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Location: Worldwide APPLICATION INSTRUCTIONS: If you’ve already completed the 20four7VA Recruiting Process—including the Final Interview—or have previously been contracted by a 20four7VA Client, please make sure to apply via the 20four7VA Team Portal for faster processing. Log in using your 20four7VA-issued email address to access the portal. If you’ve just logged in to the Team Portal, please proceed to review the Independent Contractor Opportunity outlined below. 💡 Quick Tip: Upload your resume first—this will automatically populate most of the fields in the application form. Let the magic happen! If you're interested in this opportunity, click APPLY TO POSITION to proceed. ******************************************************************** Title: CPT-11491 Credit Operations & Customer Support Virtual Assistant Independent Contractor – CPT-11491 Credit Operations & Customer Support Virtual Assistant/Business Support VAy/Entry-Senior Level (Remote). Overview 20four7VA is seeking offshore independent contractors to deliver remote services to clients worldwide, with a primary focus on developed markets such as the United States, the United Kingdom, Canada, and Australia. An established credit restoration company is seeking a part-time Business Support VA to assist with credit report retrieval, client file management, customer service, reporting, and recurring administrative processing. The company already has established processes, templates, and workflows in place. The immediate priority is removing repetitive, time-consuming backend work from the internal team. As the VA becomes familiar with the company's processes and credit reports, the role may expand into account-update processing and additional customer-facing support. Training will be provided by 20four7VA and the client on specific workflows and Credit education, thus direct Credit repair/education/restoration experience is not required. The objective of each engagement is to assist the client in improving business efficiency, enhancing service delivery, or supporting operational functions through high-quality, task-specific services rendered by a qualified contractor. Scope of Services Contractors will be required to provide services that align with the following client tasks: Credit Report & Client File Support Access client Experian accounts using securely provided credentials Pull and save updated credit reports Follow established procedures for managing applicable Experian account settings Upload reports and supporting files to client profiles Maintain accurate notes using established templates Ensure required client documentation is properly saved and organized Follow up when credentials, PINs, security information, or other required information is missing Prioritize accurate credit-report and client-profile processing during the initial training period. Review assigned tasks and organize work based on priority. Client Updates & Processing Support Assist with recurring client account updates Compare updated credit information using client-provided processes Enter relevant changes into established update templates Prepare client update emails from approved templates Assist with credit-report processing as training progresses Escalate questions or unusual situations to the internal team Maintain processing speed and accuracy as key performance measures. Use client-specific verbiage and scripting when preparing client communications. Customer Service Assist with routine client questions and follow-up Provide professional, careful communication using established scripts and templates Route incoming calls to the appropriate team member Support additional phone responsibilities as the VA becomes trained Avoid providing information outside approved company processes Maintain a customer-service approach appropriate for sensitive credit-related conversations Conduct outbound calls to warm referral leads as training progresses. Support inbound and outbound customer-service calls using approved scripts. Handle referred leads who may not initially answer, respond, or show interest. Reporting & Administration Prepare recurring pipeline reports for referring affiliates Enter and update report information using existing templates Maintain organized client records and administrative files Assist with other repetitive backend tasks as assigned Help ensure recurring reporting and follow-up deadlines are completed Participate in regular team meetings on Monday, Wednesday, and Friday at 9:00 AM MST. Use time-blocking to prioritize daily tasks and workload. Each engagement is based on a defined scope of work and is governed by an independent contractor agreement. Services must be performed professionally, with adherence to any timelines, guidelines, and deliverables agreed upon in writing. Skills The Contractor must demonstrate proficiency in the following, depending on the Client’s requirements: Previous customer service, administrative, or account-support experience required Strong spoken and written English required Data entry and document-management experience required Experience following detailed processes and templates Credit education, credit restoration, credit restoration, financial services, or similar experience is a plus but not required Experian experience is a plus CRM or client-portal experience preferred Previous successful 20four7VA experience is a plus IDEAL CANDIDATE PROFILE Highly detail-oriented and accurate Strong customer-service background Comfortable handling repetitive, process-driven work Able to follow established templates and procedures Strong comprehension and learning ability Professional and careful when communicating with clients Comfortable learning how to read and understand credit reports (training provided) Organized and dependable Able to grow from backend processing into client-facing responsibilities APPLICATION SOFTWARE KNOWLEDGEABLE / REQUIRED Credit Repair Cloud – Client System (training provided) Experian Dialpad (Voip phone system) Email / Client Communication Platforms Microsoft Office / Google Workspace VPN / Secure Access Tools – 20four7VA IT to assist in setup Work Schedule Contracted Hours per Week: 20 Hours (Hours may increase based on performance and workload) Scheduled Working Days: Monday through Friday (unless otherwise mutually agreed in writing) Daily Working Time: 8:00 AM – 12:00 PM MST Note: The Company will make reasonable efforts to align the Assigned VA’s schedule with the Client’s preferred hours as set forth above. However, availability may vary based on time zones, capacity, and the contracted hours set in this SOW. Any changes must be mutually agreed to in writing through a revised SOW. Terms of Engagement Contractors will operate under a Master Services Agreement and a Statement of Work This is not an offer of employment; contractors are not employees of 20four7VA or any client All compensation is processed through 20four7VA according to the terms of the engagement Role Summary & Requirements REQUIRED SERVICE: Business Support REQUESTED EXPERIENCE TIER LEVEL: Entry, Junior, Senior Level Contracted Hours per Week: 20 hours/week (Hours may increase based on performance and workload) Daily Working Time: 8 AM-12 PM MST Scheduled Working Days: Monday-Friday REPORTING TO/POC: To Be Determined Number of VAs: 1 GENDER PREFERENCE: None LANGUAGES SPOKEN/PREFERENCE: English ACCENT PREFERENCE:  Level A-B (Native or Near-Native English Accent Required) REGION PREFERENCES: Any What we offer Competitive rates Weekly payments Various open roles are available Free training and upskilling Constant support and guidance A vibrant community always ready to support you And more!

Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Remote Workplace: Remote WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: London Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Санкт-Петербург Workplace: гибкий Крупнейший российский видеосервис: ежедневно им пользуются десятки миллионов людей. Перед нами стоит амбициозная задача — развивать видеосервис № 1 в России и внедрять новые технологии. Задачи Разработка и оптимизация Android-приложений с использованием Java/Kotlin Работа с видеотехнологиями: обработка видео, кодирование/декодирование, трансляции, стриминг Оптимизация производительности мультимедийных компонентов и управление ресурсами Взаимодействие с командами backend и QA для обеспечения качества продукта Проектировании архитектуры мультимедийных решений Анализ и устранение багов, профилирование кода Дизайн и верификация метрик и статистики Требования Уверенные знания Android SDK, Java и (или) Kotlin Умение строить, верифицировать, доказывать и опровергать гипотезы безопасно для продукта Декомпозиция, планирование и исполнение сложных задач Сильные навыки проектирования библиотек для мобильных платформ: поддержка обратной совместимости, наблюдаемости, версионирования, отказоустойчивости и так далее Развитие крупных сегментов функциональности в самостоятельном режиме: выбор ориентированного на бизнес направления развития компонента Будет плюсом Глубокие знания видеотехнологий: кодеки (H.264, H.265), форматы видео, протоколы потоковой передачи (RTMP, WebRTC и тому подобное) Опыт работы с мультимедийными библиотеками (FFmpeg, OpenGL, Vulkan или аналогичными) Навыки оптимизации производительности и работы с мультимедийными потоками Знание систем сборки (Gradle, CMake) и отладки нативного кода Опыт работы с live streaming и broadcast решениями

Разрабатывать и поддерживать backend-сервисы и REST API на C# и .NET. Развивать frontend-приложения на современных JavaScript/TypeScript-фреймворках.

