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Компания AI research lab 42 — лаборатория, разрабатывающая автономного AI Scientist — систему, способную самостоятельно формулировать гипотезы, проводить эксперименты и находить решения. Задачи: — TradFi Research Lead: построить и возглавить research-направление в traditional markets, разрабатывать MFT-стратегии, строить портфели и risk/execution models, выводить стратегии в production — AI Researcher — Autonomous Research: перейти от ручного quant research к автономной agent-driven системе, генерировать гипотезы, тестировать и оптимизировать стратегии — Quantitative Researcher — Crypto MFT: полный цикл разработки medium-frequency crypto strategies, поиск alpha и backtesting, production и мониторинг live performance Требования к кандидату: — TradFi Research Lead: 5+ лет в systematic quant research, подтверждённый track record прибыльных MFT-стратегий, опыт с equities / futures / options / FX, опыт лидерства — AI Researcher — Autonomous Research: MFT/HFT researcher, сильное понимание market microstructure, статистики и Python/ML, способность формализовать research-процесс для автоматизации — Quantitative Researcher — Crypto MFT: 2+ лет в systematic trading, опыт запуска стратегий в live, глубокое понимание crypto market structure (spot, perps, funding), сильные Python, statistics и ML/DL Условия: — B2B контракт — помощь с релокацией в Амстердам по high skilled migrant visa — оформление в голландскую компанию с 30%ным налоговым рулингом

Location: United Kingdom, London Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role overview We are seeking a Senior Localisation Quality Engineer, a highly skilled and innovative individual who brings together design-phase product thinking, software engineering expertise, localisation awareness, and technical problem solving. The role builds on the core responsibilities of a Senior Localisation QA Engineer, combining strong localization quality expertise with software engineering, automation, and earlier involvement in the product design and development lifecycle. This role is ideal for someone who has worked closely with design teams in Figma, has experience reviewing and validating designs before implementation, understands how localisation impacts product and UI design, and can build scalable technical solutions to improve quality across the product lifecycle. You will partner with design, engineering, product, and localisation teams to identify risks early, improve design quality and localisation readiness, and create tools, systems, and solutions that enable faster and smarter delivery. Rather than focusing only on post-implementation testing, this role emphasises early engagement in the design phase, including reviewing Figma files, prototypes, design systems, user flows, and content structures to ensure they are scalable, testable, and ready for localisation across languages and regions. You will also contribute as a hands-on engineer, building software, automation, integrations, and AI-driven solutions such as agents, assistants, or plugins that improve workflows, validation, and quality decision-making. The ideal candidate combines strong software development skills, experience working with design systems and Figma-based workflows, practical understanding of localisation and internationalisation, and hands-on interest in engineering solutions to product and quality challenges. Responsibilities Design Systems, Figma & Early Product Quality - Partner with designers, product managers, engineers, and the wider Localisation team to help identify localisation risks early in the design phase. - Support the Localisation team by reviewing Figma designs and providing technical and design expertise to improve localisation readiness before implementation. - Help the Localisation team identify and address design risks such as text expansion, truncation, layout issues, bidirectional languages, locale-aware components, and cross-market scalability. - .Build and improve tools, automation, and processes that enable Localisation QA to identify issues earlier and at scale, including automated design and content validation, screenshot capture, localisation readiness checks, and quality validation across languages and regions. - Work with the wider Localisation team to define best practices and guidance that help designers and engineers create products that are ready for localisation from the start. - Collaborate with design teams on design systems, UI patterns, and content structures to improve quality and reduce downstream issues before code is written. - Help define quality expectations, localisation considerations, and implementation guidance directly from design artefacts and product requirements. Localisation Quality & Testing - Perform hands-on Localisation QA testing across multiple languages, platforms, products, and regions, including linguistic, functional, visual, and internationalisation testing. - Lead and support complex localisation quality initiatives, while contributing directly to day-to-day testing when needed. - Develop and improve localisation test strategies covering linguistic, functional, visual, and internationalisation quality. - Investigate complex localisation and internationalisation issues and work with engineering, design, product, and localisation teams to identify root causes and appropriate solutions. - Help define localisation quality standards and ensure localisation considerations are integrated throughout the product development lifecycle, from design through implementation and release. Software Engineering & Technical Solutions - Design and develop software, internal tools, automation, and reusable services that improve product quality, design validation, and workflow efficiency. - Build scalable software solutions that support validation of product experiences across design, development, and release stages. - Contribute to codebases, frameworks, and technical infrastructure that improve quality signals, design consistency, and localisation support. - Partner with software engineers to improve feature readiness, system testability, and quality-by-design practices. - Integrate validation and quality workflows into modern development environments and CI/CD pipelines where appropriate. Automation, Tooling & Process Improvement - Identify opportunities to reduce manual work and improve localisation and product quality across design, engineering, and localisation workflows. - Design and build tools, automation, integrations, or other technical solutions that help teams review designs, validate content, detect issues, and improve workflows. - Choose the right technical approach for each problem, which may include traditional automation, scripts, plugins, APIs, AI/LLMs, or existing internal tools. - Develop solutions that help identify localisation and quality issues earlier in the product lifecycle and provide faster feedback to teams. - Prototype and test new approaches, measure their value, and develop successful solutions so they can be used by the wider Localisation team and potentially other teams. Cross-Functional Leadership - Act as a bridge across design, engineering, product, and localisation teams, helping align quality, scalability, and user experience goals. - Communicate clearly with both technical and non-technical stakeholders, translating complex issues into actionable recommendations. - Influence teams toward a shift-left, design-led