Вакансии

Задачи: — Проектировать, строить и оптимизировать масштабируемые AWS-решения для данных с использованием Databricks, включая архитектуры Lakehouse с Delta Lake и Unity Catalog. — Разрабатывать пакетную и потоковую обработку данных с использованием Apache Spark, Flink, Kafka, Amazon MSK и Kinesis. — Руководить интеграцией и миграцией данных (сопоставление источников и целей, загрузка, трансформация и обеспечение качества данных). — Вести архитектуру платформы данных, моделирование данных и лучшие инженерные практики для масштабируемости, надежности и долгосрочной поддержки. — Создавать и управлять автоматизированными рабочими процессами и конвейерами данных с использованием Databricks Workflows, Apache Airflow, MWAA, Snowflake и Amazon Redshift. — Наставлять команды инженеров данных и переводить бизнес-требования в технические решения, дорожные карты и планы поставки. Требования: — Подтвержденный опыт работы Lead Data Engineer с масштабируемыми платформами и конвейерами данных. — Практические навыки пакетной и потоковой обработки с Apache Spark, Flink, Kafka, Amazon MSK или Kinesis. — Сильный опыт работы с AWS и Databricks, включая Delta Lake, Unity Catalog, Workflows и Jobs. — Продвинутый уровень SQL и владение Python (предпочтительно), Scala или Java. — Опыт оркестрации рабочих процессов данных с Databricks Workflows, Apache Airflow или MWAA. — Английский язык на уровне не ниже Upper-intermediate. Условия: — Удаленная или офисная модель работы. — Работа в инновационной среде на протяжении всего жизненного цикла решения. — Возможность изучать новые технологии и делиться знаниями в инженерном сообществе. — Руководящая роль с наставничеством и поддержкой команды. Процесс найма: — Подать заявку через форму. — Связь с рекрутером и этапы интервью.

Задачи: — активно участвовать в разработке микросервисов на Python; — участвовать в проработке технических требований, архитектуры и подходов к решению; — участвовать в управлении бэклогом команды, проводить приоритезацию и контролировать выполнение задач; — заниматься people-менеджментом: участвовать в найме, развитии сотрудников и т.д. Требования: — опыт работы в роли MLOps Engineer от 4-х лет; — опыт работы в роли Team Lead/ проведение code review – не менее 1 года; — опыт коммерческой backend-разработки на Python от 3-х лет; — понимание способов интеграций IT-систем (шины, очереди, API); — практический опыт с Kubernetes, Redis; — опыт работы с реляционными базами данных, уверенные знания SQL; — понимание принципов CI/CD; — понимание микросервисной архитектуры; — опыт работы с ИИ моделями и их внедрением. Будет плюсом: — знания в области BigData (Hadoop, Spark), OpenSearch; — знание планировщиков процессов (AirFlow); — опыт работы в банковской сфере; — понимание гибких методологий разработки (Agile); — знание основных инструментов управления разработкой (например: Jira, Confluence); — знания и опыт в Machine learning; — опыт управления IT проектами, включая разработку и внедрение ML моделей в продакшн; — опыт разработки ML моделей в роли data scientist, data engineer, ML Ops. Условия: — Хорошая зарплата: уровень обсуждается индивидуально, есть доплаты за менторство и профактивности. — Развитие: долгосрочные проекты от российских заказчиков, возможность менять направления, прозрачная система Performance Review. — Комфорт и свобода: релокейт между офисами, выбор формата работы (удалённо, офис, гибрид), адаптация для новых сотрудников. — Обучение: доступ к корпоративному порталу, митапам, конференциям (и как гость, и как спикер). — Социальный пакет: ДМС со стоматологией, частичная компенсация спорта, бесплатный английский, оплачиваемый отпуск и больничные. — Корпоративная жизнь: тимбилдинги, детские праздники, внутренние мероприятия.

Location: Dhahran, Saudi Arabia Muller's Solutions is seeking an experienced Data Engineer with 5–6 years of experience in designing, developing, and maintaining scalable data solutions. The ideal candidate should possess strong expertise in Python, Pandas, NumPy, Airflow, BigQuery, SQL, and API development . The candidate will play a key role in building robust data pipelines, processing large datasets, and supporting business-critical applications related to inventory optimization, master data management, and backend services. Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion and processing. Build and optimize data workflows using Apache Airflow . Develop and maintain data processing solutions using Python , Pandas , and NumPy . Design and optimize complex SQL queries and data models in BigQuery . Develop and integrate APIs to support data exchange between systems. Implement data ingestion frameworks from various internal and external sources. Perform data cleansing, transformation, and validation to ensure data accuracy and consistency. Develop and maintain processes for master data management . Support inventory optimization initiatives by implementing data processing and business logic. Build and maintain backend services that enable data-driven applications. Monitor and troubleshoot data pipelines to ensure reliability and performance. Collaborate with cross-functional teams, including Product, Analytics, and Engineering teams. Ensure adherence to data governance, security, and best practices. Requirements Technical Requirements Must-Have Skills 5–6 years of experience in Data Engineering or related roles. Strong hands-on experience with: Python Pandas NumPy Apache Airflow Google BigQuery SQL API development and integration Experience in designing and implementing scalable ETL/ELT pipelines . Strong understanding of data modeling, data transformation, and database concepts. Experience working with large-scale datasets and optimizing query performance. Proficiency with version control systems such as Git . Good-to-Have Skills Experience with PySpark and distributed data processing. Basic understanding of Machine Learning concepts and workflows . Familiarity with data quality frameworks and data validation practices. Experience with Docker and containerization technologies. Knowledge of CI/CD pipelines and DevOps practices. Experience working in cloud-based data environments. Preferred Qualifications Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Experience working on enterprise-scale data platforms and data-driven applications.