Задачи: — Проектировать, разрабатывать и поддерживать backend-сервисы и REST API на C# и .NET — Развивать frontend-приложения на современных JavaScript/TypeScript-фреймворках — Проектировать и использовать API, интегрировать сторонние и локальные российские сервисы — Разворачивать и эксплуатировать приложения в облаке (Azure/AWS или российские облачные провайдеры) — Писать чистый, тестируемый и документированный код, участвовать в код-ревью — Работать в связке с продакт-менеджерами, дизайнерами, QA и DevOps-инженерами — Находить и устранять проблемы производительности, надёжности и безопасности — Участвовать в поддержке CI/CD и инфраструктуры как кода Требования: — 2-4 года коммерческого опыта с C# и .NET (ASP.NET Core) — Уверенное понимание ООП, SOLID, паттернов проектирования и чистой архитектуры — Опыт работы с реляционными БД (SQL Server / PostgreSQL) и ORM (EF Core) — Опыт разработки frontend-приложений на React или Angular (TypeScript) — Базовое понимание облачных платформ (Azure/AWS): вычисления, хранение, сети — Знакомство с Docker и контейнеризацией — Опыт работы с REST API, асинхронным программированием и очередями сообщений — Уверенное владение Git и командными процессами разработки — Свободный русский язык (устная и письменная речь) - обязательное требование для ежедневной работы с командой и заказчиками — Английский на уровне чтения технической документации (A2/B1+) Будет плюсом: — Опыт интеграции с российскими сервисами и системами (1С, ЭДО, платёжные провайдеры, SMS/email-шлюзы) — Опыт работы с российскими облачными провайдерами (Yandex Cloud, VK Cloud, Selectel) — Опыт с микросервисами и распределёнными системами — Знание Kubernetes — Опыт с CI/CD (GitLab CI, TeamCity, Azure DevOps, GitHub Actions) — Знакомство с NoSQL-базами (MongoDB, Redis, Cosmos DB) — Понимание observability (логирование, метрики, трассировка) — Опыт автоматизированного тестирования (xUnit/NUnit, Jest, Playwright/Cypress) Условия: — Конкурентная зарплата в рублях, обсуждается по результатам интервью, регулярный пересмотр — Полностью удалённая работа — Оплачиваемый отпуск, оплачиваемые больничные — Дружная русскоязычная команда, код-ревью и менторство

Location: Москва Workplace: гибкий Инфраструктурная команда Core Backend отвечает за надёжность ВКонтакте, разрабатывает HighLoad core-сервисы, которые находятся на стыке продукта и инфраструктуры — от них зависят многие сценарии продуктовой разработки. Также мы являемся одним из главных драйверов по распилу монолита. В настоящий момент мы переходим от монолитной архитектуры к сервисной и одним из ключевых компонентов становится API Gateway как решение, обеспечивающее набор базовых операций с запросом пользователя и перенаправляющее его в нужный внутренний сервис или набор сервисов. Наш стек: Go, а также большое количество внутренних решений. Задачи Развитие API ВКонтакте и повышение надёжности платформы Проектирование и развитие механизмов устойчивой работы при сбоях и повышенной нагрузке Анализ инцидентов, поиск первопричин и внедрение системных улучшений Развитие инструментов безопасной доставки и применения конфигураций Улучшение наблюдаемости платформы: метрики, логи, алерты и средства диагностики Развитие взаимодействия gateway с внутренними сервисами и облачной инфраструктурой Участие в архитектурных решениях для высоконагруженной платформы Требования Уверенное владение Go Опыт разработки и эксплуатации высоконагруженных backend-систем Опыт работы с контейнерами и оркестраторами, например Kubernetes Понимание облачной инфраструктуры и принципов построения распределённых систем Знание SRE-практик: мониторинг, управление инцидентами, надёжность, отказоустойчивость, безопасные изменения в production Опыт работы с реляционными или NoSQL-БД, а также системами кеширования Будет плюсом Опыт разработки платформенных или инфраструктурных продуктов Опыт проектирования систем, критичных к доступности и производительности Навыки performance-инжиниринга, поиска узких мест и планирования ресурсов Опыт улучшения процессов эксплуатации и автоматизации рутинных операций

— Тестирование микросервисной архитектуры: функциональное, интеграционное и E2E. — Написание ручных и автоматизированных тестов на Java.

Location: London; Belgrade Workplace: Hybrid About the role Perplexity's fraud prevention team protects our products, users, and infrastructure from fraud and abuse across the whole lifecycle: sign-up, authentication, payments, API usage, and product features. We build and operate a real-time decisioning platform together with the surrounding systems: data pipelines for detection and model training, integrations with product and payment systems, and internal tooling for investigation and response. As a software engineer on the team, you will own services end to end, from design to production operations, and work closely with fraud analysts, ML engineers, and product teams to make abuse expensive and legitimate usage frictionless. Responsibilities - Design, build, and operate high-throughput, low-latency backend services for fraud detection and prevention - Build data pipelines and real-time feature computation that power detections and ML models - Collect and process trust signals - Integrate fraud decisions into product, auth, and payment flows across Perplexity - Own reliability of production services: observability, alerting, safe rollouts, incident response - Build internal tooling for investigation, enforcement, and auditability - Partner with fraud analysts to turn new abuse patterns into production detections quickly Qualifications - 5+ years building and operating high-throughput, latency-sensitive backend systems in production - Strong systems programming skills; Rust, Go, or C++ experience preferred (we write Rust) - Hands-on experience with Kubernetes, Terraform and cloud infrastructure - Solid data fundamentals: stream/batch computations, caching and storage trade-offs - Pragmatic, ownership-driven approach: ship incrementally, measure, and make failures degrade safely Nice to have - Fraud prevention, anti-abuse, or payments-risk domain experience - Experience serving ML models in production - Client-side experience (web or mobile) for signal collection

Развивать конвейер обработки товаров: получать данные и фотографии, разбирать текстовые задания, анализировать изображения и собирать карточки. Интегрировать языковые и мультимодальные модели, сервисы сегментации и генерации изображений.