quality approach. - Contribute to planning, design reviews, implementation discussions, and release readiness with a focus on preventing issues early. - Provide technical guidance and mentorship to members of the Localisation team, sharing engineering, automation, localisation, and quality best practices. - Promote a culture of innovation, technical excellence, and continuous improvement. Qualifications Education BS/BA in Computer Science, Engineering, Human-Computer Interaction, Design Technology, or a related field, or equivalent practical experience. Experience - 5+ years of experience in software engineering, design technology, quality engineering, localisation engineering, or related product development roles. - Strong hands-on experience in software development, with the ability to build tools, systems, integrations, or automation that solve real product challenges. - Experience working closely with design teams and Figma workflows, including reviewing designs, prototypes, component systems, and user journeys before implementation. - Experience validating or testing Figma designs for quality, scalability, localisation readiness, and implementation feasibility. - Practical understanding of localisation and internationalisation principles in digital products. - Experience with localisation quality or testing across multilingual products, platforms, or regions. - Strong programming skills in one or more languages such as Python, JavaScript, TypeScript, or Java. - Hands-on experience building or experimenting with AI agents, plugins, copilots, or intelligent workflow tools. - Experience with APIs, structured data, system integrations, and modern software development practices. - Familiarity with developer collaboration tools such as GitHub, JIRA, and Confluence. - Strong understanding of product development lifecycle, Agile methodologies, and cross-functional delivery models. Soft Skills Excellent written and verbal communication skills. Strong product thinking and problem-solving ability. Comfortable operating across design, engineering, product, and localisation domains. Self-motivated, adaptable, and effective in a fast-paced environment. Strong organisational and stakeholder management skills. Desired qualifications Experience with Figma design systems, component libraries, and design-to-development workflows. Experience creating or contributing to Figma plugins, design validation tools, or workflow extensions. Experience building AI agents, assistants, or plugins for design, engineering, content, or localisation use cases. Experience influencing product quality earlier in the lifecycle through design review and engineering collaboration. Familiarity with multilingual product development, translation workflows, or international launch readiness. Experience in video games, consumer technology, digital entertainment, or large-scale product environments. Fluency in one or more non-English languages is a plus. What We Offer The opportunity to shape next-generation quality, localisation, and design-to-development practices. A dynamic and inclusive workplace where technical excellence, collaboration, and global impact thrive. Competitive compensation, performance bonuses, and comprehensive benefits. Career growth opportunities in a forward-looking engineering environment focused on quality, localisation, automation, intelligent systems, and early product excellence. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: United Kingdom (Hybrid); United Kingdom (Remote); Spain; Netherlands Workplace: Hybrid Most money apps talk at you. Cleo talks back ✨ We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process 💰 For everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money. We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in. Follow us on LinkedIn https://www.linkedin.com/company/cleo-ai/ for new features and the occasional roast 🔥 Meet the team 👥 Here at Cleo, we have ~45 ML engineers ✨ They are the builders behind the AI that powers our product. They design experiments, create models that personalise financial insights, deploy fraud detection systems and scale our conversational AI, making sure that what we build genuinely helps people feel better about their money. From shaping product features and building the models that personalise our users' money journeys, to tackling fraud, scaling our systems and giving leaders the insights they need, our data team is at the heart of it all.   About the role ✍️ We're hiring a Machine Learning Tech Lead to take on technical leadership and ownership of the Payments Intelligence team, managing a team of circa 4 MLEs. This team is responsible for optimising Cleo's payments systems - covering both credit collections and subscription retention - a workstream with a direct impact on the company's financial performance. You'll work closely with your cross-functional squad to understand business issues, then use your ML engineering skills to deploy best-in-class models that move the bottom line. - Lead and manage a team of 4 MLEs - Deploy machine learning models into production - classifiers, payments recommendation systems, and any other model that can have impact, typically working with tabular data rather than language models - Collaborate with product managers, backend engineers, and analysts, playing an active role in planning and sequencing work for the squad - Work closely with engineers to make sure the right data is collected to build future machine learning models What we're looking for 🕵 - At least 5 years of experience in data science, ML engineering, or related roles - At least 1 year of management experience, ideally of a small team - Ability to write production-quality Python code - Experience deploying machine learning models into production - Track record in payments, pricing, risk decisioning, or other business process optimisation problems - Comfortable with complexity, and developing a holistic understanding of a system in order to propose and build solutions - A strong ability to communicate findings to non-technical stakeholders in a concise and engaging manner - Nice to have: experience with credit collections WHAT WE OFFER We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub https://meetcleo.notion.site/Cleo-Candidate-Hub-3b95c63b874580e9a068fdc6c8929ebf 👈 WHAT MATTERS Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits. We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know. We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Задачи: — Развивать antifraud-направление: определять стратегию, roadmap и приоритеты; — Руководить командой scientists/developers и развивать экспертизу; — Разрабатывать и внедрять antifraud-правила, scoring-модели и автоматизировать ручные процессы; — Развивать единый antifraud-сервис и выводить решения в production. Требования: — Опыт построения fraud prevention в iGaming, fintech, marketplace или payments; — Опыт работы с разными типами фрода и управления antifraud-направлением; — Опыт управления разработкой в роли лида + готовность самостоятельно писать и выводить код в production; — Уверенный SQL и Python; опыт Machine Learning для classification и scoring-задач будет плюсом; — Опыт взаимодействия с бизнесом и другими стейкхолдерами. Условия: — Компенсация на основании ваших ожиданий; — 24 дня оплачиваемого отпуска; — Корпоративные занятия английским; — Для сотрудников офиса на Кипре - компенсация питания, GYM & SPA в офисе и корпоративные мероприятия.

