Данные и ML вакансии

Location: Barcelona, Spain; Tokyo, Japan; Portland, OR Workplace: onsite About Welocalize  Welocalize, a Welo Global brand, serves localization teams through AI-enabled multilingual content solutions that enable enterprises to operate and scale globally. Welocalize combines AI, automation, and human expertise to support enterprises in more than 300 languages, enabling accurate, culturally aligned, and compliant multilingual content at scale.   Welocalize’s Opal Platform comprises patented technology designed to automate multilingual content and improve workflow performance for enterprises. Opal functions as an agentic system that orchestrates AI, automation, and human expertise to coordinate content workflows across the lifecycle, improving speed, scalability, and operational control for global enterprises. These solutions operate within a secure and compliant environment supported by seven ISO certifications. Welocalize is headquartered in New York with offices worldwide. welocalize.com  ROLE OVERVIEW  Welocalize is looking for a native-level Urdu speaker to join a confidential, large-scale AI and consumer technology programme for a major global technology and communications client.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how the product actually performs on a client-supplied device — a smartphone and a next-generation smart glass. If you enjoy noticing the detail other people miss, this is work you'll find satisfying.  Welocalize is looking for a native-level Urdu speaker to join a large-scale AI and consumer technology programme.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how it performs on a real device. You'll be among the first people to see this technology in Urdu, and your judgement shapes how well it works before anyone else uses it.  If you enjoy noticing the detail other people miss, this is work you'll find satisfying.    MAIN RESPONSIBILITIES  Review pre-release AI model output in Urdu and judge it on accuracy, naturalness, appropriateness, and overall quality — would a native speaker really say it this way? This includes fact-checking each response against the source material.

Nebius is an international cloud technology company that is fully focused on infrastructure for artificial intelligence. Work format: On-site (Israel) or remote work (Europe, United Kingdom).

Компания ВсеИнструментыру приглашает на должность Data Engineer для удалённой работы в России с полной занятостью. Основная задача специалиста — развитие корпоративной платформы данных и хранилища данных (DWH), включая модернизацию ETL-процессов с переходом с SSIS на Apache Airflow 3 и внутренний Python-фреймворк, а также повышение надёжности и удобства работы с данными для аналитических команд. В обязанности входит создание и поддержка устойчивых data-пайплайнов с обеспечением таких функций, как повторные попытки выполнения, backfill, идемпотентность, дедупликация и корректная обработка ошибок. Также требуется развитие проверок качества данных, оптимизация SQL-запросов и работы с Microsoft SQL Server, внедрение CI/CD-процессов для работы с данными, создание переиспользуемых инструментов и self-service решений, а также участие в развитии архитектуры DWH и методик моделирования данных. Кандидат должен иметь не менее трёх лет опыта работы Data Engineer, уверенные навыки SQL и опыт работы с Microsoft SQL Server, владение Python с применением ООП, модульной архитектуры, type hints, тестирования, логирования, работы с REST API и базами данных. Необходим опыт работы с Apache Airflow или аналогичными промышленными оркестраторами, знание dbt или похожих SQL-трансформационных фреймворков, понимание ETL/ELT процессов, batch и near-real-time обработки, умение строить отказоустойчивые data-пайплайны, опыт работы с Git и CI/CD, а также реализация проверок качества данных. Требуется понимание архитектуры DWH, организации слоёв данных и подходов к моделированию, таких как Kimball, Inmon, Data Vault и Anchor Modeling.

Задачи: — Обучение ML-моделей под разные задачи, включая прогнозаторы кликов, конверсий, ставок и работу с аукционами. — Обучение мультиязычных NLP-моделей и адаптация решений под особенности конкретных стран. — Строительство end-to-end ML-пайплайнов: сбор и подготовка данных, офлайн- и онлайн-метрики, оптимизация инференса. — Совместная работа с продуктовой и технической командами, участие в инженерных и продуктовых решениях. Требования: — Опыт построения end-to-end ML-пайплайнов и доведения решений до продакшена. — Желание заниматься прикладными ML-исследованиями. — Практический опыт в NLP или RecSys. Условия: — Корпоративная подписка на чекапы, спорт, терапию, образовательные курсы и другие бонусы в Яндексе.

Компания Alif Tech — международная финтех-компания, работающая на рынках Узбекистана, Таджикистана, Пакистана, Великобритании и ОАЭ. Стек: Python (pandas, numpy), XGBoost/LGBM/CatBoost, SQL, Airflow, базовый DL. Формат работы: офис (предпочтительно), возможен гибрид или удалённая работа.