Location: Munich, Germany; Berlin, Germany What client look for: You design, build, and optimize scalable data pipelines and architectures that form the foundation for analytics and AI solutions. You ensure that data from various sources is efficiently integrated, transformed, and made available for business and analytics use cases. You collaborate closely with Data Scientists, Consultants, and Product Owners to deliver end-to-end data solutions with measurable business impact. You develop and maintain ETL/ELT processes that ensure data quality, reliability, and performance. You take ownership of cloud-based data infrastructures (Azure, AWS, or GCP) and contribute to their continuous improvement. You leverage containerization and workflow tools (e.g. Docker, Airflow) to build robust, automated, and reproducible systems. You develop solutions with a clear end-to-end mindset, from raw data ingestion to production deployment. You actively contribute to the evolution of our data strategy, tooling, and best practices within Client. Requirements What the client requires: You hold a degree with excellent grades in Computer Science, Data Engineering, Information Systems, Mathematics, Physics, or a related field. You have strong experience in Python and SQL as foundational tools for data integration, transformation, and automation. You have hands-on experience in building and managing ETL/ELT pipelines and data workflows. You are experienced with cloud environments (preferably Azure, alternatively AWS or GCP). You are familiar with containerization and workflow orchestration tools such as Docker and Airflow. You have experience with Infrastructure as Code (e.g. Terraform) to manage scalable, reproducible setups. You understand data lakes, data warehouses, and streaming technologies (e.g. Kafka, Kinesis). You ideally have experience with distributed processing systems like Spark, Snowflake, or Databricks. You ensure data quality, observability, and monitoring as integral parts of your solutions. You enjoy cross-functional collaboration with Data Scientists, Product Owners, and clients. You are a service-oriented and communicative team player with a high degree of self-responsibility and passion for your work. You have strong communication and presentation skills, and can explain complex topics clearly. You speak English fluently; regional languages are an advantage. Benefits What you can expect: Your impact is crucial : You actively shape the digital future in a highly motivated & smart team in direct cooperation with the founders & partners, creating real added value by linking strategy and implementation. Your hard work pays off! You benefit from attractive salary packages, participation in sales success, and exclusive investment opportunities. In addition, we promote our top talents through the 'Digital Leaders of Tomorrow' program and thus offer you further exciting benefits. Your development: From day one, you will be supported on your journey through a wide range of development opportunities, quickly take on responsibility, and have the opportunity to shape your individual career at the company. You will become a digital leader! Your working environment: You will be immersed in a diverse and family-friendly environment with a strong team spirit, benefitting from a flexible and hybrid working model in one of our offices in Munich, London, Amsterdam, Milan, and Berlin. Your view into the future: You will work at the cutting edge and gain valuable insights and practical experience with a focus on digital business models and data-driven value creation in eight forward-looking industries. Your benefits on top: You can look forward to regular team events and joint sports sessions, an attractive company pension scheme, access to local fitness and wellness partnerships, as well as mobility and meal allowances, and a wide range of other company benefits.

Мы развиваем ИТ-продукт, который включает в себя масштабную WEB-платформу и интерактивного Telegram-бота / Mini App. Наш стек: Python, Airflow 2+, dbt Core, ClickHouse, PostgreSQL, Docker, GitLab. Продукт быстро растет, и сейчас мы ищем Data Engineer, который поможет нам масштабировать аналитическую инфраструктуру и сделать работу с данными быстрой и надежной. Задачи: — Разрабатывать и поддерживать ETL/ELT-процессы на базе Airflow и dbt Core — Интегрировать новые источники данных: PostgreSQL, внешние API и сервисы — Развивать существующее хранилище данных на ClickHouse и поддерживать аналитические витрины — Оптимизировать SQL-запросы и производительность пайплайнов — Поддерживать и развивать инфраструктуру аналитической платформы (Docker, Airflow, dbt) — Взаимодействовать с аналитиками для реализации новых витрин, метрик и источников данных — Участвовать в расследовании инцидентов, связанных с качеством данных и работой пайплайнов — Поддерживать техническую документацию и участвовать в передаче знаний внутри команды Требования: — Опыт на позиции инженера данных от трёх лет — Уверенное знание SQL и опыт работы с аналитическими СУБД — Практический опыт работы с ClickHouse: проектирование таблиц, выбор движков, партиционирование, оптимизация запросов — Опыт разработки и поддержки ETL/ELT-процессов: способность самостоятельно выбирать способ интеграции источника данных, проектировать структуру загрузки, хранение и обновление данных с учетом требований бизнеса и технических ограничений — Опыт работы с Apache Airflow 2+: разработка, поддержка и отладка DAG'ов, понимание механизмов планирования, зависимостей и мониторинга пайплайнов — Опыт работы с dbt Core — Хорошее знание Python: умение разбираться в существующем коде, дорабатывать и разрабатывать новые компоненты интеграций и пайплайнов — Опыт работы с PostgreSQL и понимание особенностей инкрементальных выгрузок данных — Опыт интеграции внешних REST API — Понимание принципов контейнеризации и опыт работы с Docker / Docker Compose — Умение самостоятельно декомпозировать задачи и доводить их до результата Будет плюсом: — Опыт работы с Airflow 3+ — Опыт работы с BigQuery — Опыт работы с Google Analytics / GA4 — Опыт работы с облачными платформами (GCP, Yandex Cloud, AWS) — Понимание базовых принципов работы блокчейн-сетей и транзакционных данных — Опыт использования AI-инструментов для разработки и сопровождения кода Формат работы: удаленно Часовой пояс: MSK

Обязанности: • Проектировать, разрабатывать и сопровождать ETL/ELT-процессы для загрузки, преобразования и контроля качества данных; • Разрабатывать и оптимизировать сложные DAG в Apache Airflow; • Проектировать архитектуру пайплайнов данных с учетом надежности, масштабируемости и производительности; • Интегрировать данные из различных источников: PostgreSQL, внешние API, webhook, S3-совместимые хранилища и другие системы; • Разрабатывать и сопровождать пайплайны обработки данных на Python и Apache Spark; • Работать с lakehouse-архитектурой и таблицами Apache Iceberg; • Оптимизировать SQL-запросы, ETL/ELT-процессы и инфраструктуру обработки данных; • Писать тесты для пайплайнов данных, обеспечивать качество и стабильность решений; • Проводить code review и участвовать в развитии инженерных стандартов команды; • Взаимодействовать с аналитиками, BI-специалистами и разработчиками для реализации бизнес-требований к данным; • Участвовать в сопровождении инфраструктуры и разборе инцидентов. Требования: • Опыт работы дата-инженером / ETL-разработчиком / backend-разработчиком от 1 года; • Уверенное знание Python; • Уверенное знание SQL, опыт написания и оптимизации сложных запросов; • Практический опыт работы с PostgreSQL; • Опыт работы с Apache Airflow, умение самостоятельно создавать и сопровождать сложные DAG; • Понимание архитектуры пайплайнов данных и умение проектировать технические решения; • Опыт разработки ETL/ELT-пайплайнов; • Опыт оптимизации производительности обработки данных; • Навыки написания тестов; • Опыт проведения code review; • Опыт работы с различными источниками данных и интеграциями; • Самостоятельность, системное мышление, ответственность. Условия: • Зарплата: 250 – 280 тыс на руки (полностью белая); • Ненормированный график, но без переработок (любые переработки компенсируются дополнительными выходными днями, но нужно быть готовым в случае необходимости поработать и поздно вечером, и в выходной день); • Офис в центре города (м. Трубная/Цветной бульвар).