Location: Amsterdam; Spain; Poland; Cyprus; United Kingdom; Germany Workplace: remote About Finom   Finom is a European tech startup headquartered in Amsterdam, and we’re on a journey towards revolutionizing the financial landscape for entrepreneurs worldwide. Our mission is to develop an all-in-one financial B2B solution that integrates banking functions, accounting, financial management, and invoicing into a seamless, mobile-first platform.   We recently closed a €115 million Series C equity round (around $133 million), bringing our total funding to approximately $346 million. This significant investment follows a $105 million growth funding round from General Catalyst, a long-term backer since 2021 known for supporting companies like Airbnb, HubSpot, KAYAK, and Stripe.   Finom's platform goes beyond traditional banking, offering invoicing and a growing suite of features, including AI-enabled accounting, aiming to simplify financial management for entrepreneurs. We're actively expanding our reach across key EU markets like Germany, France, the Netherlands, Italy, and Spain.   At Finom, we’re not just redefining the entrepreneurial experience — we’re empowering our employees to make a real difference. Your work matters, and your impact extends far beyond product metrics. We nurture innovation and an inspiring work environment where bold ideas thrive, prioritizing thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and our business as a whole.   Maintaining our start-up spirit, we prioritize thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and, of course, our business. We are looking for a Senior Treasury Manager to build and run Finom's treasury function. Finom safeguards a significant book of customer funds across its regulated entities. Net interest income on that book is a meaningful revenue line, and it will grow. Today the function is up and running: the money is placed, the investment policy is in place, and a large part of the book sits with an external asset manager. What we are building now is the machinery around it — an evidenced limit framework, look-through into what our managers actually hold, automated investment accounting, and a reconciled NII number we can defend to an auditor and a regulator. That is the job. You will take part in building it, and you will run it while it is being built. This is a hands-on role at the intersection of regulation, liquidity, and commercial impact — not a back-office position. It suits someone who has done this before in a regulated environment and wants to do it again without four layers of committee above them. What you'll own Liquidity and funding Daily liquidity positioning and float management across entities and accounts Intraday funding of payment channels; nostro and correspondent account management Collateral and minimum-balance obligations across card schemes, T2, and credit providers Contingency funding — the playbook for the day we need €20m by tomorrow morning A daily treasury balance sheet — net liquidity and net capital available — that reconciles Safeguarding and portfolio Portfolio management of safeguarded client funds: term deposits, MMFs, short-dated debt, held directly and via external managers Safeguarding adequacy: shortfall detection, top-up execution, same-currency discipline Instrument eligibility screening under CRR risk-weight, maturity and WAL constraints, and UCITS/MMF rules Independent, evidenced validation that externally managed allocations sit inside mandate — position-level look-through, daily monitoring of concentration, maturity, WAL and credit quality, breach escalation NII forecasting, attribution, and reconciled performance reporting; treasury inputs into the financial model and company forecast Governance and controls Ownership of the investment policy, limit framework, and eligible-instrument register Treasury governance: decision pack, agenda, decision log, and delegated-authority register Pre-deal checks and post-trade evidencing, designed so that the first line executes and the second line challenges Covenant tracking across credit facilities Regulator, external audit, and second-line engagement on treasury and safeguarding matters Systems and data Selection and implementation of investment accounting and treasury tooling — a Clearwater/Advent-class implementation is already in flight and will be yours Custodian, asset-manager and bank data feeds; API connectivity where it exists and pragmatic alternatives where it doesn't Replacing manual spreadsheet processes with something that survives your holiday Commercial Bank, custodian, broker and asset-manager relationships: onboarding, commercial terms, mandate setting, service review Challenging our managers on allocation, transparency and fees — and changing them if the answers are weak What good looks like in the first 12 months Investment policy and limit framework live, with treasury governance running on a documented decision log Daily, evidenced mandate compliance across the full book — we can answer "are we inside the boundaries?" in minutes, not weeks Investment accounting platform implemented; monthly close on the portfolio no longer manual An NII number that is reconciled, attributed, and forecastable A contingency liquidity playbook that has been tested rather than written Who you are 5+ years in treasury, ALM, fixed income, or portfolio management at a regulated financial institution, EMI/PI, or asset manager Direct experience with client money or safeguarding under PSD2 / EMD — core to this role, not adjacent to it Experience building or materially rebuilding a treasury function, not