Workplace: Удалённый, Офис, Гибридный Команда экспериментальных финтех‑проектов создаёт финансовый сервис на базе AI‑агентов. Мы ищем AI Engineer с опытом коммерческой разработки от пяти лет. Вам предстоит разрабатывать агентные сценарии, интегрировать LLM с сервисами и данными, проверять гипотезы и доводить решения до запуска. Мы — команда экспериментальных финтех‑проектов в Яндексе, создаём финансовый сервис на базе AI‑агентов. Наша задача — превратить возможности языковых моделей в работающий продукт. Ищем AI Engineer. Вам предстоит разрабатывать агентные сценарии, интегрировать LLM с сервисами и данными, проверять гипотезы и доводить решения до запуска. Работа затронет весь пользовательский сценарий: от взаимодействия с AI до изменений в бэкенде и мобильном приложении. Мы ценим самостоятельность, короткие итерации и готовность экспериментировать. У вас будет возможность влиять на технические решения и развитие продукта. Обязанности Разработка AI-агентов Вы будете проектировать и создавать AI-агентов: подбирать инструменты, настраивать контекст и прорабатывать логику взаимодействия с сервисами, чтобы агенты решали задачи пользователей. Интеграция языковых моделей Вы будете встраивать языковые модели в сценарии продукта, создавать нужные серверные компоненты и соединять их с мобильным приложением. Оценка качества Вы будете оценивать ответы и действия агентов, составлять проверочные сценарии, разбирать ошибки и дорабатывать решения, чтобы повысить их надёжность. Проверка гипотез Вы будете быстро собирать MVP и проверять работу новых решений на практике. Успешные эксперименты нужно будет развивать и превращать в полноценные фичи продукта. Разработка с применением AI‑инструментов Вы будете применять AI‑инструменты в разработке, сохраняя контроль над архитектурой и качеством кода. Больше о бэкенде в Яндексе — в канале Yandex for Backend Требования * Имеете больше пяти лет опыта коммерческой разработки: мобильных приложений, бэкенда, ML, инфраструктуры * Работали с LLM и создавали решения на их основе * Понимаете, как организовать контекст модели, вызовы инструментов и проверку результатов * Умеете проектировать сервисы и API, писать код, готовый к эксплуатации * Используете AI‑агентов для разработки и умеете проверять результаты их работы * Готовы разбираться в разных компонентах продукта и самостоятельно доводить задачи до результата * Умеете выбирать достаточное решение для эксперимента и понимаете, что потребуется для его масштабирования Будет плюсом * Запускали и развивали AI‑продукты с реальными пользователями — от прототипа до промышленной эксплуатации * Разрабатывали многошаговые агентные сценарии с управлением контекстом, состоянием диалога и вызовами инструментов * Создавали автоматизированную оценку качества агентов: тестовые наборы, сравнение моделей и промптов, выявление регрессий * Оптимизировали LLM‑приложения по качеству, скорости ответа и стоимости работы * Разрабатывали сервисы на Kotlin или Java, работали с асинхронной обработкой данных и событийной архитектурой * Имеете опыт фулстек‑разработки — от интерфейса до инфраструктуры