Location: Paris, France Workplace: Hybrid HEALTH CAN’T WAIT. Not for symptoms to get worse. Not for a six‑month appointment. Not for a system to catch up. But that’s exactly how healthcare works today. You wait, until you can’t. Alan exists to end the wait. Health is a universal right, and we believe this right can only become real when it’s coupled with prevention. We need to stop treating health as something we repair and start treating it as something we build, every day. It’s not solely a question of willpower. It’s the healthcare system itself that needs to work for everyone, in a sustainable way. So we are building the new standard in prevention insurance. Alan is the first company that integrates insurance, prevention, and care into a single, acclaimed user experience. We are on an incredible journey to build a global leading company, with a unique culture https://alan.com/en/careers. We already partner with 40K+ companies of all sizes, serving more than 1M+ members, and have reached €800M+ in ARR. Prevention as the new norm. That's what we're building with our team of 1000+ people. If it speaks to you: we're hiring across France, Spain, Belgium, and Canada. And beyond. ⭐️ THE DATA TEAM - Being part of Alan's data team means you'll have a positive impact on people's health and wellbeing. - We create insights to help our colleagues focus on what is most impactful. - We build features and tools powered by data that directly help our members. - Examples include: - going deep into health consumption patterns, - understanding our product usage, - creating visibility to help our sales team perform, - automating how we reimburse our members, - building products that help our members stay healthy...  We also believe in having a full stack approach: - Each one of us contributes to all 3 aspects of the data spectrum (analytics, engineering, science). This encourages strong ownership and drives impact. - We own our infrastructure. We pride ourselves on a nimble data stack that gives us the flexibility we need. We're mainly using SQL, Python, R, Airflow, Snowflake, and Metabase. - We build in-house tooling to organize our data and serve it to the rest of the company. 🎯 EXPECTED SKILLS AND ABILITIES You would thrive at Alan if most of this sounds like you: - Passionate about owning ambitious problems and developing simple solutions for them - Demonstrated impact during a first successful experience. - Experience or willingness to grow in all 3 aspects of the data spectrum (analytics, engineering, science) -- being specialized in one of these areas is good too! - Proficient in SQL, Python and/or R- Setting a high standard of rigor and precision for yourself, interested in your craft - Great listening and communication skills - Humble, kind, collaborative, and still willing to grow (no matter your seniority!) - Fluent and clear in English, both oral and written (no need to speak French!) For this role we are looking to hire within the C1-E level range https://alan.com/en/careers/a/salary-equity. ⚙️ IMPORTANT NOTE: WE HIRE PEOPLE, NOT ROLES. If you're excited about this opportunity but don't check every box, we'd love to hear from you. Everyone, no matter how underrepresented, should feel free to apply, as it can only bring learnings or success. If you identify yourself as a woman: Did you know that research shows women often apply only when meeting 100% of requirements? Remember, this is just a guide, not a checklist. We'll be thrilled to receive your application! 🔖 Check out our About Alan https://alan.com/about and Career https://alan.com/careers pages, as well as our Medium https://medium.com/alan, blog https://blog.alan.com/ and Glassdoor page https://www.glassdoor.com/Overview/Working-at-Alan-EI_IE1696043.11,15.htm for more info. YOU WANT TO KNOW MORE ABOUT ALAN? - 🙌 Perks & Benefits https://alan.com/en/careers/a/salary-equity: Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers. - 🤘 A strong culture https://alan.com/en/about/a/leadership-principles: People joining Alan are often surprised and delighted by our innovative working method. We have a set of cultural values that guide our approach to work 🔄 A quick note about the process Note: While you're applying for a specific area, you may join a different engineering team based on where we think you'll have the most impact. Check out descriptions of other areas here https://www.notion.so/Software-Engineering-Areas-Alan-2c61426e8be7805bacd2cdbc08c32640?pvs=21.