Задачи: • Разрабатывать и валидировать модели машинного обучения, тренировочные пайплайны, системы инференса и поддерживающую инфраструктуру. • Реализовывать компоненты моделей, пайплайны данных, системы оценки и численные методы. • Строить воспроизводимые программные рабочие процессы с использованием Python и командных инструментов. Требования: • Магистерская степень или PhD в области компьютерных наук, машинного обучения, искусственного интеллекта, прикладной математики, статистики, инженерии или близкой количественной дисциплины. • Сильный профессиональный или исследовательский опыт в машинном обучении. • Практическое владение Python и кодирующими агентами. • Опыт работы в технологической компании, AI-лаборатории, исследовательской организации или другом признанном инженерном окружении приветствуется. • Исключительный опыт в open-source или академической сфере также может быть квалификацией. Условия: • Полностью удалённая работа. • Контрактный формат занятости. • Гибкий график — кандидат сам выбирает часы и дни работы, включая выходные. • Оплата сдельная, от $80 до $150 в час, до 15 часов в неделю. • Выплаты через Stripe или Wise без назначения платежа, аналогично UpWork. • Область проекта: искусственный интеллект. Процесс отбора: • Откликнуться и пройти скрининговые вопросы. • Пройти AI-интервью около 30 минут. • Пройти ревью менеджера по найму. Сроки начала: • Роли обычно закрываются в течение 48 часов. • Ожидается начало выполнения первой задачи в течение 24–48 часов после онбординга. Описание роли: Работа связана с разработкой, обучением и инференсом моделей машинного обучения, оптимизацией производительности и численными вычислениями. Требуется решение сложных инженерных задач, включая реализацию и модификацию моделей, построение воспроизводимых рабочих процессов, оптимизацию памяти и пропускной способности, отладку численных и системных ошибок, а также проверку корректности и производительности реализации.

Задачи: — обновление информации в базе; — проверка записей; — поиск дублирующихся данных; — подготовка простых отчётов; — поддержание порядка в системе. Новым сотрудникам дают инструкции и вводное обучение. Работа проходит полностью онлайн, без необходимости ездить в офис.

Задачи: — разрабатывать и оптимизировать SQL-запросы, процедуры, функции, триггеры, views; — работать со структурой БД, индексами и миграциями; — анализировать execution plans, находить блокировки, deadlock и проблемы производительности; — контролировать изменения БД в Test и Production; — мониторить состояние и нагрузку БД; — заниматься backup/restore, репликацией и отказоустойчивостью; — участвовать в расследовании Production-инцидентов; — взаимодействовать с разработчиками, DevOps и QA. Требования: — опыт работы DBA / Database Engineer / SQL Developer; — уверенный SQL; — хорошее понимание реляционных БД; — опыт оптимизации запросов и анализа execution plans; — понимание индексов, транзакций, locking и deadlock; — опыт работы с Production-БД; — понимание backup/restore, репликации и High Availability; — Git и версионирование SQL-кода. Будет плюсом опыт в FinTech, банках или платежных системах, а также работа с высоконагруженными БД. Условия: — официальное трудоустройство по ТК РК; — понятный онбординг и поддержка на старте; — обучение и развитие за счёт компании; — частичная компенсация занятий спортом; — корпоративные активности и мероприятия; — работа в офисе в Караганде или удалённо по всему Казахстану.

Задачи: — Разрабатывать AI-агентов на Python — Интегрировать модели и внешние API — Работать с RAG и Tool Calling — Упаковывать решения в Docker — Разворачивать через Helm в Kubernetes — Работать с ArgoCD и анализировать логи — Исправлять ошибки и самостоятельно обновлять production-деплои — Работать с SCA-сканерами и зависимостями Требования: — 3–6 лет опыта, Middle / Senior — Python + LangChain / LlamaIndex / Semantic Kernel или аналоги — Docker, Kubernetes, Helm — Bash, debugging, анализ логов — Понимание AI Agents, RAG, Tool Calling — Глубокое понимание Python-зависимостей (pip, poetry, virtualenv) — Высокая самостоятельность: от кода до запуска в production Условия: — Формат работы: Remote — Занятость: Full-time — Зарплата: до 260 000 ₽ на руки — Оформление: ИП / СМЗ — Локация: РФ, гражданство РФ

