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🔹Опыт работы в области тестирования программного обеспечения минимум 2 года.

Location: Россия Workplace: Москва и Краснодар (гибрид/офис), другие города - удаленно Мы в поиске талантливого Fullstack разработчика в команду Магнум. Мы работаем над внутренним корпоративным порталом Магнум. Большая система, обеспечивающая мониторинг перформанса всех сотрудников компании, их обучение, ревью, оценки работы и карьерный рост. Команда: TL, PM, 5 fullstack разработчиков, дизайнер, 6 СА. Стек технологий: HTML, CSS, JS, Vue.js, TS, MS SQL, WebTutor. Задачи Разрабатывать бизнес-логику ПО и программный код (frontend, backend, запросы к БД) Взаимодействовать с системными аналитиками и сопровождением Описывать техническое решение по разрабатываемому ПО Писать шаблоны под мобильное приложение WebTutor Требования Коммерческий опыт разработки на Vue3 от 3-х лет Коммерческий опыт разработки backend от 2-х лет Опыт разработки с SQL более 1 года – не ORM, а написание SQL-команд Опыт работы с Git Будет плюсом Опыт работы с WebTutor Условия Оформление в аккредитованную ИТ-компанию Конкурентоспособную заработную плату (обсуждается индивидуально) ДМС со стоматологией и льготными условиями для членов семьи Технику для работы График работы 5/2 Работу в максимально уютном офисе в центре Москвы (ст. м. Савеловская), в Краснодаре или удаленно из других городов РФ, так же есть офисы в Санкт-Петербурге (ст. м. Балтийская) и в Иннополисе Возможность реализовать свой опыт и потенциал в интересных и многоплановых проектах Развитие – мы оплачиваем обучение на курсах и участие в конференциях Возможность проведения и участия в митапах, хакатонах, где есть возможность познакомиться с работой других подразделений Наличие корпоративных скидок PRIMEZONE и программ лояльности от компании Наличие корпоративной библиотеки курсов Возможность рекомендовать компанию своим друзьям, участвуя в реферальной программе Формат работы Москва и Краснодар (гибрид/офис), другие города - удаленно