only operating inside an established one Strong command of bond math, yield and duration, MMF mechanics, and credit and concentration risk at instrument level Track record of automating manual treasury processes and implementing treasury or investment accounting systems Comfortable working with position-level data directly — you can interrogate a portfolio file rather than wait for a report Experience with regulators, external audit, and external asset managers (mandate setting, IMA terms, performance challenge) Sound judgement under time pressure in a lean environment with real accountability and limited cover Strong Excel skills Fluent English Nice to have Familiarity with IFRS 9 or Dutch GAAP (RJ 290) financial instrument accounting SQL or Python Experience in a firm transitioning toward a banking licence Experience using AI tools (e.g. LLMs, copilots) to accelerate analytical and reporting workflows What You Will Get In Return   Make a genuine impact on the product   Join our upward trajectory, and grow with us. We provide the resources and opportunities for continuous personal and professional development, empowering you to make a genuine impact on our evolving product.   Work in the EU   Embark on this exciting journey with us and enjoy the flexibility of traveling and working remotely or in a hybrid model across Europe.   Become a stock options holder   Unlock your inner entrepreneur and align your aspirations with ours through our Stock Options Program. This exciting opportunity is available to every team member, from junior team members to our founders.   Receive unwavering support and care   Finom stands by you at every step, embodying our commitment to your well-being and success reflected in our modern, friendly, and eco-conscious corporate culture. We offer constant support and care to ensure your Finom experience is successful and fulfilling.   Work & Swim program   Immerse yourself in our exclusive Work & Swim Program. Spend one month in a comfortable corporate apartment in enchanting Cyprus. It's the ideal opportunity to strike the perfect work-life balance while enjoying breathtaking Mediterranean views.   Equal Opportunity Statement    At Finom, we're an equal opportunity employer and value diversity at our company. We embrace diversity and invite applications from all walks of life. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, disability status, or other applicable legally protected characteristics.

Location: Dublin, Dublin, Ireland, EMEA From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. ​ During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role Fivetran is building data pipelines to power the modern data stack for thousands of companies. We’re looking for a high-performance, experienced engineer to be a part of a team of Site Reliability Engineers. You will be working closely with engineering teams, product managers, as well as support, sales engineers and solution architects to build the future of the Fivetran Data Platform Reliability. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Cloud Service Providers(CSPs): AWS, Azure and Google Cloud Kubernetes: Managed Kubernetes services (EKS, AKS and GKE) Continuous Integration tools: github actions, Buildkite Continuous Delivery: ArgoCd Databases: Postgres and all the major Databases Languages: Go, Java Scripts: Typescript, Python, Shell IaC: Terraform and Pulumi RESTful API: FastAPI Cloud networking: Privatelinks in Azure and AWS, Private service connect in GCP and site-to-site VPN tunnels in all 3 major cloud service providers - AWS, Azure and Google Cloud What You’ll Do As a member of the Site  Reliability Engineering team, you will take ownership over the overall performance and reliability of Fivetran’s infrastructure, the robustness of the deployment pipeline, as well as timely and effective incident response and resolution. You will take responsibility for the growth and stability of Fivetran’s infrastructure, and be a key player driving effective incident response and overall issue avoidance. Responsible for ongoing reliability and robustness of Fivetran’s production infrastructure by monitoring availability, capacity, and throughput. Evolve systems by adding reliability into our product roadmap Coordinate the re-prioritise or fix critical bugs for support or sales requirements as needed Make recommendations to production infrastructure by interfacing with engineering to ensure 100% availability Ensure scalable artifacts deployment to all environments by automation scripts Constantly monitor infrastructure vulnerabilities and remedy them by working with the security team Skills We’re Looking For Expertise in managed Kubernetes (EKS, AKS, and GKE). Knowledge of Cloud Platforms and related tooling: AWS, Azure, Google Cloud (GCP), Terraform, Ansible, Buildkite, Pulumi and ArgoCD. Experience in Python/Shell scripting and Go Language. Bonus if you have Java. Experience with Linux operating systems internals and administration Experience with cloud networking like Site-to-Site VPNs, Privatelinks and Private Service connect (GCP) AI-assisted engineering: Experience using AI tools for code review, automation, incident analysis, documentation, and reducing operational toil. Bonus Skills​ 5+  years of  experience working with SaaS products at scale Experience with databases such as PostgreSQL #LI-IM1 #LI-HYBRID Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Требования: • Опыт работы в качестве аналитика от трех лет • Опыт работы с высоконагруженными СУБД ORACLE • Опыт работы с Python • Знание SQL, DWH Обязанности: • Анализ полноты и корректности требований в поступающих заявках на отчетность • Анализ доступности источников информации, необходимых для реализации заявки • Внесение предложений по схемы предоставления отчетности • Планирование графика формирования периодической отчетности на серверах • Анализ запросов нерегламентированной отчетности по заявкам ITSM, формирование технических требований