Команда DS Lab — это RnD-подразделение внутри департамента Trust & Safety, которое разрабатывает решения для повышения доверия и безопасности пользователей на площадке. Мы работаем с широким спектром AI-задач, используем современный стек технологий, а также регулярно внедряем SOTA-подходы для того чтобы быть быстрее и умнее тех, кто пытается обмануть бизнес и пользователей. Задачи: — Обучать и развивать ML-модели, направленные на повышение доверия и безопасности миллионов пользователей на площадке; — Реализовывать полный жизненный цикл ML-проектов: от глубокого анализа данных и поиска гипотез до запуска решений в production и их мониторинга; — Работать с передовыми архитектурами (Transformer, LLM, VLM), проектируя на их основе сложные решения, включая автономные агентские системы; — Изучать текущие бизнес-процессы департамента, находить точки роста и внедрять инновационные методы для их качественного улучшения; — Исследовать SOTA-подходы к решению сложных задач и адаптировать их под специфику и потребности бизнеса. Требования: — Успешно реализовали сложные технические проекты «с нуля» и обладаете опытом доведения своих решений до этапа промышленной эксплуатации в высоконагруженных системах; — Детально понимаете устройство современных нейросетевых архитектур (включая трансформеры, мультимодальные системы и агентские паттерны) и имеете опыт их практического применения; — Обладает глубокой экспертизой в CV и/или NLP; — Уверенно владеете современным стеком разработки и фреймворками для DS/ML, понимаете принципы оптимизации производительности моделей; — Способны самостоятельно вести проект, декомпозировать задачи, оценивать риски, аргументировать выбранный подход, коммуницировать со стейкхолдерами и заказчиками; — Умеете работать в условиях высокой неопределенности, быстро проверять гипотезы и вовремя отказываться от неработающих подходов; — Используете Claude Code, Codex и другие агентные инструменты в ежедневной работе: умеете декомпозировать задачи под агента, писать контекст и инструкции, проверять и дорабатывать результат. Будет здорово, если вы: — Имеете опыт работы с агентскими решениями или понимаете принципы их построения на базовом уровне; — Умеете быстро создавать работающие прототипы и интерактивные инструменты для демонстрации результатов заказчикам; — Обладаете экспертизой в области Trust & Safety и/или имеете опыт работы в крупных E-commerce проектах; — Есть опыт в edge computing, распознавании речи или машинном переводе.

Задачи: — Разработка и внедрение ML-моделей прогнозирования спроса (временные ряды, градиентный бустинг, нейросети) на уровне SKU; — Автоматизация пайплайнов ретрайна и мониторинга качества прогнозов в продакшене с использованием MLflow, Airflow, Docker; — Интеграция внешних факторов (промо, погода, сезонность, макроэкономика) и сценарное "what-if" моделирование; — Согласование иерархических прогнозов для оптимизации запасов в цепочке поставок (дефицит ↔ перепроизводство). Требования: — Уверенное владение Python (Pandas, NumPy, Scikit-learn); — Продвинутый уровень SQL (оконные функции, CTE, оптимизация запросов); — Опыт работы с Big Data: PySpark (распределённые данные > 100 ГБ); — Знания MLOps: Airflow / Prefect, MLflow / Weights & Biases, Docker, CI/CD; — Опыт работы с облачными платформами: AWS (SageMaker, S3, Redshift) или Azure / Yandex Cloud; — Знания статистики: теория вероятностей, проверка гипотез, A/B-тестирование, байесовские методы; — Бизнес-ориентация: понимание метрик (WMAPE, Fill Rate, оборачиваемость) и их влияния на P&L; — Умение объяснять сложные вещи простым языком нетехническим менеджерам и закупщикам; — Проактивность: самостоятельный поиск гипотез и точек роста, а не просто выполнение ТЗ; — Стрессоустойчивость: работа с "грязными" данными и умение отстаивать качество прогнозов перед бизнесом. Условия: — Работа в офисе у м. Кунцевская, бизнес-центр Kutuzoff Tower; — График работы 5/2 с 09:00 до 18:00; — Официальное оформление по ТК РФ, официальная зарплата с больничными и отпусками; — Заработная плата обсуждается на собеседовании; — Корпоративные скидки на продукцию компании (алкоголь); — Подарки сотрудникам и их детям на праздники.