Workplace: Москва и Краснодар (гибрид/офис), другие города - удаленно О продукте Новое направление для ускоренного прототипирования и внедрения AI/ML-решений внутри Магнита. Заказчики — команда стратегии и аналитики. Модель работы: бизнес приносит POC и решения, а мы дорабатываем их до продуктового состояния и запускаем в production. Задачи Развивать ML/AI-компоненты для прикладных бизнес-задач в направлениях классического ML, NLP/LLM, RAG и агентных сценариев, компьютерного зрения, речевых и мультимодальных технологий. Проводить эксперименты по улучшению существующих моделей и сценариев: изменять подготовку данных, архитектуру или параметры моделей, подходы к retrieval и reranking, промпты, логику оркестрации, алгоритмы постобработки результатов. Подготавливать, очищать, размечать и анализировать данные для обучения, дообучения и оценки моделей: текстовые, табличные, изображения, видео, аудио, транскрипты и иные данные в зависимости от решаемой задачи. Разрабатывать и поддерживать пайплайны подготовки данных, обучения, inference и evaluation; обеспечивать воспроизводимость экспериментов, версионирование данных и моделей, логирование результатов. Оценивать качество ML/AI-решений: формировать тестовые и evaluation-наборы, выбирать и рассчитывать профильные метрики, проводить анализ ошибок, выявлять причины деградации качества и предлагать улучшения. Оптимизировать производственные решения по качеству, latency, throughput, потреблению GPU/CPU-ресурсов и стоимости эксплуатации; участвовать в интеграции моделей в прикладные сервисы, релизах и мониторинге после запуска. Требования Высшее техническое образование либо подтверждённый практический опыт разработки и внедрения ML/AI-решений. Опыт коммерческой разработки на Python от 2 лет; для кандидатов с общим опытом разработки от 3 лет допустим опыт в ML/AI от 1–2 лет при наличии практических проектов. Уверенное знание Python и основных библиотек для анализа данных и машинного обучения: NumPy, pandas, scikit-learn; практический опыт работы с PyTorch или аналогичным DL-фреймворком. Знание базовых методов машинного обучения и глубокого обучения: подготовка и анализ данных, обучение и валидация моделей, выбор метрик, борьба с переобучением, анализ ошибок и интерпретация результатов экспериментов. Практический опыт работы как минимум с одним из направлений: классический ML, NLP, LLM/RAG-системы, компьютерное зрение, речевые технологии, рекомендательные системы или мультимодальные модели. Понимание полного жизненного цикла ML/AI-решения: сбор и подготовка данных, разработка и проверка гипотез, обучение или адаптация модели, оценка качества, inference, интеграция в сервис, мониторинг и последующее улучшение. Опыт проведения воспроизводимых экспериментов: фиксация конфигураций, версий данных и моделей, метрик и результатов; знание MLflow, ClearML, DVC или аналогичных инструментов будет преимуществом. Навыки работы с SQL и реляционными базами данных; понимание принципов хранения, выборки и проверки качества данных. Понимание принципов разработки и интеграции сервисов: REST API, JSON, FastAPI или аналогичные фреймворки, обработка ошибок, логирование, тестирование. Базовые практические знания Docker, Linux, Git и CI/CD; понимание особенностей запуска и отладки ML-нагрузок в контейнерах. Понимание принципов работы с GPU и ограничений inference-нагрузок: latency, throughput, потребление памяти, стоимость вычислений. Умение формализовать бизнес-задачу в виде ML/AI-сценария: определить входные и выходные данные, целевую метрику, ограничения, риски, критерии приемки и способ оценки результата. Навыки взаимодействия с Product-, Backend-, Data- и MLOps-разработчиками; умение понятно документировать результаты экспериментов, технические ограничения и ожидаемый эффект от изменений. Условия Трудоустройство в аккредитованную IT‑компанию ДМС со стоматологией и льготными условиями для членов семьи Работу в максимально уютном офисе в центре Москвы (ст. м. Савеловская), в Краснодаре или удаленно из других городов РФ, так же есть офисы в Санкт-Петербурге (ст. м. Балтийская) и в Иннополисе Корпоративные скидки от компании и партнеров, бесплатная подписка Магнит Премиум с повышенным кешбэком по программе лояльности М+ Ежегодная программа признания с ярким праздником и впечатляющим подарком Поддержку в развитии через обучение, конференции и митапы, а также программу для руководителей — Leadership club IT‑комьюнити — среда, где быстрее находишь решения, делишься практиками, пробуешь новые роли и растешь от эксперта в стекe до лидера инициатив Мы являемся партнером Минцифры России по проекту Национальная система подтверждения IT‑компетенций Работа над масштабными продуктами и проектами (Умный магазин, роботизация, беспилотность, GenAI и другое) Социально– психологическая поддержка от >370 специалистов по направлениям: юристы, психологи, врачи, финансовые и ЗОЖ советники Формат работы Москва и Краснодар (гибрид/офис), другие города - удаленно

Workplace: Удаленно Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Обязанности Разрабатывать и поддерживать автотесты: API, интеграционные, E2E, регрессионные; Построение процессов тестирования, с использованием ИИ; Проектировать тестовую стратегию и тестовые сценарии для файлового хранилища; Проверять работу с большими и мелкими файлами, параллельными загрузками, версиями, удалением и восстановлением данных; Тестировать разграничение прав доступа, аудит действий, безопасность файловых операций; Проверять отказоустойчивость: сетевые сбои, недоступность сервисов, частичные ошибки загрузки, повторные операции; Интегрировать автотесты в CI/CD, анализировать нестабильные тесты и качество релизов; Работать вместе с backend-разработчиками, DevOps, аналитиком и ручными тестировщиками; Участвовать в разборе инцидентов и улучшении процессов качества. Требования Понимание кода написанного на GO; Умение писать скрипты Python/GO/bash; Опыт работы с брокерами сообщений Kafka; Опыт работы с ETCD/ClickHouse/PG; Опыт работы с Grafana K6; Опыт работы с ELK; Опыт работы с docker; Понимание основных принципов работы REST API. Опыт работы с S3; Тестирование файловых хранилищ; Опыт построения процессов тестирования с использованием ИИ. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.

Workplace: Удаленно Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Наша команда развивает направление цифровых активов, и мы в поиске QA инженера. Обязанности Построение автотестирования для backend-сервисов; Тестирование финансовой логики (балансы, комиссии, расчёты); Проверка торговых сценариев и стратегий; Тестирование асинхронных процессов и event-driven систем; Проверка идемпотентности и устойчивости API; Contract testing (API, protobuf/gRPC); Анализ edge-case сценариев, приводящих к финансовым потерям; Участие в проектировании тестируемых решений. Требования 5+ лет в автоматизации тестирования; Опыт тестирования backend и API; Опыт работы с асинхронными системами; Умение тестировать race conditions и idempotency; Уверенные знания SQL; Опыт в crypto / trading / fintech. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.