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Liquidity Platform The Liquidity Platform provides cutting-edge technology that covers all aspects of crypto trading. We build low-latency connectivity to global crypto venues — across both CeFi and DeFi — strategy services for automated pricing and trading bots, high-frequency data capture and analysis, and state-of-the-art micro frontends for trading management. On top of this infrastructure, we build highly customized strategies to facilitate crypto liquidity. Our engineering teams own the full trading lifecycle, from venue connectivity and execution to strategy, data, risk, and analytics. Our risk solutions are independent of trading logic, decoupled by design, and connected to 20+ trading venues across spot, derivatives, and event-contract markets. If you are a strong technologist excited about the potential of crypto trading and fully-automated systematic trading, we should talk. About the Role We are hiring software engineers across the Liquidity Platform’s engineering teams. You will design, build, and operate the systems that price, execute, monitor, and safeguard our liquidity-providing business 24/7. You will work closely with liquidity managers, product managers, and desk developers — developing strategies, services, and infrastructure using in-house toolkits — while growing capabilities in inventory and risk management, strategic problem solving, cross-functional collaboration, and effective communication. These roles are open to Senior and Staff-level candidates; scope and title are calibrated based on experience and impact. Specializations span Delta One Systematic Trading, Cash OTC, Option Market Making, Trading Infra Service, Data Engineering and Risk & Analytics. What You’ll Be Doing Design, build, and operate scalable, fault-tolerant, low-latency trading infrastructure and microservices that handle 24/7 crypto market operations. Build and maintain connectivity to centralized exchanges, DeFi venues, and counterparties using FIX 5.0+, WebSocket, HTTP/2, and REST — handling the real-world complexities of external integrations and on-chain data. Develop and maintain core services across the trading lifecycle: strategy and execution engines, automated pricing and trading bots, order execution and position tracking, trade & position data platforms, and risk & analytics systems. Architect and optimize high-throughput order execution with sub-millisecond latency targets, and build real-time market-data pipelines aggregating order books and price feeds across multiple venues. Implement pre-trade risk controls, circuit breakers, rate limiters, position/PnL and risk calculations, automated alerting, and high-availability architecture. Implement robust monitoring, alerting, and auto-recovery so strategies remain stable, scalable, and self-healing in a 24x7 trading environment. Build trusted data models, reconciliation workflows, and data-quality controls with clear lineage, reproducibility, and documentation — delivering outputs for the trading desk, Finance, and Operations. Profile and eliminate latency hotspots using garbage-free coding and lock-free concurrency; continuously improve system performance and user experience. Collaborate with liquidity managers, product managers, desk developers, risk, finance, and operations to design, implement, and roll solutions into production. Conduct code reviews, mentor junior engineers, and uphold scalability, resiliency, maintainability, and security best practices across all development activities. What We Look For In You STEM foundation: Bachelor’s degree or above in Computer Science, Engineering, Mathematics, Physics, or a related technical discipline; a combined finance background is advantageous. Experience: Typically 3–8 years in software or data engineering (level-dependent), ideally with exposure to trading, OMS, middle/post-trade, or latency-sensitive systems. Languages: Strong proficiency in one or more of Java (17+), Rust, C++, or Python, with a focus on code quality and operational reliability. Systems: Strong understanding of high-performance, low-latency distributed systems, multi-threaded/concurrent programming, and — where relevant — JVM internals and GC behavior. Connectivity & protocols: Hands-on experience with FIX 5.0+, WebSocket, HTTP/2, and REST APIs, plus network protocol and TCP/UDP optimization. Data & messaging: Strong SQL (MySQL, PostgreSQL — schema design and performance tuning); experience with Redis and Kafka. Infrastructure: Comfortable in Linux/Unix environments; familiarity with Docker, Kubernetes, CI/CD pipelines, and cloud platforms (AWS, AliCloud, GCP) and on-premise infrastructure. Markets: Understanding of market microstructure, order lifecycle, and core trading concepts such as PnL, margin, leverage, and market risk. Mindset: Strong analytical thinking, ownership, and attention to detail; able to work effectively under pressure in a fast-paced environment; a controls mindset around data quality and reproducibility. Communication: Excellent communication and collaboration skills across business and technical teams; fluency in English required, with Chinese/Mandarin a strong plus for global, cross-functional work. Passion: Genuine interest in crypto markets, blockchain, and the broader financial industry, and a drive to keep learning new technologies. Nice to Haves Prior experience in proprietary trading, market making, quantitative research, or front-office technology at exchanges, banks, or investment institutions. Experience with execution algorithms (TWAP, VWAP, iceberg, sniper, smart order routing) and backtesting / strategy-simulation frameworks. Low-latency tooling and IPC: Aeron, Chronicle Queue, Disruptor, shared-memory messaging, Agrona Collections, Protocol Buffers, SBE. Frameworks and libraries such as Spring, Netty, and Vert.x. Modern data platforms (Spark/PySpark, Iceberg, ClickHouse, InfluxDB), workflow orchestration (Airflow, Celery), and ML tooling (MLflow, TensorFlow). Strong understanding of DeFi, blockchain, smart contracts, and crypto exchange APIs; exposure to event-contract / prediction markets. Agentic programming fluency — hands-on use of AI coding tools (e.g., Claude Code, Codex) on real production work. Risk and compliance experience; professional certifications such as CFA or FRM. Technical Environment Languages: Java 17+, Rust, Python, C++ Protocols: FIX 5.0+, WebSocket, HTTP/2, REST Stack: Spring, Netty, Aeron, Chronicle Queue, Disruptor, Kafka, Redis, etcd, MySQL, PostgreSQL, InfluxDB, ClickHouse, Iceberg, Spark Infrastructure: Linux/Unix, Docker, Kubernetes, CI/CD, AWS / AliCloud / GCP Team Specializations The Liquidity Platform comprises several engineering teams. Depending on your strengths and interests, you may join one of the following: Delta One – Systematic Trading: Build cross-venue liquidity and market-making strategies with deep market-microstructure and execution-optimization focus. Option Market Making: Build and operate automated option market-making strategies and pricing systems — managing volatility, greeks, and inventory risk while quoting continuously across crypto options venues. Cash OTC: Develop and own OTC trading strategies and their production environment, partnering closely with liquidity and product managers. Trading Infra Service: Build and maintain the core strategy engine and trading-infrastructure microservices on a distributed, enterprise-grade architecture. Deliver high-throughput, sub-millisecond order execution, market-data pipelines, and exchange connectivity. Data Engineering: Own the trade & position platform end-to-end — venue connectors, the Python + SQL data model, reconciliation, and data-quality controls. Risk & Analytics: Build a greenfield, next-generation risk platform — real-time risk monitoring, PnL/risk calculation, alerting, and circuit-breaking strategies. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. OKX Statement: OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: Chicago, IL, USA; New York, NY, USA; San Francisco, CA, USA About the role Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring AI/ML Engineers across several teams, Trust & Safety, Lending, Growth, and Foundation Models, and you'll be matched with the team where your background, experience and interests fit best. In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into decisions that protect members from fraud, expand access to credit, and power the personalized experiences and marketing that help millions of members get more out of products like MyPay, Instant Loans, and SpotMe — along with the foundational models the rest of our teams build on. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters. In this role, you can expect to Build, train, and deploy deep learning and classical ML models on large-scale financial, transactional, and behavioral datasets Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one Connect model performance to member outcomes and business metrics, and use experimentation to prove impact Contribute to the shared ML platform, tooling, and standards that the rest of the team builds on Help identify where AI/ML creates measurable impact for members — and where a simpler answer is the better one To thrive in this role, you have Experience building and deploying deep learning models in production, with a solid grasp of architecture choice, training dynamics, and evaluation — and the judgment to model design choices Solid machine learning fundamentals: classical modeling, evaluation design, and knowing which metric actually answers the question in front of you Hands-on experience across the end-to-end ML lifecycle — training, experimentation, optimization, deployment, and monitoring Comfort with messy real-world data, including label definition, leakage, class imbalance, and train/serve skew Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy The ability to operate independently in ambiguous environments, and to communicate clearly with both technical and non-technical partners Nice-to-Have Experience in any one of these is a plus, and helps us match you to the right team. Trust & Safety — fraud, risk, abuse detection, or adversarial modeling Lending — credit or underwriting models, and familiarity with model governance, explainability, and fairness requirements Growth — personalization, recommendation, marketing measurement, or experimentation at scale Foundation Models — transformers on tabular or semi-structured data, large-scale pretraining, ML platform work, or applied research with a publication record #LI-DA1 #LI-Onsite Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. Wage Notice $125,000 — $292,000 USD A little about us At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members. We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress. We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential. Because if we don't—who will? *Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC. What we offer for our full-time, regular employees 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees. ✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life. 🏝 Generous vacation policy and company-wide paid days off 🫂 1% of your time off to support local community organizations of your choice 👟 Annual wellness stipend to use towards eligible wellness related expenses 👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents 👪 Access to family planning reimbursement 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals. Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: accommodations@chime.com . To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice .

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the team The Finance Data Team is responsible for the data infrastructure that powers OKX's compliance, regulatory, and financial reporting operations globally. Our Finance Data domain covers everything from raw transaction ingestion to consolidated group financials — supporting statutory reporting, board-level financials, and audit readiness across 100+ markets. This is a team that treats data correctness as a non-negotiable. We operate at the intersection of engineering rigour, financial domain knowledge, and regulatory accountability. About the role We are looking for a Staff Data Engineer to be the technical anchor for Finance Data at OKX. You will define how Finance data is architected, validated, and delivered, and set the standard for how the team operates in an AI-native way. You will work directly with Finance, Accounting, and Treasury stakeholders to ensure that financial data is complete, reconciled, traceable, and audit-ready. You will also be the domain's primary escalation point and the technical voice of Finance Data within the broader engineering organisation. This role suits someone who has operated as a de facto domain lead before — someone who has built financial data systems that have been reviewed by auditors, regulators and who knows what "good" looks like in a regulated financial data environment. Responsibilities: Domain Architecture & Technical Direction Own the end-to-end Finance data architecture: from ODS ingestion through CDM transformation to reporting mart, with clear data lineage documented at every layer Define and enforce data modelling standards for Finance: period cut-off immutability, multi-entity consolidation logic, revenue recognition alignment, and audit trail completeness Lead the design of scalable pipelines supporting trading data, asset positions, P&L, and cost accounting across multiple legal entities and jurisdictions (SG, EU, US, and others) Make architectural decisions independently and articulate trade-offs clearly to both engineering peers and non-technical Finance stakeholders Financial Reporting & Audit Readiness Partner with Accounting, Finance PMO, and Treasury to deliver datasets for month-end close, statutory reporting, and board-level financials on time and to audit standard Ensure every financial figure is traceable back to the source system with full transformation history — no black boxes Build the data foundation that supports OKX's regulatory reporting obligations and long-term financial reporting maturity Data Quality & Controls Design proactive, self-validating DQC frameworks — reconciliation logic, SLA monitoring, and anomaly detection built into pipelines, not bolted on after incidents Own incident response for Finance-critical pipeline failures; conduct structured post-mortems