Требования к кандидату: — Опыт работы DevOps-инженером от 7 лет; — Установка и администрирование ОС Linux / Ubuntu / Talos; — Работа на уровне железа/сети: обновление прошивок сетевых карт, настройка бондинга (bonding); — Создание и поддержка кластеров: K8s, Kafka, Greenplum, Cassandra, Hadoop, Apache Ozone; — Глубокое понимание принципов DevOps и выстроенных процессов CI/CD; — Опыт работы с системами управления конфигурациями (Ansible) и оркестраторами; — Уверенная автоматизация рутинных процессов на Python и Bash; — Навыки написания скриптов автоматизации и опыт разработки веб-сервисов (API) на Python; — Отличное владение Docker и Git; — Опыт администрирования реляционных баз данных на уровне администратора.

Мы ищем: Талантливого ML-разработчика с временными рядами и классикой, в области прогнозирования в ритейле на стажировку, которому предстоит работать над интересными высоконагруженными проектами. Требования: — Опыт в Data Science / Machine Learning от 2 лет; — Прагматизм: готовность искать рабочие решения, а не идеальные, но нереализуемые модели; — Глубокое знание Python, SQL и PySpark; — Разработка ETL-процессов для обработки больших данных (чтение, трансформация, агрегация, запись); — Оптимизация Spark-запросов (партиционирование, кэширование, работа с broadcast-переменными); — Знание основных ML-фреймворков (Scikit-learn, TensorFlow/PyTorch); — Опыт работы с данными: обработка, анализ, feature engineering. Будет плюсом: — Опыт продакшн-разработки (не только исследования); — Понимание, как устроены процессы в бизнесе, а не только в Jupyter Notebook; — Умение запускать ML-модели в PySpark; — Использование Spark MLlib для распределенного обучения; — Работа с PySpark Pandas UDFs для эффективного применения ML-моделей к большим данным. Условия: — Работа в команде экспертов; — Широкий технологический стек, сотни проектов; — Гибкий график работы, который позволяет высыпаться и выделять время на хобби; — Возможность разрабатывать IT-решения для разных отраслей, пробовать новые технологии; — Процессы удаленной работы и просторные офисы с зонами коворкинга; — Возможность прокачаться во всех интересующих направлениях: стать тимлидом, архитектором, разработчиком full-stack; — Развитая система наставничества, сертификация за счёт компании, участие в конференциях, изучение английского языка; — Активный обмен опытом, внутренние и внешние митапы, хакатоны, доклады по развитию hard и soft skills; — 50+ клубов по интересам и профессиональных сообществ внутри компании; — Корпоративная база знаний и социальная сеть для удобства общения с каждым из 1500+ сотрудников. Дополнительно: — Набор осуществляется по ИТ специальностям, указанным в Приказе Минцифры № 27 от 22.01.2026г. — Решение Министерства цифрового развития, связи и массовых коммуникаций РФ о предоставлении государственной аккредитации организации от 10.03.2022 №АО-20220309-3771014210-3

Задачи: — Проектирование и разработка сервисов с применением принципов DDD. — Формирование культуры тестирования: написание unit/integration тестов, обеспечение необходимого уровня покрытия и тестируемости кода. — Наблюдаемость на стороне кода: метрики, структурные логи и сквозная трассировка запросов в сервисах. — Принятие и защита архитектурных решений в команде (контексты С3-С4 из модели C4), ведение ADR (Architecture Decision Records). — Развитие сделочного контура (заказы и платежи): асинхронное межсервисное взаимодействие, идемпотентность денежных операций, транзакционный outbox, повторные попытки и отложенные срабатывания. Требования: — Опыт коммерческой бэкенд-разработки от 4-х лет на Go или Python. — Владеть вторым языком с первого дня не требуется: вход обеспечивается онбордингом и ревью внутри команды. — Уверенное знание алгоритмов и структур данных, умение применять их для решения практических задач. — Уверенный опыт работы с PostgreSQL: оптимизация запросов, индексы, транзакции, уровни изоляции и блокировки, понимание планов выполнения (EXPLAIN), опыт ведения миграций. — Работа с ORM (GORM) с пониманием генерируемого SQL. — Умение проектировать и реализовывать API (REST, gRPC), понимание версионирования и контрактного тестирования. — Уверенный опыт работы с Linux, Docker, Kubernetes (базовое понимание/опыт написания манифестов), настройка CI/CD пайплайнов. — Глубокое понимание принципов чистого кода, SOLID, DDD, микросервисной архитектуры и паттернов распределенных систем. — Уверенный опыт работы с брокерами сообщений (RabbitMQ, Kafka или аналоги): понимание гарантий доставки, обработка ошибок и dead-letter queues, идемпотентность и транзакционный outbox. — Плюсом: опыт вывода Python-сервисов в продакшен (FastAPI, Django/DRF), опыт платёжного или финансового контура, интеграции с LLM-провайдерами. — Опыт AI-assisted development: использование AI-ассистентов разработки (Cursor, GitHub Copilot, Claude Code, Codex) для декомпозиции задач, подготовки черновиков кода, рефакторинга, написания тестов, поиска дефектов и работы с документацией. — Умение критически проверять результаты AI: валидировать бизнес-логику, соответствие архитектуре и кодстайлу, покрытие тестами, производительность, безопасность и лицензионные риски. — Готовность нести персональную ответственность за код и технические решения, независимо от использования AI-инструментов.