Workplace: Удаленно Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Обязанности Работать с обращениями - диагностика, решение, маршрутизация, проработка плана по автоматизации процессов; Оперативно принимать организационные решения для скорейшего устранения инцидентов; Работать с инцидентами - диагностика, эскалация, координирование, инцидент-менеджмент (любой инцидент фиксируется и прорабатывается с целью исключить повторение проблемы); Работать с системами мониторинга; Формировать базу знаний и инструкции для поддержки; Участвовать в приеме новых проектов \ процессов \ сервисов в поддержку; Автоматизировать все рутинные \ повторяющиеся задачи; Формировать выборки и отчеты с помощью SQL-запросов; Ставить задачи на команды разработки c дальнейшей приоритизацией; Применять Postman\Swagger. Требования ​​​Имеете опыт работы в поддержке L2 от года (плюсом будет опыт работы в логистике e-com); Имеете опыт продуктовой поддержки; Понимаете принципы работы backend и frontend веб-приложений; Понимаете принципы работы SOAP веб-сервисов и REST API; Имеете базовое знание SQL, опыт работы с СУБД PostgreSQL, MySQL, MS SQL, или Oracle SQL; Умеете работать с логами в Kubernetes. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.

Location: Remote Canada At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Card Experiences team builds the product surfaces that make the Affirm Card feel simple and trustworthy. We own the cardholder journey from the moment a card is ordered to every time it's used. Our work spans the full stack: customer-facing web and mobile experiences and the backend services behind them. You'll work closely with product, design, risk, and operations partners to turn customer pain points into shipped improvements, and use data to measure their impact. You'll own features end to end, from shaping the problem to launching and monitoring in production, and you'll help raise the bar on reliability and on-call health. AI is central to how we work. We use it to build faster, to improve the quality of what we ship, and to create smarter, more helpful customer experiences. We lead from the front on adopting it, while holding a high bar on security and craft. A card is a high-trust product, so speed never comes at the expense of quality. If you want to help change how people plan their purchases, with a customer-first mindset and an eye for both speed and craft, we'd love to meet you. What You'll Do You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, policies, testing and alerting in place to support “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For This is a full stack role. You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes. You have a total of 8+ years of experience as a software engineer. You are proficient in developing web apps using declarative UI frameworks like React Native or React or Vue. You are proficient in designing, developing and launching systems at scale. You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others. You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work. You think AI first and an adopter of latest technologies. You identify trends and safely apply them to the work. Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. Base Pay Grade - P Equity Grade - 7 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). CAN base pay range per year: CAD $181,000 - $241,000 Location - Remote Canada This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Remote US At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Card Experiences team builds the product surfaces that make the Affirm Card feel simple and trustworthy. We own the cardholder journey from the moment a card is ordered to every time it's used. Our work spans the full stack: customer-facing web and mobile experiences and the backend services behind them. You'll work closely with product, design, risk, and operations partners to turn customer pain points into shipped improvements, and use data to measure their impact. You'll own features end to end, from shaping the problem to launching and monitoring in production, and you'll help raise the bar on reliability and on-call health. AI is central to how we work. We use it to build faster, to improve the quality of what we ship, and to create smarter, more helpful customer experiences. We lead from the front on adopting it, while holding a high bar on security and craft. A card is a high-trust product, so speed never comes at the expense of quality. If you want to help change how people plan their purchases, with a customer-first mindset and an eye for both speed and craft, we'd love to meet you. What You'll Do You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, policies, testing and alerting in place to support “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For This is a full stack role. You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes. You have a total of 8+ years of experience as a software engineer. You are proficient in developing web apps using declarative UI frameworks like React Native or React or Vue. You are proficient in designing, developing and launching systems at scale. You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others. You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work. You think AI first and an adopter of latest technologies. You identify trends and safely apply them to the work. Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. Base Pay Grade - P Equity Grade - 13 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA Pacific base pay range (CA, WA, NY, NJ, CT): $230,000 - $290,000 USA Sapphire base pay range (all other U.S. states): $204,00 - $264,000 #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: AU: Sydney (45 Clarence St); AU: Melbourne: (260 Burwood Rd) Workplace: Hybrid The role You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship. You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team. Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across Xero to make data usable and systems dependable.   The team You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business. Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses. The team is currently working on - Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production. - JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences. - Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks. - XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale. - End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.   Where and how you can work Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively. Here are some of the things we are looking for - A track record of designing, shipping and operating production-grade backend systems at scale - Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management) - Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs - Experience running services in production, including on-call and incident response - Solid SQL and experience with large-scale data processing - Excellent communication, with the ability to explain complex technical concepts to business and technical audiences - A coaching mindset and the ability to set engineering standards and mentor other engineers Nice to have - Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines) - Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask)   Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: AU: Sydney (45 Clarence St); AU: Melbourne: (260 Burwood Rd) Workplace: Hybrid The role You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship. You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team. Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across Xero to make data usable and systems dependable.   The team You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business. Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses. The team is currently working on - Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production. - JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences. - Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks. - XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale. - End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.   Where and how you can work Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively. Here are some of the things we are looking for - A track record of designing, shipping and operating production-grade backend systems at scale - Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management) - Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs - Experience running services in production, including on-call and incident response - Solid SQL and experience with large-scale data processing - Excellent communication, with the ability to explain complex technical concepts to business and technical audiences - A coaching mindset and the ability to set engineering standards and mentor other engineers Nice to have - Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines) - Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask)   Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: Remote.AR, Remote.LATAM-country; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for an experienced Frontend Developer to join our engineering team working on a large‑scale cloud product. In this role, you will collaborate closely with product managers, designers, developers, QA engineers, and technical writers to deliver high‑quality features and improve the user experience for a widely used enterprise solution. We are especially interested in someone who focuses on solving real user problems. Develop clean, maintainable, and testable client‑side code using TypeScript, JavaScript, and modern frameworks Build and maintain unit tests; occasionally contribute to integration or performance testing Participate in code reviews and follow best engineering practices Work on complex technical challenges with a strong focus on performance, usability, and security Collaborate with cross‑functional teams to design, implement, and improve product features Maintain high quality standards across the codebase 4+ years of experience in frontend development in commercial projects At least 1 year of experience with React and TypeScript Strong knowledge of JavaScript, TypeScript, HTML5, CSS3 Experience building complex user interfaces Understanding of API design and integration Experience with performance optimization Upper‑intermediate English (spoken and written) Strong communication skills and ability to work in a distributed, multicultural team Ability to work independently and take ownership of tasks, even with incomplete specifications Willingness to learn and effectively communicate about unfamiliar technical topics Degree in Computer Science or related field, or strong understanding of CS fundamentals Experience with Java or backend development