Location: San Francisco, California; New York, New York Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE: Notion has been at the cutting edge of AI since before ChatGPT launched. The job of the Model Capabilities team is to keep us there. We own the model layer of Notion AI: integrating frontier models as they ship, keeping inference reliable and economical at scale, and building new capabilities that other teams take advantage of.   This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. WHAT YOU'LL ACHIEVE: - Bring new frontier models into production quickly, making them available for our users and our engineers. - Make inference reliable: better error categorization, self-healing retries, and cross-provider failover. - Own observability for the model layer, driving down both time to detection and time to fix. - Build new model-level capabilities and help product teams adopt them. - Act as connective tissue across Notion's AI teams: find the gaps, unblock people, and make sure fixes land with the right owner. SKILLS YOU'LL NEED TO BRING: - Comfort with a moving frontier: The model landscape changes monthly. You keep up with it, form your own view of what's real, and stay pragmatic about what's worth adopting now. - AI fluency as a practitioner: You use AI tools seriously in your own work and have opinions about where they help and where they don't. - Production AI systems experience: You've built and operated systems on top of LLM APIs, not just prototyped with them. You understand token economics, streaming, tool calling, context limits, and how each of these fails in production. - Measurement before conviction: You don't ship a prompt or model change on vibes. You define what "better" means, build or use the evaluation to test it, and are willing to be proven wrong by your own data. - Cost and performance instincts: You treat latency and dollars as product qualities, not afterthoughts, and you can reason about the tradeoff between them and output quality. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $255,000 – $300,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy https://notion.notion.site/Notion-Global-Recruiting-Privacy-Policy-fc3eb4e829354a26a2bb6fd5e289b550?pvs=74 and NYLL 144 https://notion.notion.site/Ashby-AI-Bias-Audit-2b0efdeead05803bbbfae159ec86c528. #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Location: New York, NY (HQ); Remote (US) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis. WHAT YOU’LL DO - Employ statistical and machine learning techniques on large datasets to discover patterns of fraud, platform abuse, and identity theft - Prototype and productionize machine learning models and rules-based systems to protect Ramp and its users from fraud - Partner closely with Fraud Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make - Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way WHAT YOU NEED - Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields - A minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist or Data Scientist - Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and backend engineering - Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems - Strong knowledge of SQL (Snowflake, Postgres, etc.) - Fluency with agentic (AI) tools for software development and data analysis - Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions NICE-TO-HAVES - PhD in Math, Economics, Physics, Computer Science, or other quantitative fields - Context on Fraud and/or Identity Threat detection systems - Experience at a high-growth startup - Experience with the modern data stack ( Snowflake / Hex / dbt / RisingWave / etc ) - Strong perspective on data science + ML engineering development cycle, especially in a post-AI setting - Experience developing LLM-backed systems or tools BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: San Francisco, CA • New York, NY Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We are looking for Data Engineering interns who are excited to help scale the systems and pipelines that power decision-making at Figma. As an intern on our data team, you will partner with engineers and analysts to design and build reliable datasets, ensure data quality, and make Figma's data more accessible across the company. This internship will be based out of our San Francisco or New York Hub. What you'll do at Figma: Build, test, and document data pipelines that bring product or business data into Figma’s data warehouse Help design foundational datasets that are trusted, well-documented, and easy to use Optimize pipelines for performance and scalability as Figma grows Partner with cross-functional teammates to understand data needs and deliver solutions Contribute to the tools and practices that make working with data at Figma easier With support from a manager and mentor, you’ll own a scoped project from problem definition through implementation, testing, documentation, and sharing the results. Some projects you could work on: Develop new ETL jobs to integrate product or business data into our warehouse Improve the performance and reliability of core pipelines Build reusable datasets that support experimentation, product and business analytics, or cross-functional stakeholders Document and simplify complex data workflows for broader use We'd love to hear from you if you have: Experience coding in Python or a similar language and writing SQL queries Experience building or working with data pipelines, ETL, or large datasets Curiosity about how data systems work and interest in making them more scalable and reliable Strong communication and collaboration skills Excitement to learn, get feedback, and grow as a data engineer At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure This internship role is based in either Figma’s San Francisco or New York hub offices, and has the hourly base pay rate stated below.  Figma also offers interns a housing stipend and travel reimbursement. Figma’s compensation and benefits are subject to change and may be modified in the future. Internship $46 — $46 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