and drive permanent fixes Define "done" for financial correctness in partnership with Accounting; hold the line on data quality standards even under delivery pressure AI-Native Finance Data Lead the team's adoption of AI-assisted engineering: LLM-assisted development, automated anomaly detection, intelligent reconciliation, AI-generated reporting summaries Evaluate and introduce AI tooling into Finance data workflows with production evidence — not POC demos Set the bar for what an AI-native Finance data team looks like, and bring junior engineers along Technical Leadership & Influence Be the go-to escalation point for Finance data domain questions across the team Mentor and grow engineers working in the Finance domain; translate domain complexity into learnable patterns Represent Finance Data in cross-team architecture discussions, sprint planning, and stakeholder reviews Document domain knowledge that outlasts any individual — data dictionaries, pipeline specs, onboarding guides Requirements: 6+ years in data engineering, with at least 3 years owning a Finance, Accounting, or financial reporting data domain end-to-end Deep understanding of financial data fundamentals: period close and cut-off rules, revenue recognition, multi-entity consolidation, reconciliation, and audit trail requirements Demonstrated experience building data systems that have been reviewed in a statutory audit or regulatory review Strong SQL and Python; proven ability to design and maintain complex production pipelines at scale Experience designing for immutability and lineage — financial data that can be rolled back, re-run, and traced without manual intervention Track record of operating with significant autonomy: defining requirements from ambiguous stakeholder input, not just executing tickets Preferred Qualifications: Experience at a crypto exchange, fintech, or company that has gone through IPO preparation or public company financial reporting Familiarity with regulatory reporting requirements across multiple jurisdictions (MAS SG, SEC, FCA, or equivalent) AI/ LLM tooling applied to data engineering workflows in production — concrete examples required; "exploring" does not count Experience with Spark, Airflow, or equivalent orchestration at scale Prior experience as a de facto domain lead or tech lead without formal people management title Background working with Accounting/Controllership teams as a technical counterpart Perks & Benefits: Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Обязанности: • Проектировать, разрабатывать и сопровождать ETL/ELT-процессы для загрузки, преобразования и контроля качества данных; • Разрабатывать и оптимизировать сложные DAG в Apache Airflow; • Проектировать архитектуру пайплайнов данных с учетом надежности, масштабируемости и производительности; • Интегрировать данные из различных источников: PostgreSQL, внешние API, webhook, S3-совместимые хранилища и другие системы; • Разрабатывать и сопровождать пайплайны обработки данных на Python и Apache Spark; • Работать с lakehouse-архитектурой и таблицами Apache Iceberg; • Оптимизировать SQL-запросы, ETL/ELT-процессы и инфраструктуру обработки данных; • Писать тесты для пайплайнов данных, обеспечивать качество и стабильность решений; • Проводить code review и участвовать в развитии инженерных стандартов команды; • Взаимодействовать с аналитиками, BI-специалистами и разработчиками для реализации бизнес-требований к данным; • Участвовать в сопровождении инфраструктуры и разборе инцидентов. Требования: • Опыт работы дата-инженером / ETL-разработчиком / backend-разработчиком от 1 года; • Уверенное знание Python; • Уверенное знание SQL, опыт написания и оптимизации сложных запросов; • Практический опыт работы с PostgreSQL; • Опыт работы с Apache Airflow, умение самостоятельно создавать и сопровождать сложные DAG; • Понимание архитектуры пайплайнов данных и умение проектировать технические решения; • Опыт разработки ETL/ELT-пайплайнов; • Опыт оптимизации производительности обработки данных; • Навыки написания тестов; • Опыт проведения code review; • Опыт работы с различными источниками данных и интеграциями; • Самостоятельность, системное мышление, ответственность. Условия: • Зарплата: 250 – 280 тыс на руки (полностью белая); • Ненормированный график, но без переработок (любые переработки компенсируются дополнительными выходными днями, но нужно быть готовым в случае необходимости поработать и поздно вечером, и в выходной день); • Офис в центре города (м. Трубная/Цветной бульвар).

Location: US - San Francisco, United States Scopely is a global gaming company whose mission is to inspire play every day. Scopely Explore (a division of Scopely)’s mission is to inspire people to explore the world together. We build products that inspire exercise, exploration, and social in-person interaction. We are seeking a quantitatively adept and business-minded Senior Data Scientist, Marketing , to support our global marketing organization. You will operate at the intersection of data science , deep marketing domain expertise , and AI proficiency . In this role, you will help develop measurement frameworks, analytical models(e.g Marketing Mix Modeling), and scalable reporting solutions that inform user acquisition, brand investment, CRM efforts, and long-term player growth. You will also utilize AI-augmented workflows to accelerate the end-to-end data science lifecycle. This role is ideal for someone who combines strong technical skills with intellectual curiosity, a forward-thinking perspective on how AI will transform data science workflows, and a desire to understand how marketing investments translate into long-term player value. Responsibilities User Acquisition (UA) Contribute to and own the Marketing Mix Modeling (MMM) and other aggregate measurement approaches to evaluate cross-channel and upper-funnel impact (e.g. brand) where deterministic attribution is limited. Build and maintain robust ETL pipelines that ingest, transform, and validate UA data from ad networks, MMPs, and internal systems. Develop and refine predictive LTV (pLTV) models to enable faster optimization of UA campaigns based on early user signals. Explore, develop, and refine AI-based systems that are able to answer common data inquiries from stakeholders, as well as quickly diagnose data pipeline issues, etc. Support testing frameworks (e.g., geo experiments, holdouts, incrementality tests) to evaluate campaign effectiveness in privacy-constrained environments. Partner with Finance and UA teams to align on forecasting methodologies and investment strategies driven by pLTV and payback periods. Direct Marketing Build and maintain reliable datasets and ETL workflows that ingest and transform marketing data from ad platforms, CRM systems, social channels, and internal data sources. Support measurement and optimization of direct marketing channels including email, push notifications, in-app messaging, and other CRM/lifecycle campaigns. Partner with Marketing stakeholders to provide actionable insights on targeting, segmentation, messaging effectiveness, and channel strategy. Analytics Infrastructure & Workflow Efficiency Contribute to scalable dashboards and standardized reporting that enable self-serve marketing analytics. Identify