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.BR, Brazil; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for a QA Engineer to join a team supporting an AI platform/product team. This role requires a more technical profile than a traditional QA position, with a strong focus on backend systems, API testing, and close collaboration with engineering teams. The ideal candidate has solid quality assurance experience, strong technical capabilities, and preferably a background in software development or SDET practices. This individual will help ensure the quality, reliability, and performance of AI platform services within a rapidly evolving AI environment. Beyond technical expertise, this person is an effective communicator who works well with developers and cross-functional teams, asks for support when needed, adapts quickly to change, and takes initiative to solve problems and improve processes. They thrive in collaborative environments and are motivated to contribute to the success of innovative AI-powered products. Design, develop, and maintain automated test suites using TypeScript and Playwright Create and execute functional, regression, smoke, and end-to-end tests Collaborate with developers and product teams to define test scenarios and acceptance criteria Identify, document, and track defects with clear reproduction steps Maintain and improve test frameworks, test data, and automation best practices Contribute to CI/CD integration for automated test execution Support release validation and quality assurance activities Review application changes and assess test impact Work closely with the team to improve test coverage, reliability, and execution efficiency Strong hands-on experience in QA Automation with TypeScript and Playwright. Experience designing and maintaining automated end-to-end and regression test suites. Solid understanding of software testing principles, QA processes, and defect management. Experience working with web applications, APIs, and modern frontend technologies. Ability to collaborate with developers, product owners, and other team members in an Agile environment. Experience with test framework maintenance, test data management, and CI/CD integration. Strong analytical and problem-solving skills with attention to detail. Good communication skills and ability to document test results and issues clearly. Experience with API testing tools or frameworks Experience with CI/CD tools such as GitHub Actions, Jenkins, or GitLab CI Familiarity with performance or accessibility testing Experience in data, analytics, or BI-related products Experience with test reporting tools and quality dashboards