Задачи: — Выполнение системного анализа требований, включая BRD, FRD, SRS, Use Cases и User Stories — Моделирование бизнес-процессов с использованием UML, AS-IS / TO-BE — Проектирование и описание данных через ER-диаграммы и логические модели — Анализ данных и требований в реляционных и нереляционных базах данных — Работа с интеграциями через REST API, форматы обмена и спецификации OpenAPI — Декомпозиция сложных бизнес-задач до технических требований — Чтение и написание аналитических SQL-запросов — Взаимодействие с большим количеством стейкхолдеров — Описание требований к ML и аналитическим компонентам — Построение экономических обоснований (ROI, TCO, cost-to-serve) — Анализ данных для валидации гипотез Требования: — Гражданство и локация РФ — Опыт работы в бизнесе в сфере ритейла и производства на роли бизнес/системного аналитика — Опыт работы в консалтинге в сфере управления цепями поставок и ритейла на роли бизнес/системного аналитика — Знание стека: Knowledge Space, Optimacros, Novo BI, Jume, Reshape — Опыт работы системным аналитиком от 5 лет — Желателен совмещённый опыт системного и бизнес-анализа — Опыт работы с аналитическими платформами, корпоративными системами или системами планирования — Опыт участия в сложных проектах с большим количеством данных и интеграций — Понимание событийных интеграций — Высшее образование в области информационных технологий, математики, экономики или прикладных наук — Навыки фасилитации — Опыт в Supply Chain, Demand Planning, Forecasting, ERP, APS — Опыт работы в продуктовых командах с Agile и Scrum — Понимание процессов Supply Chain Planning, S&OP, Demand Sensing — Понимание задач линейной и смешанно-целочисленной оптимизации, LP, MILP — Базовое понимание методов Operations Research для взаимодействия с разработчиками алгоритмов — Владение инструментами моделирования: Draw.io, PlantUml, Miro или аналоги — Опыт работы с Яндекс.Трекером Axenix, Яндекс.Вики Axenix или Jira, Confluence — Базовое понимание архитектуры web-приложений, backend-сервисов и ML-конвейеров — Владение инструментами бизнес-анализа: gap-анализ, моделирование бизнес-объектов — Наличие сертификаций по системному или бизнес-анализу (IIBA CBAP, CCBA, курсы по BABOK) — Обучение в области Supply Chain, Demand Planning, Operations Research Условия: — Удалённая работа — Полная занятость (full-time)

We're looking for a Senior Product Engineer* who combines building software with coaching and direct people management. You'll write and review code, grow mainly junior and mid level engineers, and take responsibility for their feedback, performance, and career development.