Проект: Телеком Требования: Опыт работы DevOps от 7 лет Установка и администрирование ОС Linux/Ubuntu/Talos Обновление прошивок сетевых карт, настройка бондинга Создание и поддержка кластеров Kubernetes, Kafka, Greenplum, Cassandra, Hadoop, Apache Ozone Понимание принципов работы DevOps, процессов CI/CD Опыт работы с системой управления конфигурацией Ansible Опыт работы с оркестраторами Автоматизация на Python, bash Навыки работы с Docker Умение работать с git Опыт написания веб сервисов (api) на python Написание скриптов по автоматизации на python Опыт работы с реляционными БД на уровне администратора Очень важен опыт с Apache Ozone Условия: ИП до 1300 руб/час (фуллтайм) Сроки проекта: 6 мес (с возможной пролонгацией) Гражданство РФ и локация РФ (удаленка) Потребуется оформление по ТК РФ по совместительству для доступов

Задачи: — Управление командами Data Analysts и Data Scientists, распределение задач, развитие экспертизы и формирование рабочих процессов. — Формирование и развитие data-driven стратегии направления Soft Collection. — Анализ поведения клиентов и эффективности стратегий коммуникации с клиентами. — Разработка и внедрение ML-моделей для прогнозирования вероятности платежа, сегментации клиентов, определения оптимального канала и времени коммуникации, приоритизации клиентов и оценки эффективности стратегий collection. — Разработка стратегий Decisioning / treatment для определения кому, когда и каким способом осуществлять коммуникацию. — Проведение A/B-тестов и uplift-исследований, оценка причинно-следственного воздействия стратегий взыскания. — Развитие системы KPI и метрик направления: cure rate, roll rate, recovery rate, collection rate, cost-to-collect, ROI и других бизнес-метрик. — Создание аналитических витрин, дашбордов и систем мониторинга эффективности стратегий и моделей. — Взаимодействие с бизнесом, Collection, Risk, IT, Data Engineering и другими подразделениями. — Преобразование бизнес-задач в аналитические и ML-задачи, обеспечение внедрения в production. — Ответственность за качество моделей, мониторинг производительности и регулярный пересмотр стратегий. — Развитие культуры experimentation и принятия решений на основе данных. Требования: — Уверенное владение Python: pandas, numpy, sklearn и ML-библиотеки. — Продвинутый уровень SQL. — Хорошее понимание статистики, ML и методов оценки моделей. — Опыт в A/B-тестах, propensity-моделях, классификации, сегментации и прогнозировании. — Знание банковских/финансовых метрик и кредитных процессов — большой плюс. — Опыт работы с большими данными и распределёнными вычислениями — преимущество. — Опыт разработки аналитических решений и ML-моделей от постановки задачи до внедрения в production. — Понимание принципов MLOps и мониторинга моделей — преимущество. — Опыт работы с BI-инструментами и созданием управленческих дашбордов. — Опыт управления командами аналитиков / Data Scientists или техническое лидерство. — Умение самостоятельно формировать roadmap направления. — Сильные коммуникативные навыки и умение говорить на языке бизнеса и финансовых результатов. — Умение декомпозировать сложные задачи и расставлять приоритеты. — Ориентация не только на качество аналитики или моделей, но и на бизнес-эффект. — Способность развивать сотрудников и повышать профессиональный уровень команды.