Location: France; Slovakia; Estonia; Latvia; Slovenia; Czechia 🧭 About RealAdvisor RealAdvisor is one of the leading digital platforms in the European real estate ecosystem. Founded in Switzerland, we now support 7,000+ real estate agencies and attract 10+ million users per year across Europe. We are scaling fast across multiple markets with a clear mission: help real estate professionals grow through data, transparency and smart technology. At RealAdvisor, we value ownership, autonomy and impact. Role Overview We are looking for a business‑oriented Data Scientist to join RealAdvisor. You will consolidate and analyze diverse data sources (product, marketing, transactional), build ML models and experiments to drive subscription growth, and translate insights into concrete product and marketing actions. This is a hands‑on, full‑stack role: you will query databases, run experiments, build models, and present clear data stories to stakeholders. Requirements Key responsibilities Consolidate and aggregate data from product, marketing, CRM, and transactional systems into reliable datasets. Perform product analytics to measure feature usage, user journeys, and retention drivers. Design and run experiments (A/B tests, cohort analysis, population and variation control) to validate hypotheses and measure causal impact. Build ML models for revenue optimization, churn prediction, segmentation, and subscription forecasting. Analyze marketing performance to measure acquisition efficiency, LTV, and campaign ROI. Translate analysis into action: propose product changes, growth experiments, and operational KPIs. Report results using concise dashboards, reports, and data storytelling for non‑technical stakeholders. Work cross‑functionally with product, marketing, engineering, and country managers to standardize metrics and training. Maintain data quality: identify polluted data, propose remediation, and implement robust ETL checks. Required skills and experience 3+ years in data science, analytics. Python and SQL skills for data manipulation, modeling, and production prototyping. Experience consolidating diverse data sources and building reliable analytical pipelines. Experiment design and causal inference methods. Practical ML experience (classification, regression, segmentation) and model evaluation. Product analytics tools experience. Ability to build dashboards and present insights clearly (Looker, Tableau, Power BI, or similar). Business mindset: translates technical results into measurable business outcomes. Proactive: takes initiative, owns end‑to‑end delivery, and can work with limited supervision. Nice to have Experience with subscription businesses and monetization models. Familiarity with marketing attribution and LTV modeling. Frontend or backend dev experience to implement tracking or small UI changes. Knowledge of data engineering tools (Airflow, dbt, Spark). Experience working across international markets and multilingual datasets. Benefits Why Join Us Fully remote. Full-time freelance role. Competitive monthly rate.

Location: São Paulo, Brazil; Buenos Aires, Argentina; Bogotá, Colombia; Lima, Peru New opportunities in Latin America! 🟢 Dev.Pro is a US-based software development company helping tech companies build their products and grow their business. We’re remote-first, and we work with independent contractors in over 55 countries, so you’d be collaborating in a multicultural environment on some really interesting projects. We invite a skilled AI Engineer to join our team in building GPU-accelerated video analytics for real-time safety monitoring across large fleets and industrial environments. In this role, you’ll help design and optimize pipelines that detect and track actionable safety events in high-volume video streams. You’ll work on real-world systems that make an impact, collaborating with engineering and product teams to deliver reliable, high-performance solutions. 🟩 What's in it for you: Collaborate with top engineers on an innovative, technically challenging computer vision project Build impactful systems that enhance safety across large fleets and industrial operations Gain hands-on experience with GPU-accelerated video analytics, temporal tracking, and real-time safety monitoring ✅ Is that you? 7+ years of software engineering experience with strong backend skills 3+ years of experience shipping computer vision solutions to production Strong Python proficiency Experience with OpenCV, PyTorch, async I/O frameworks, and API integrations Hands-on experience with YOLO/Ultralytics or similar object detection frameworks Experience detecting, labeling, and tracking objects in video Solid knowledge of frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregation Experience with GPU inference optimization (batching, stride, TensorRT, CUDA, quantization, throughput tuning) Ability to communicate and collaborate effectively with engineering and product teams Upper-Intermediate+ English level Desirable: Experience with Azure Event Hub, Blob Storage, Application Insights, or similar Familiarity with Docker, cloud deployments, and production monitoring systems Experience in temporal/sequence analysis for event detection Experience with video analytics in safety, compliance, or industrial/transportation environments 🧩 Key responsibilities and your contribution In this role, you’ll develop and maintain robust backend solutions that process video data and deliver actionable insights using pre-trained computer vision models. Develop and optimize GPU-accelerated video inference pipelines for real-time processing Implement, evaluate, and improve object detection models (YOLO or similar) Build temporal smoothing and tracking logic for safety event detection Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services Add metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs Contribute to dataset curation, labeling, and model evaluation; fine-tuning/training as needed Support containerized deployments (Docker) and assist with monitoring and scaling production workload Our next steps: ✅ Submit a CV in English — ✅ Intro call with a Recruiter — ✅ Interview — ✅ Signing the Contract Interested? Find out more: 📋 How to Join Us 💻 LinkedIn Page 📈 Our website 💻 IG Page By submitting application, I've read and agree to the Dev.Pro Private Policy and Consent on Processing of Personal Data . I agree to have my Personal Data being stored and processed by Dev.Pro.

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