Вакансии

-управлять командой, состоящей из DS, DE, MLOps. -соблюдать требования и стандарты производственного процесса банка.

💎 Опыт с AWS, Kubernetes, VPC, IAM, EKS, RDS, Strong English.

Location: Berlin, Germany; Helsinki, Finland; London, United Kingdom About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. We are looking for an experienced Data Analytics Engineer to join our growing Tax Data Mart team. This role will be a key contributor to the team and will be responsible for building the tax data operations function for our Deliveroo and Wolt legal entities.  This includes building and operating the data pipelines and infrastructure that power tax analytics and support decision-making across the company. As DoorDash continues to grow its global footprint across multiple business lines, we are looking for a candidate with experience working with Tax teams to gather requirements, and designing scalable data processes to support them.. This person will grow our unique community via your blend of tax, data technology, and process improvement experience. About the Role You will be reporting to the Senior Manager of Tax Data & Operations, and play an integral role in DoorDash’s data function, owning the processes for ingesting, transforming, and controlling our data, ensuring accuracy, and making it available to analytics and business users. As a member of this team, you will lead the design, implementation, and operation of data pipelines and related processes to support the Company’s exponential growth. What you’ll be doing Lead the collection of Tax Data and Reporting requirements through close relationships with Tax team counterparts Design, build, and maintain scalable, reliable data pipelines (ETL/ELT) that serve data across the company Develop and optimize data models and warehouse structures to support analytics and reporting Participate in new business initiatives and identify their impact on existing data system(s) and processes. Work closely with Analytics, Data Science, and business partners in the development and validation of new data sources. Identify and document business, functional and technical requirements to support new business initiatives and to enhance existing system functionality. Leverage AI & AI assisted tooling to build and automate recurring data tasks & pipelines. Monitor data quality, reliability, and observability, and resolve data-related issues for our internal business partners. Participate in defining the Company’s data tooling needs, including the maintenance of existing systems. Prepare documentation related to our data systems and processes. Share knowledge and best practices with engineers and analysts across the team. Our humble expectations You have 7+ years of experience in a Tax data & technology or similar role. Experience using Data Build Tool (DBT) or a similar product to manage data flows. Experience using Claude, Cursor and similar AI tools. You are an expert at using SQL with experience using Snowflake. Proficiency in Python (or a comparable language) for building data pipelines. Experience with modern data stack and orchestration tools such as Airflow, Spark, or Kafka. You have strong attention to detail and analytical, organizational, and problem-solving skills. You’re an independently motivated person with a proven ability to manage multiple projects and prioritize work independently. You have excellent written and verbal communication skills. Project management experience, including creation of project plans, milestones, and due dates. Computer Science, Information Technology, Engineering, or a related degree. Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

Looking for an engineer who has hands-on experience building AI agents that actually execute workflows, not just chat interfaces. You’ll work on agents that connect to APIs and internal systems, use tools, retrieve context, make decisions across multiple steps, and recover when something fails.

The role You will build and lead our Forward Deployed Engineering team: the engineers who connect estaie to the hospitality ecosystem and make those integrations work in production. You own how the team works, what it ships, and the quality bar it holds.

— Тестировать продукт целиком: мобильные приложения, веб, API, взаимодействие сервисов между собой. — Проверять не только то, что описано в acceptance criteria, а систему в целом: граничные случаи, сбои интеграций, поведение при плохой сети и параллельных действиях.

🕹 Список обязанностей: Мониторинг: создать систему, которая регулярно сверяет инвест тезисы с новыми данными и показывает подтверждается тезис, слабеет или требует пересмотра. Данные: Создать point-in-time хранилище: рыночные и фундаментальные данные, документы SEC, стенограммы звонков, новости, внутренняя аналитика.

🌸Work with our engineers and leverage your own knowledge to understand the challenges they face and how to improve their experience. 🌸Contribute to our internal development platform (IDP) by designing, implementing, and maintaining internal tooling and systems.

Looking for an engineer who has hands-on experience building AI agents that actually execute workflows, not just chat interfaces. You’ll work on agents that connect to APIs and internal systems, use tools, retrieve context, make decisions across multiple steps, and recover when something fails.

Ищут Junior QA Engineer в продуктовую команду. Ваша задача - поймать такие вещи до релиза.

Ищем Senior Golang Engineer для работы над high-load backend-системами в betting-продукте. Что важно: — 7+ лет коммерческой разработки; — 4+ последних лет преимущественно с Go; — Обязательный опыт разработки betting-продуктов; — Глубокое понимание Go и его внутренних механизмов: concurrency, memory allocation, GC, data structures; — Сильный SQL и опыт с relational databases; — Production-опыт с Kafka, Kubernetes, Docker, Linux; — Опыт работы с high-load / distributed systems; — English — Intermediate+, Russian — Upper-Intermediate+ Будет плюсом: PostgreSQL, ClickHouse, microservices, DDD / Clean / Hexagonal Architecture, а также опыт с financial/transactional systems. Условия: — Fully Remote — Full-time

Remote - Location: Mostly remote (within Germany), with monthly in-person collaboration at our Berlin officeHours: Part-time, 32 hours per weekContract: Fixed-termSalary: EUR 53,000 – 59,000 (at 32 hours per week)We are building a new capability that turns fragmented,...