Location: New York, New York; San Francisco Bay Area, California Workplace: remote We build production AI systems for enterprises. Financial services, healthcare companies, PE-backed operators. We are a Select-tier partner in Anthropic's Claude Partner Network, among the first integrators selected. Every one of those systems has two stories. What we built, and why it changed the economics of the business that bought it. Most technical marketing tells the first and bores the buyer. We want one person who can tell both, and build things themselves. Not a marketer who uses AI tools. Not an engineer who writes copy. Someone who moves between the two without noticing the border. What you will do: Tell both halves of the story. Sit close to the teams shipping these systems, understand what was actually hard, and translate it into video, writing, and demos that travel. Then go a level up: what the system changed for the operator, what it cost, what it replaced, why the CFO signed. Shape how Provectus is positioned. Not just the case studies but the argument above them. What we stand for, which problems we claim, where we say no. You will have a real hand in that, not a style guide to follow. Build the tools that make the marketing work. A scraper that watches what our market is saying. An agent that drafts case studies from delivery artifacts. A microsite for a launch. A dashboard showing which stories moved pipeline. You write the code. You do not file a ticket and wait. Own channels outright. Write, publish, and measure across LinkedIn, YouTube, X, and whatever channel matters six months from now that does not matter today. Run experiments and kill the ones that lose. Real budget, real autonomy, in exchange for showing your numbers. What we are looking for: You have shipped things people used. A side project, a channel with an audience, a tool, a launch. We care more about what you made than where you worked. You write well, and you have a point of view. You can hold attention for 90 seconds on video and 900 words on a page. You are curious about how companies make money. You can read a business case and find the part that actually matters. You can sit with a CFO or a PE operator and not reach for features. You code. Python or TypeScript, comfortably. You use Claude Code, Cursor, or equivalent every day and you have opinions about them. You have built something agentic that does actual work. You are interested in AI for real. You read the papers, or the people who read the papers, and you have changed your mind about something in the last six months. You are anywhere from your first job to your tenth year. Three levels, one bar: what have you made. If you are early, show us an internship where the bar was high and a portfolio with range. If you are senior, tell us what you built with your own hands in the last 90 days. You are in New York or San Francisco, or you will be. What we offer: Base salary of $80,000 to $180,000 depending on level and location, plus a performance bonus. Direct access to the people building the systems and the executives selling them. Small team, no layers between you and the work. A budget for tools, models, and experiments, with no approval chain under a threshold. Promotion tied to output, not tenure. 401(k) profit sharing plan after probation period Unlimited PTO policy Medical, Visual and Dental insurance How to apply: No cover letter. Send three links: something you wrote, something you built, and something you posted that got a reaction. One paragraph on why the third one worked. Then, two sentences on a company whose positioning you think is wrong and what you would change. Base salary depends on level and location, plus a performance bonus.

Location: EMEA; Romania; Bulgaria; Kenya; Portugal; United Kingdom; Spain; Brazil; South Africa; Argentina; Armenia Workplace: Remote ✨ ONE PLATFORM, A WHOLE WORLD OF OPPORTUNITY The best jobs have always clustered in a handful of the world's wealthiest cities. But talent is everywhere. Oyster set out to close that gap - building a global employment platform that lets companies hire, pay, and care for brilliant people anywhere. We're proof that a high-performing culture doesn't need an office. Distributed across 60+ countries since 2020, we've built something the industry keeps noticing: - Ranked #10 of 250 on TIME and Statista's 2026 list of America's Top WorkTech Companies https://www.oysterhr.com/library/oyster-hr-named-10-of-americas-top-worktech-companies-of-2026-by-time - Named one of America's Greatest Startup Workplaces 2026 https://www.oysterhr.com/library/oyster-2026-newsweek-award by Newsweek - A G2 Spring 2026 Leader https://www.oysterhr.com/library/oyster-named-best-roi-for-any-global-employment-platform-for-g2-spring-2026 across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance - The only B Corp-certified global employment platform ~ independently verified since 2023 Two of those rankings measured our business impact from the outside. One measured how our own people feel about working here. They landed in the same place ~ because at Oyster, culture and performance aren't separate conversations. They're the same one. And we're just getting started. If you want to do the best work of your career alongside people who care as much as you do, we'd love for you to apply. 👩‍💻 THE ROLE Location: While this position is posted in a specific location, all of Oyster’s positions are fully remote and you can work from home. Forever. To create the best experience for our new hire, this role requires you to be based within UTC−6 to UTC+3. Oyster’s Data Engineering team is building the foundational AI platform layer that will enable teams across Oyster to develop, deploy, and operate secure, production-grade AI capabilities. As a Senior Data Engineer focused on AI Platform, you’ll work at the intersection of data engineering, platform engineering, and applied AI. You’ll build the data pipelines, services, integrations, and reusable platform capabilities that power AI use cases across Oyster. You’ll leverage Oyster’s existing AWS and Snowflake data platform to make enterprise data accessible, reliable, secure, and useful for AI, supporting capabilities such as LLMs, RAG, embeddings, vector search, AI agents, tool calling, and AI workflows. This is not a traditional data engineering role focused primarily on analytics pipelines or reporting. You’ll help define and build the data and platform foundations that let AI systems move from experimentation to reliable production, working closely with Engineering, Product, IT, and