Location: Canada; Uruguay; Costa Rica; Colombia; Argentina; Paraguay; South Africa; Panama; Mexico; Chile 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. We’re looking for a hands-on Engineering Manager to lead a cross-functional Consumer pod focused on building and scaling core Krak experiences. This leader will guide a team of Frontend (React / React Native) and Backend (Rust) engineers to deliver seamless, performant user experiences across Kraken’s primary consumer surfaces. You’ll work closely with Product, Design, and other Engineering Managers to ensure Krak delivers exceptional UX, technical quality, and operational reliability. This role is an opportunity to shape high-impact, consumer-facing functionality used daily by a global user base. THE OPPORTUNITY - Lead a cross-functional team of frontend and backend engineers responsible for core Krak consumer experiences. - Own the end-to-end UX for key Krak features across mobile and client platforms. - Guide the delivery of high-quality consumer applications, with a focus on usability, performance, and scale. - Partner with Product Managers and Designers to define and deliver high-impact features with measurable business and customer value. - Collaborate with other Engineering Managers and Tech Leads to maintain consistent engineering standards across services and client platforms. - Champion engineering excellence, maintainable architectures, and code quality. - Mentor engineers and foster a culture of technical growth, collaboration, and inclusivity. - Strengthen team organization and delivery using agile processes, project tracking, and engineering metrics (e.g., DORA, cycle time). SKILLS YOU SHOULD HODL - Proven experience leading engineering teams delivering customer-facing products at scale. - Experience managing combined frontend and backend engineering teams. - Deep technical background in React Native with a solid understanding of modern frontend architectures. - Strong cross-functional leadership, able to align frontend and backend efforts in a complex, multi-platform environment. - Excellent communication and stakeholder management skills. - Empathy for the customer and a passion for building intuitive, performant consumer experiences. - Experience building large-scale consumer or financial products. NICE TO HAVES - Background in systems design or distributed architectures. - Working knowledge of Rust (or similar languages such as Go or C++), and familiarity with async architectures, APIs, and microservices. - Experience in the payments and card domains. 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: Москва Workplace: Офис, Гибридный Яндекс ID — одна из ключевых инфраструктурных систем Яндекса. Через неё проходят аутентификация и авторизация пользователей и сервисов, а от её работы напрямую зависит доступность большого количества продуктов компании. Система ID построена на нескольких критически важных инфраструктурных компонентах — среди них Паспорт, Blackbox, TVM и прокси. Уровень надёжности таких систем должен быть очень высоким: мы стремимся довести доступность до 99,99–99,999% там, где это возможно технически. А в тех случаях, когда это неосуществимо, — разобраться в фундаментальных ограничениях и сделать реальную надёжность как можно выше. Мы ищем опытного технического лидера. Вместе с CTO Яндекс ID вам предстоит работать над повышением надёжности платформы. Роль сочетает в себе глубокую инженерную работу, практику SRE и задачи технического лидерства. Вам нужно будет участвовать в формировании архитектуры систем, совершенствовать инженерные практики команды и развивать подходы к обеспечению надёжности критичных сервисов ID. Обязанности Обеспечение надёжности Паспорта Вы будете техническим партнёром CTO по вопросам надёжности. Вам предстоит помогать принимать архитектурные решения, выявлять системные риски, разбирать сложные инциденты и оценивать, какие инвестиции в надёжность принесут наибольший эффект. Также вы станете ментором и дополнительным экспертом для команд, которые отвечают за критически важные компоненты ID. Надёжность компонентов Яндекс ID Вы будете детально изучать работу Blackbox, TVM, Паспорта и прокси. Вам нужно будет выявить основные причины сбоев и ограничения текущей архитектуры, а затем разработать программу, которая повысит их надёжность. Цель — добиться доступности критичных компонентов на уровне 99,99–99,999% там, где это возможно технически. При этом главное — не просто достичь высоких показателей, а обеспечить реальную надёжность: чтобы система устойчиво работала при сбоях инфраструктуры и зависимостей, позволяла локализовать аварии, продолжала функционировать при частичных отказах и автоматически восстанавливала работу. Развитие SRE‑подхода Вы будете вместе с командой развивать подходы к обеспечению надёжности критичных сервисов Яндекс ID: автоматизировать эксплуатационные задачи, улучшать инструменты и процессы, развивать инфраструктурную разработку. Важно помогать команде находить системные решения проблем надёжности, сокращать объём ручной работы и постепенно наращивать инженерные практики и экспертизу внутри службы. Больше о бэкенде в Яндексе — в канале Yandex for Backend Требования * Работали с SRE-практиками * Обладаете сильным инженерным бэкграундом и работали с высоконагруженными распределёнными системами * Глубоко понимаете принципы построения отказоустойчивых систем и умеете находить не только отдельные проблемы, но и системные ограничения надёжности * Можете самостоятельно погрузиться в большую существующую систему и разобраться в её архитектуре, зависимостях и классах отказов * Знаете, что такое техническое лидерство, и можете влиять на несколько команд без необходимости напрямую управлять каждым инженером * Умеете превращать большие и плохо определённые проблемы в конкретную инженерную программу * Можете одновременно работать на уровне архитектуры системы и погружаться в детали конкретного инцидента или компонента * Умеете аргументировать технические решения и договариваться с сильными инженерами и руководителями Будет плюсом * Отвечали за надёжность критичных инфраструктурных систем * Строили системы с требованиями доступности 99,99% и выше * Работали над разработкой инфраструктурных систем и хорошо пишете код

Location: Remote; Croatia; Hungary; Switzerland; Poland; United Kingdom Workplace: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual team offsite: Each year, we bring your entire team together in a new location - past offsites have included Croatia, Italy and Cancún - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE ElevenMusic is a consumer music app where music is the core product: a place to listen, create, remix and share. The team is small, agent-first and sits apart from the main org, with very fast CI, so ideas often ship the same or next day. Today, one engineer runs the whole iOS app alone. We’re looking for a Mobile Engineer to own ElevenMusic across iOS and Android, and to make mobile a driver of the product rather than a downstream port of web features. You’ll build for musicians and creatives, think in systems as well as screens, and work with high autonomy and a high bar for taste. Requirements - Shipped a well-designed, production mobile app that real users love, and can show us what you owned. - Strong systems thinking across mobile and backend. We’re framework-agnostic (Swift UI or Kotlin Jetpack Compose), but expect you to work across iOS and Android. - Exceptional product taste and a clear view on what makes a mobile experience great. - Highly self-directed: you turn loose directions into shipped work and own the outcome. Bonus: musical interest or intuition. Open-source or GitHub contributions. Location This role is remote-first, so it can be executed from anywhere in Europe and the US East Coast, with the ability to operate in GMT-5 to GMT+1 timezones required. If you prefer, you can work from our offices in London, New York, Warsaw, and Amsterdam. #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.