and the ability to approach complex problems with clarity and sound reasoning. Strong business judgment, communication, and collaboration skills, with the ability to translate business needs into effective technical solutions. Preferred Qualifications Experience in search, advertising, or recommendation algorithms at major technology companies such as ByteDance, Alibaba, Tencent, Meituan, Kuaishou, or Xiaohongshu. Experience with multi-objective modeling, short- and long-term user sequence modeling, personalized uplift modeling, or generative modeling. Publications at leading international conferences such as KDD, SIGIR, RecSys, ACL, or NeurIPS. An AI-driven approach, with hands-on experience bringing LLM or agent applications into production for search, advertising, or recommendation use cases. Why Join Us A multi-domain recommendation challenge in fintech: Go beyond a single domain such as video or e-commerce. Build personalization capabilities across trading products, market intelligence, community content, campaigns, and AI-powered investment workflows. Proven business impact with significant room for ML advancement: Our current recommendation system has demonstrated a 71% increase in CTR and a 1,285% increase in conversion rate, with substantial potential for an ML-native upgrade. Work at the intersection of AI and recommendations: Build where traditional recommender systems, generative AI, and LLM agents meet—one of the most active frontiers in engineering. An opportunity to lead, not just follow: Bybit’s combination of trading, content, community, AI, and campaigns creates distinctive technical challenges and opportunities for rapid iteration. Global scale: Serve more than 80 million users across over 200 countries, tackling the real-world complexity of large-scale, real-time systems. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

🏢 Проект: Проектирование и разработка пайплайнов обработки данных, поддержка и развитие DWH/ETL-процессов, рефакторинг кода, аналитика и миграция источников данных в отчетности. Проектирование и разработка пайплайнов данных с нуля;

Responsibilities: — Own the reliability, availability, and performance of Orkes' cloud-based distributed workflow platform. — Define SLIs/SLOs. — Run incident response. — Build observability, automation, capacity planning, and operational tooling for Kubernetes-based systems. The position requires working remotely but only within Australia and EMEA regions. Working outside these locations is forbidden.

Location: Hyderabad, India About Workato Workato is the leading Control and Execution Platform for Enterprise AI — the neutral platform enterprises trust to put AI to work across their business. Workato unifies data, applications, and processes into a single platform so AI can reliably orchestrate business processes in production at enterprise scale. Built on more than a decade of running mission-critical processes for over half the Fortune 500 — including Nasdaq, Amazon, Cisco, Vodafone, Atlassian, and Lucid Motors — Workato turns over 14,000 enterprise systems AI needs to act on into one governed execution layer. For more information, visit workato.com . Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles . We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care . That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: Business Insider named us an “enterprise startup to bet your career on” Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers Responsibilities We are looking for an exceptional Automation Engineer Intern to join our team. In this role, you will support the SaaS applications and platforms that power our demo and field environments, investigating access issues, misconfigurations, and recurring requests. You will focus on identifying root causes, developing lasting solutions, and documenting your findings. Working alongside Automation Engineers and Field Systems Analysts, you will receive regular mentorship, take ownership of well-scoped problems, and identify opportunities to automate repetitive work using Workato. In this role, you will also be responsible for: Assist with acquiring and setting up SaaS, PaaS, and IaaS platforms for demos and proofs of concept, including Salesforce, SAP, Workday, NetSuite, ServiceNow, Snowflake, AWS, and GCP, ensuring environments meet user requirements. Collaborate with technical teams to keep demo applications integrated and functioning as expected. Administer demo applications by adding users, configuring permissions, and assigning licenses. Support complex application configurations and verify that they align with organizational requirements. Review application settings regularly to help maintain performance and security. Support users in accessing demo environments and applications, serving as the first point of contact for their requests. Investigate and troubleshoot access problems, misconfigurations, and failed logins, identifying root causes and recommending lasting solutions. Assist with routine governance activities, including access reviews, license tracking, and compliance checks, and flag any anomalies. Identify recurring issues and repetitive manual tasks, and propose or help build automations and tools on Workato to manage demo infrastructure. Help build and maintain environments that support high-quality Workato product demonstrations. Document troubleshooting steps, configurations, and how-to guides to make solutions repeatable. Keep stakeholders informed of request status and escalate blockers promptly. Share findings and lessons learned with the team, including approaches tried and their outcomes. Requirements Qualifications / Experience / Technical Skills Degree in Information Systems, Computer Science, Engineering, or a related field. Demonstrated problem-solving ability through coursework, projects, work, or personal experience involving the diagnosis and resolution of a complex issue. Hands-on exposure to at least one SaaS application or administration console, such as Google Workspace, Slack, Salesforce, Okta, or Jira. Basic understanding of user access concepts, including roles, permissions, and least privilege. Professional working proficiency in English. Experience delivering a project involving application, integration, or system troubleshooting is a plus. Exposure to cloud platforms such as AWS or GCP, or enterprise applications such as Salesforce, Workday, or NetSuite, is a plus. Familiarity with single sign-on and identity concepts, including SAML, OAuth, and MFA, is a plus. Basic scripting or low-code/no-code automation experience using Workato, Python, or similar tools is a plus. Experience using spreadsheets or data tools for analysis and reporting is a plus. Interest in IT governance, security, or compliance is a plus. Soft Skills / Personal Characteristics Methodical approach to problem-solving, with a focus on understanding issues and identifying root causes before proposing solutions. Strong analytical mindset, with the ability to gather information from multiple sources, question assumptions, and draw evidence-based conclusions. Persistence when facing blockers, with sound judgment about when to escalate or ask for help. Clear written communication skills, with the ability to explain problems, reasoning, and solutions so others can follow. Strong attention to detail and a consistent habit of verifying work. (REQ ID: 3000)