opportunities to automate recurring reporting and insight generation for marketing stakeholders. Leverage modern AI/ML tools (e.g., automated modeling workflows, AI coding assistants) to improve analysis speed, code quality, and documentation and bridge the gap between technical AI-driven insights and business stakeholders to ensure output is accurate and aligned with complex business logic. Ensure data quality, documentation, and consistency across marketing data pipelines. Contribute to responsible and thoughtful adoption of AI-powered analytics tools to ensure maintainability and long-term knowledge sharing. Qualifications 4-8 years of experience in data science, marketing analytics, or a related quantitative role (gaming, mobile, or digital consumer experience preferred). Demonstrated proficiency in integrating AI agentic tools to accelerate end-to-end data science workflows. Proven experience in user acquisition measurement and attribution with exposure to Marketing Mix Modeling or other aggregate-level measurement frameworks. Understanding of full marketing funnel, including brand/awareness, social, UA, and direct marketing channels (e.g., email, push, CRM). Familiarity with core performance metrics such as CAC, ROAS, retention, engagement, and LTV. Experience working with marketing data from ad platforms, CRM systems, or aggregate reporting environments. Proficiency in SQL and experience using Python (or similar) for analysis. Experience working with large datasets in a cloud data warehouse (e.g., BigQuery) and building dashboards in BI tools (e.g., Looker). Strong analytical, communication, and stakeholder management skills in a cross-functional environment. Plus If… Experience supporting brand or upper-funnel marketing measurement. Familiarity with lifecycle marketing analytics, segmentation modeling, or propensity modeling. Experience building marketing data pipelines using Airflow, Composer, or similar orchestration tools. Experience working with global marketing teams across multiple regions. For candidates in CA, CO, NJ, NY, and WA, the annual salary range is provided below. In addition to base pay, employees may be eligible for equity, bonuses, and a comprehensive benefits package, including healthcare benefits, retirement benefits, pet insurance, paid holidays, paid Scopely free days, and unlimited paid time off. Base pay offered may vary depending on job-related knowledge, skills, and experience. CA, CO, NJ, NY, and WA Annual Salary Range $17,100 — $253,000 USD About Scopely Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play. Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come. Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play. Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit: https://www.scopely.com/ . Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official website and verify that all Talent Partner communications come from an email address ending in @ scopely.com . Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here: California Privacy Notice and EEA/UK Privacy Notice . Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. KEY RESPONSIBILITIES - Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. - Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. - Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. - Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. - Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. - Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. - Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity’s roadmap. - Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration. QUALIFICATIONS - 5+ years (Senior) or 8+ years (Staff) of software engineering experience. - Strong experience building production data infrastructure systems. - Hands-on experience with batch and/or streaming data processing at scale. - Deep familiarity with data orchestration systems (Airflow, Dagster, or similar). - Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.). - Strong systems thinking around reliability, latency, cost, and complexity tradeoffs. - Experience supporting ML/AI workflows, training pipelines, or evaluation systems. - Familiarity with data quality, lineage, observability, and governance tooling. - Prior ownership of internal platforms used by many teams. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. KEY RESPONSIBILITIES - Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. - Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. - Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. - Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. - Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. - Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. - Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity’s roadmap. - Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration. QUALIFICATIONS - 5+ years (Senior) or 8+ years (Staff) of software engineering experience. - Strong experience building production data infrastructure systems. - Hands-on experience with batch and/or streaming data processing at scale. - Deep familiarity with data orchestration systems (Airflow, Dagster, or similar). - Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.). - Strong systems thinking around reliability, latency, cost, and complexity tradeoffs. - Experience supporting ML/AI workflows, training pipelines, or evaluation systems. - Familiarity with data quality, lineage, observability, and governance tooling. - Prior ownership of internal platforms used by many teams. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Задачи: - Поддержка текущего функционала продукта. - Расширение и развитие функционала действующего продукта. - Анализ логов, данных, выстраивание логических цепочек, построение и проверка гипотез. - Создание и поддержка новых дата-пайплайнов. - Работа с Clickhouse. Написание и оптимизация средних/сложных SQL запросов. - Анализ, подготовка и обработка данных. - Обеспечение качества данных. Предстоит поддерживать и развивать: - Десктопное кроссплатформенное ПО (Java 17+, Swing). - Монолитное ПО, включает в себя клиентскую и серверную части (взаимодействие посредством gRPC). - Отсутствие фрэймворка, используются собственные наработки. - Организация взаимодействия с БД (PostgreSQL, ClickHouse) посредством jdbc, без подключения дополнительных библиотек. - Организация работ механизмов в многопоточном режиме с помощью ExecutorService, CompletableFuture. - Покрытие кода тестами (Mockito, JUnit). - Аналитические запросы и большие объёмы данных (~60 TB). Требования: - Опыт работы в аналогичной роли от 3 лет. - Знание теории реляционных БД, понимание логической, физической моделей БД. - Опыт оптимизации сложных запросов. - Опыт поиска проблем в работающих под высокой нагрузкой системах. - Опыт создания и поддержки ETL-процессов. - Глубокий практический опыт разработки на Python (pandas, numpy). - Опыт работы с Apache Airflow, самостоятельное создание DAG. - Опыт работы с СУБД Clickhouse, написание средних/сложных и нетривиальных SQL-запросов. - Умение самостоятельно брать задачи, по необходимости уточнять требования и доводить до финального результата. - Навык поиска оптимальных решений: умение работать в условиях неопределенности, формулировать вопросы и предлагать решения.