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

Location: Barcelona, Spain; Tokyo, Japan; Portland, OR Workplace: onsite About Welocalize  Welocalize, a Welo Global brand, serves localization teams through AI-enabled multilingual content solutions that enable enterprises to operate and scale globally. Welocalize combines AI, automation, and human expertise to support enterprises in more than 300 languages, enabling accurate, culturally aligned, and compliant multilingual content at scale.   Welocalize’s Opal Platform comprises patented technology designed to automate multilingual content and improve workflow performance for enterprises. Opal functions as an agentic system that orchestrates AI, automation, and human expertise to coordinate content workflows across the lifecycle, improving speed, scalability, and operational control for global enterprises. These solutions operate within a secure and compliant environment supported by seven ISO certifications. Welocalize is headquartered in New York with offices worldwide. welocalize.com  ROLE OVERVIEW  Welocalize is looking for a native-level Swedish speaker to join a confidential, large-scale AI and consumer technology programme for a major global technology and communications client.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how the product actually performs on a client-supplied device — a smartphone and a next-generation smart glass. If you enjoy noticing the detail other people miss, this is work you'll find satisfying.  Welocalize is looking for a native-level Swedish speaker to join a large-scale AI and consumer technology programme.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how it performs on a real device. You'll be among the first people to see this technology in Swedish, and your judgement shapes how well it works before anyone else uses it.  If you enjoy noticing the detail other people miss, this is work you'll find satisfying.    MAIN RESPONSIBILITIES  Review pre-release AI model output in Swedish and judge it on accuracy, naturalness, appropriateness, and overall quality — would a native speaker really say it this way? This includes fact-checking each response against the source material.

Location: Barcelona, Spain; Tokyo, Japan; Portland, OR Workplace: onsite About Welocalize  Welocalize, a Welo Global brand, serves localization teams through AI-enabled multilingual content solutions that enable enterprises to operate and scale globally. Welocalize combines AI, automation, and human expertise to support enterprises in more than 300 languages, enabling accurate, culturally aligned, and compliant multilingual content at scale.   Welocalize’s Opal Platform comprises patented technology designed to automate multilingual content and improve workflow performance for enterprises. Opal functions as an agentic system that orchestrates AI, automation, and human expertise to coordinate content workflows across the lifecycle, improving speed, scalability, and operational control for global enterprises. These solutions operate within a secure and compliant environment supported by seven ISO certifications. Welocalize is headquartered in New York with offices worldwide. welocalize.com  ROLE OVERVIEW  Welocalize is looking for a native-level Finnish speaker to join a confidential, large-scale AI and consumer technology programme for a major global technology and communications client.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how the product actually performs on a client-supplied device — a smartphone and a next-generation smart glass. If you enjoy noticing the detail other people miss, this is work you'll find satisfying.  Welocalize is looking for a native-level Finnish speaker to join a large-scale AI and consumer technology programme.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how it performs on a real device. You'll be among the first people to see this technology in Finnish, and your judgement shapes how well it works before anyone else uses it.  If you enjoy noticing the detail other people miss, this is work you'll find satisfying.    MAIN RESPONSIBILITIES  Review pre-release AI model output in Finnish and judge it on accuracy, naturalness, appropriateness, and overall quality — would a native speaker really say it this way? This includes fact-checking each response against the source material.

Location: Barcelona, Spain; Tokyo, Japan; Portland, OR Workplace: onsite About Welocalize  Welocalize, a Welo Global brand, serves localization teams through AI-enabled multilingual content solutions that enable enterprises to operate and scale globally. Welocalize combines AI, automation, and human expertise to support enterprises in more than 300 languages, enabling accurate, culturally aligned, and compliant multilingual content at scale.   Welocalize’s Opal Platform comprises patented technology designed to automate multilingual content and improve workflow performance for enterprises. Opal functions as an agentic system that orchestrates AI, automation, and human expertise to coordinate content workflows across the lifecycle, improving speed, scalability, and operational control for global enterprises. These solutions operate within a secure and compliant environment supported by seven ISO certifications. Welocalize is headquartered in New York with offices worldwide. welocalize.com  ROLE OVERVIEW  Welocalize is looking for a native-level Hindi speaker to join a confidential, large-scale AI and consumer technology programme for a major global technology and communications client.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how the product actually performs on a client-supplied device — a smartphone and a next-generation smart glass. If you enjoy noticing the detail other people miss, this is work you'll find satisfying.  Welocalize is looking for a native-level Hindi speaker to join a large-scale AI and consumer technology programme.  It's a hands-on, on-site role that combines two things: evaluating a pre-release AI model in your language, and testing how it performs on a real device. You'll be among the first people to see this technology in Hindi, and your judgement shapes how well it works before anyone else uses it.  If you enjoy noticing the detail other people miss, this is work you'll find satisfying.    MAIN RESPONSIBILITIES  Review pre-release AI model output in Hindi and judge it on accuracy, naturalness, appropriateness, and overall quality — would a native speaker really say it this way? This includes fact-checking each response against the source material.