We're looking for a Documentation Engineering Manager to lead this work. What you’ll do Lead the execution, development, and prioritization of the Docs Engineering team while remaining hands-on in both technical writing and engineering.

Location: Los Angeles, USA Riot’s Data Engineers build tools and data products that help teams understand and improve the experience of players worldwide. They work across data pipelines, data modeling, data infrastructure, and data quality to make large-scale data useful, reliable, and accessible. As a Data Engineering Intern, you’ll work with data engineers, software engineers, data scientists, analysts, and game or product partners to build and improve data products. You’ll gain exposure to transforming raw data into clean, queryable datasets, designing data models, validating data quality, and supporting data pipelines. You’ll be supported by experienced team members as you learn Riot’s tools, systems, and engineering practices. Potential Responsibilities: Collaborate with data engineers, software engineers, data scientists, analysts, and game teams on data-focused projects. Transform raw data into clean, documented datasets that can be queried and used by downstream partners. Implement small data pipeline, data modeling, or data-quality tasks using established tools, templates, and technical guidance. Support the design of relational data models and data products for game, product, or business use cases. Help validate data for accuracy, timeliness, completeness, and sustainability. Participate in code reviews, technical discussions, team rituals, and project planning. Document technical proposals, implementation details, and data definitions clearly. Learn how cloud, distributed-processing, and data-pipelining systems support Riot’s games and products. Required Qualifications: Graduating in the 2028 calendar year. Currently enrolled in a Computer Science, Engineering, Data Science, or related technical degree program. Available to work full-time hours for the 12-week internship duration. Comfortable programming in Python or Java. Understanding of data structures and algorithms. Familiarity with SQL and relational data concepts such as tables, keys, normalization, or indexing. Minimum GPA of 2.5. Desired Qualifications: Currently enrolled in a graduate-level (Master’s or PhD) Computer Science, Engineering, Data Science, or related technical degree program. Experience developing a data pipeline, data model, database project, or data-driven application through coursework, internships, research, or personal projects. Familiarity with cloud-computing basics, such as AWS or GCP. Experience working with Linux operating systems. Understanding of distributed systems, concurrent programming, or distributed data processing. Familiarity with tools or frameworks such as Databricks, Spark, Flink, Hive, Kafka, Airflow, Luigi, Docker, Terraform, Kubernetes, Parquet, or Avro. Experience with Scala, C++, Golang, or another programming language. Familiarity with software development practices such as Git, unit testing, functional testing, or continuous integration and deployment. Portfolio, website, GitHub, or other collection of original work. Work Authorization Candidates must be legally authorized to work in the United States for the duration of the program. This position is not eligible for visa sponsorship. We do not sponsor visas for this position or internship conversions. For this role, you’ll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We’ll consider your studies and experience, as well as your personal relationship with games. If you embody player empathy and care about players’ experiences, this could be the role for you! Applications close January 4th, 2027 Our Perks: Riot Internships are paid, and interns can also participate in our 401(k) plan. You can expect in-game perks and the ability to participate in our Play Fund, so you can broaden and deepen your knowledge of our players and community through games. The University Recruiting team also invites you to intern-focused events so you can connect with your fellow interns and Rioters and make the most of your experience. Riot Games fosters a player and workplace experience that values teamwork embodied by the Summoner's Code and Community Code . Our culture embraces differences as a strength, and our values are the guiding principles for how we approach work. We are committed to putting diversity and inclusion (D&I) at the center of everything we do and promoting a fair and collaborative culture where Rioters treat one another with dignity and respect. We encourage you to read more about our value of thriving together and our ongoing work to build the most inclusive company in Gaming . It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act. Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories: Safeguarding confidential and sensitive Company data Communication with others, including Rioters and third parties such as vendors, and/or players, including minors Accessing Company assets, secure digital systems, and networks Ensuring a safe interactive environment for players and other Rioters These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. (Remote Only) The hourly rate for this internship is USD $53.41 - $69.28 hourly