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. We are looking for a passionate engineer to join our Capital Orchestration team, which is responsible for providing liquidity to Affirm by enabling the sale and collateralization of Affirm loan assets. To achieve this, our team develops a robust and extensible platform for on-demand transactions with low operational risk that scales to billions of dollars of collateral movement each month. In simpler terms, we help ensure Affirm has enough money to originate loans, pay merchants, and continue to grow. What You'll Do Build a foundational platform enabling us to reconcile each transaction across systems, partners, and cash movements. Build and integrate data pipelines from a variety of products and systems. Build intuitive and thoughtful user experiences to streamline the workflows of our business counterparts. Develop a deep understanding of the capital systems which power and fund Affirm. Partner with engineers on the team to help improve designs, code quality, and testing. Collaborate with product managers and business counterparts to design best-in-class systems and processes. With the support of your team’s tech lead and manager, you will break down larger projects into individual tasks, deliver them in multiple phases, and collaborate with others to ensure timely delivery of your work. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts What We Look For You have a total of 1.5+ years of experience as a software engineer. Fluency in full stack web development, back end development, event processing, or batch processing. Experience in designing, building, launching, and maintaining products at scale. Strong cross-team communication and collaboration skills. Proficiency with agentic coding. Knowledge of Python, JavaScript/React, Airflow, Spark, Horizon Portal, and SQL is a plus. You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code. You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews. Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. Someone who is proactive, organized, curious, and a self-starter. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. Pay Grade - L Equity Grade - 6 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 base pay range (CA, WA, NY, NJ, CT) per year: $ 165,000 - 225,000 USD USA base pay range (all other U.S. states) per year: $ 146,000 - 206 ,000 USD Additional benefits include: • Flexible Spending Wallets for tech, food and lifestyle • Away Days - wellness days to take off work and recharge • Learning & Development programs • Parental benefits • Employee Resource & Community Groups #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 Workplace: Remote ABOUT US Launched in 2019, Constructor is an AI-first ecommerce search and discovery platform that helps shoppers find the right products at the right time and enables leading global e-commerce brands to drive meaningful revenue and conversion gains. As a Senior Machine Learning Engineer in the Search Quality team, you will improve the e-commerce experience for hundreds of millions of users across the world by building the systems that power relevance for global retailers - from fashion and grocery to electronics and hardware. The mission is to measure search quality, push it higher, and catch degradations before the user does. You will achieve this through a blend of fine-tuned LLMs for relevance judgment, real-time models, and deep offline analysis of query logs. ABOUT THE JOB Your primary focus will be relevance evaluation and quality improvements: - LLM-based evaluation. We fine-tune our own models to assess relevance. This involves teaching the model to understand query intent, represent items from messy catalog data, and align model judgments with real user behavior. - Real-time quality in production. Reranking, filtering, signal computation. Latency is a strict requirement, so quality vs speed tradeoff is constant. - Automated quality monitoring and agentic insights. Pipelines to detect degradations and find underperforming patterns. Agent-based systems that generate actionable recommendations for the product data and search configurations. WHAT MAKES THIS INTERESTING - Multi-domain, multi-language, at scale - 40+ languages, 20+ domains. The models need to generalize across all of them - without per-customer rules or overrides. - No universal ground truth. A grocery retailer and a fashion retailer may have different perceptions on what "relevant" means. - Efficiency at scale. Optimizing and scaling LLM inference across our entire customer base. REQUIREMENTS - 4+ years shipping production ML systems - Experience with search, information retrieval, or recommendation systems - Hands-on experience with fine-tuning, evaluation frameworks, and scaling LLM deployments - Strong Python and PyTorch. Fluency in SQL and data orchestration tools (Spark, Airflow) - Experience designing and running A/B tests to validate model impact - Excellent English communication skills - Experience collaborating in cross-functional teams (ranking, product, data engineering) BENEFITS - 🧠 Work with smart and empathetic people who will help you grow and make a meaningful impact. - 🎉 Regular team offsite events to connect and collaborate. - 🌎 Fully remote team - choose where you live. - 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year. - 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office. - 💻 Apple laptops provided for new employees. - 🧑‍🎓 Training and development budget for every employee, refreshed each year. - 👪 Maternity & Paternity leave for qualified employees. - 💵 Base salary: $80k–$120K USD, depending on knowledge, skills, experience, and interview results - 📈 Stock options - offered in addition to the base salary DIVERSITY, EQUITY, AND INCLUSION AT CONSTRUCTOR At Constructor.io http://Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications. How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice https://constructor.com/recruitment-privacy-notice. After that period your data will be deleted or anonymized.

Location: Yerevan Workplace: OnSite About the role Teza is a systematic trading firm building quantitative strategies across multiple asset classes. We are looking for a DevOps Engineer to own and evolve our infrastructure platform — the systems that our quants, developers, and traders rely on every day. Our infrastructure team is at an inflection point. We have a working platform that supports active trading and research, and we are now investing in making it more robust, observable, and developer-friendly. The successful candidate will have significant influence over the direction of our infrastructure — shaping tooling choices, establishing standards, and building systems that scale with the firm. Location Yerevan, Armenia, Austin, Texas or London, UK What We're Building Toward As a team, we are working toward the following goals. You will play a central role in defining the approach and driving execution: - Full-stack observability** across all internal services — unified metrics, centralized logging, distributed tracing, and actionable alerting — so that engineers and traders have clear, real-time visibility into system health and performance. - Reliable, self-service compute orchestration** spanning Slurm (HPC/ML workloads), Hadoop (batch data processing), and Airflow (workflow scheduling) — enabling researchers and data engineers to run workloads at scale without infrastructure bottlenecks. - Mature secrets management** for trading credentials, API keys, certificates, and service-to-service authentication — with rotation policies, auditing, and tight integration into deployment workflows. - Unified release pipelines** that bring consistency to how diverse applications — trading strategies, data pipelines, and real-time trading systems — move from development to production, each with their own build, test, and deployment needs. - A well-maintained platform foundation** where shared services — identity management, GitHub Actions runners, VPN, observability tooling — stay current and reliable without disrupting active trading. - Strong security posture** across production and research environments — network segmentation, access controls, vulnerability management, and compliance — that evolves alongside the platform rather than being bolted on after the fact. Requirements - Experience building and operating internal platform services for development teams (CI/CD, compute, monitoring, developer tooling) — not just consuming them. - Strong proficiency in Linux systems administration and container orchestration (Docker, Kubernetes, or similar). - Deep understanding of the software development lifecycle and how infrastructure supports engineering teams — from local development through CI to production deployment. - Familiarity with ML and data-intensive workflow requirements: GPU scheduling, large dataset access patterns, experiment tracking, and reproducible compute environments. - Proficiency with at least one major cloud provider (AWS, GCP, or Azure) including networking, IAM, and managed services. - Experience designing and operating hybrid infrastructure — cloud, on-premises, and colocation environments — with an understanding of the tradeoffs between them. - Hands-on programming ability in Python or another scripting language, sufficient to build tooling, automation, and infrastructure-as-code — not just run playbooks. - Solid understanding of core network protocols and services: DNS, LDAP, SMTP, TLS, HTTP, and SSH. - Practical knowledge of infrastructure security: firewall management, access control models (zero-trust, bastion hosts), vulnerability scanning, patch management, and audit logging. Nice to Have - Experience in a trading firm or other environment with strict uptime and latency requirements. - Familiarity with infrastructure-as-code tools (Terraform, Pulumi, Ansible). - Experience with log aggregation and SIEM systems. - Understanding of compliance frameworks relevant to financial services. Benefits - Health, visual and dental insurance - Flexible sick time policy