Location: Moldova Company Background Coherent Solutions is a global digital product engineering company founded in 1995 and headquartered in Minneapolis, Minnesota. With a presence in nine countries and a team of more than 1,700 engineers, the company provides custom software development and engineering services across web and mobile applications, cloud, DevOps, and data. Coherent Solutions works with clients worldwide to build and scale digital products while fostering a culture of collaboration, transparency, and continuous professional growth. Project Description You will work with senior engineers on internal classical machine learning initiatives. The role combines structured learning, practical delivery, and gradual ownership of increasingly complex tasks. Technologies Python, pandas, NumPy, scikit-learn, Jupyter SQL XGBoost, LightGBM MLflow FastAPI Git, Docker, pytest What You'll Do Prepare and validate structured datasets for machine learning tasks, including cleaning, transformation, encoding, scaling, and missing-value handling; Conduct exploratory data analysis to identify patterns, data quality issues, and opportunities for modeling; Build, test, and compare ML models for tasks such as regression, classification, clustering, dimensionality reduction, and anomaly detection; Develop and select features with guidance from senior engineers; Run experiments, tune model parameters, and evaluate results using appropriate validation approaches and metrics; Help maintain reproducible ML pipelines, notebooks, experiment tracking, and technical documentation; Write and maintain automated tests for data and model-related code; Support the delivery of models through REST APIs or batch-processing workflows; Document model assumptions, results, limitations, and technical decisions; Work closely with senior engineers, incorporate feedback, and gradually take ownership of more complex tasks; Job Requirements 1+ year of hands-on Python development experience, including experience with pandas, NumPy, scikit-learn, and Jupyter; A strong foundation in statistics, probability, and linear algebra, plus exploratory data analysis skills; An understanding of supervised and unsupervised learning, and practical experience with regression, classification, clustering, dimensionality reduction, and anomaly detection; Experience preparing structured datasets, including cleaning, transformation, encoding, scaling, and missing-value handling, plus practical feature engineering and feature-selection skills; An understanding of train/validation/test splits, cross-validation, data leakage, overfitting, and regularization; the ability to select appropriate evaluation metrics, compare models, and perform error analysis; Familiarity with hyperparameter tuning and reproducible ML pipelines; SQL skills for data extraction and analysis; The ability to expose models through REST APIs or batch-processing workflows; Familiarity with Git, automated testing, Docker, and basic model monitoring; The ability to explain model behavior, assumptions, limitations, and results; English at B2 level or higher; Nice To Have XGBoost, time-series analysis, recommendation systems, MLflow, model interpretability, cloud services, production ML monitoring, and GenAI, LLM, RAG, prompt-engineering, or agent-development experience; What Do We Offer The global benefits package includes: Technical and non-technical training for professional and personal growth; Internal conferences and meetups to learn from industry experts; Support and mentorship from an experienced employee to help you professional grow and development; Health insurance; Sports activities to promote a healthy lifestyle; Flexible work options, including remote and hybrid opportunities; Referral program for bringing in new talent; Work anniversary program and additional vacation days.

О нас: Мы команда тестирования продукта NGFW (Next Generation Firewall). Наш продукт призван органично встроиться в сетевую инфраструктуру и обеспечить надежную защиту в сетях передачи данных. Среди наших задач ручное тестирование виртуальных и аппаратных платформ, тестирование интеграций с внешними продуктами, разработка тестового окружения. Обязанности: Подготовка тестовых сценариев, составление отчетов по тестированию; Подготовка тестовых стендов, настройка тестового окружения; Тестирование программного продукта по требованиям и тестовым сценариям; Воспроизведение проблем, регистрация обнаруженных дефектов; Проверка пользовательской документации. Требования к кандидату: Знание и понимание принципов организации сетей передачи данных; диагностика сетевых проблем; Знание и опыт работы с протоколами динамической маршрутизации: OSPF, BGP; Знание ОС Linux на уровне уверенного пользователя; Технический английский (поиск информации, чтение документации). Будет преимуществом: Опыт работы сетевым инженером или администратором NGFW и других средств защиты и мониторинга сетей; Опыт работы с трафик-генераторами.

Firebase, Crashlytics, DataDog), and strong understanding of mobile stability issues: crashes, ANRs, and freezes Proven experience building or owning a mobile QA automation framework (e.g.

💻 Чем предстоит заниматься Проектировать и развивать хранилища данных на PostgreSQL и ClickHouse, обеспечивая высокую нагрузку на запись и чтение. Обеспечивать приём и обработку непрерывных потоков телеметрии: настраивать буферизацию, дедупликацию, корректно работать с опоздавшими событиями.

— Define service-level objectives for production services. — Build and maintain useful reliability dashboards.

Develop and maintain web applications using React or Vue. Build reusable and maintainable frontend components.