Location: San Jose, California, United States Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Opportunity Building machine learning systems for risk at a global crypto exchange is fundamentally different from conventional ML engineering. The data spans on-chain activity, fiat deposits and withdrawals, trading behaviour, account access patterns, device intelligence, identity information, and customer interactions—signals that very few organizations can analyze together. The problems are complex, adversarial, and constantly evolving. Models must identify emerging fraud patterns, scams, account takeovers, payment abuse, and other forms of financial risk while minimizing disruption to legitimate customers. Success is not measured only through offline model metrics. It is measured through prevented losses, improved approval rates, reduced false positives, faster investigations, and more reliable customer experience. This role sits within a multidisciplinary risk team of machine learning engineers, data scientists, risk strategy specialists, analytics engineers, product managers, and operations teams. You will work across the full ML lifecycle — from problem formulation, feature engineering, and model development to real-time deployment, monitoring, experimentation, and continuous iteration. You will also help shape how AI is used across the risk organization. LLM-assisted development, automated model workflows, AI-powered investigations, and intelligent review agents are part of the team’s daily work. We are looking for engineers who already use these tools effectively and can help establish safe, scalable, and production-ready AI practices. What You’ll Be Doing We’re looking for a Machine Learning Engineer to build models and AI tools that help detect fraud and protect users at a global crypto exchange. You’ll apply deep learning and XGBoost, develop practical AI agents, and use AI coding tools in your daily work. Build, evaluate, and deploy machine learning models for fraud and risk detection. Improve data quality, features, and model performance, balancing fraud detection with customer experience. Develop AI agents to support investigations, summarize cases, retrieve evidence, and automate routine workflows. Use AI coding tools to accelerate development, testing, and debugging while reviewing and validating their output. Work with engineering, product, and risk teams to deploy solutions and monitor their impact. What We Look For In You A strong foundation in machine learning, with hands-on experience in deep learning and tree-based models such as XGBoost or LightGBM. Strong Python skills and experience training, evaluating, and deploying models. Some practical experience building AI agents or LLM applications, including tool calling, retrieval, or workflow automation. Prototypes and personal projects are welcome. Regular use of AI coding tools, with the ability to understand, test, and improve generated code. Familiarity with databases and data pipelines for preparing training data and supporting ML workflows. Good problem-solving, communication, and collaboration skills. Nice to Haves Experience in account takeover (ATO), scam detection, or other fraud and risk use cases. Experience with LLM training, fine-tuning, evaluation, and alignment. Experience with reinforcement learning algorithms and their practical implementation. Experience with real-time ML systems, imbalanced datasets, or model explainability. Prior fraud or risk experience is helpful Perks & Benefits Competitive total compensation package L&D programs for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! OKX Statement: OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. The salary range for this position is $214,666 to $321,999 The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site. #LI-SK1 #LI-HYBRID Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

E2B is looking for a Site Reliability Engineer to build and operate reliable Kubernetes infrastructure, deployment automation, and cloud integrations in customer environments.

SpaceXSI is looking for a Senior Model Engineer Mid Training to scale synthetic training data, optimize mid-training recipes, and develop evaluations.