other teams across Oyster. Key Responsibilities - Design and build data pipelines and platform capabilities that support AI applications, knowledge systems, and AI workflows. - Build and maintain data and knowledge pipelines for ingestion, transformation, chunking, embeddings, retrieval, vector search, metadata, and knowledge management. - Develop secure, reusable ways for AI systems to access enterprise data and systems using APIs, MCP, tool calling, and similar patterns. - Build reusable services, libraries, frameworks, and developer tooling that make it easier for engineering teams to build and productionize AI capabilities. - Apply strong data engineering practices around data modeling, data quality, lineage, access, reliability, and governance to AI-related data and systems. - Help establish patterns for AI deployment, observability, evaluation, and lifecycle management, including quality, latency, reliability, security, and cost. - Partner with engineers and stakeholders to take AI use cases from prototype to production, ensuring the underlying data and infrastructure are scalable and maintainable. - Ensure AI platform capabilities meet Oyster’s security, privacy, access control, and data governance requirements. - Evaluate emerging AI and data technologies and determine where they can create meaningful value for Oyster. Core Requirements - 5+ years of experience in data engineering, platform engineering, backend engineering, ML engineering, or a related discipline, with experience building and operating production systems. - Strong Python and SQL skills. - Strong data engineering fundamentals, including data pipelines, data modeling, data quality, orchestration, and secure data access. - Experience with Snowflake, Databricks, or comparable modern data platforms, and tools such as dbt, Airflow, or similar. - Hands-on experience building or supporting production systems using LLMs / generative AI. - Practical experience with one or more of RAG, embeddings, vector search, tool/function calling, AI agents, or enterprise knowledge systems. - Experience building data or platform capabilities that are reusable across teams, rather than only developing one-off solutions. - Experience taking systems from experimentation to reliable production, including considerations around scalability, observability, performance, and maintainability. - Solid understanding of security, authentication/authorization, privacy, and data governance, particularly in the context of enterprise data. - Strong communicator who can work across Engineering, Product, and IT to turn ambiguous AI and data problems into practical engineering solutions. Bonus - Experience with AWS Bedrock or other managed foundation-model platforms. - Hands-on experience with MCP (Model Context Protocol) or similar approaches for connecting AI systems to enterprise tools and data. - Experience with LLM evaluation, observability, monitoring, or AI quality. - Experience with LangChain, LangGraph, or similar frameworks. - Experience with vector databases or search technologies. - Experience implementing AI security, governance, or responsible AI practices. - Experience building internal developer platforms, SDKs, APIs, or reusable infrastructure for engineering teams. - Experience working across data engineering and AI/ML platform environments. YOU'LL ALSO NEED - A reliable home internet connection (or be able to get one). - Fluent English language skills. HOW WE WORK TOGETHER AT OYSTER Our values guide the work we do, the decisions we make, and the culture that makes Oyster what it is. We make it happen—progress is our default setting. We drive change, we build and give trust, and we move as one united team. Our mission is to create a more equal world of work: helping companies everywhere hire, pay, and care for talent anywhere. Everything we do ladders up to our mission. We embrace asynchronous, collaborative work and share how we operate in the Oyster Public HQ https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d so other global teams can learn from us. HOW YOU WORK With diverse locations, cultures, and needs, we created How YOU Work; https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395 a program supporting your whole human experience at Oyster: - Work from anywhere: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere. - Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country. - Mental health support: Access Plumm https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7, our mental well-being service. - Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet to spend on a wide range of options. - Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally. - WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly. ✨ THE BEST JOBS SHOULD BE AVAILABLE TO EVERYONE  We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment. Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email jobs@oysterhr.com with the subject line: Interview Accommodations. Our available positions are on our careers page. Our team will only contact you from an @oysterhr.com email, and we will never ask for money as part of an interview process or job offer. If you receive a suspicious email about Oyster jobs or are directed to a site other than www.oysterhr.com/careers http://www.oysterhr.com/careers, please report it via our Compliance and Ethics Helpline https://faceup.com/c/8tpzyyye.

Location: New York, New York; San Francisco Bay Area, California Workplace: remote We build production AI systems for enterprises. Financial services, healthcare companies, PE-backed operators. We are a Select-tier partner in Anthropic's Claude Partner Network, among the first integrators selected. Every one of those systems has two stories. What we built, and why it changed the economics of the business that bought it. Most technical marketing tells the first and bores the buyer. We want one person who can tell both, and build things themselves. Not a marketer who uses AI tools. Not an engineer who writes copy. Someone who moves between the two without noticing the border. What you will do: Tell both halves of the story. Sit close to the teams shipping these systems, understand what was actually hard, and translate it into video, writing, and demos that travel. Then go a level up: what the system changed for the operator, what it cost, what it replaced, why the CFO signed. Shape how Provectus is positioned. Not just the case studies but the argument above them. What we stand for, which problems we claim, where we say no. You will have a real hand in that, not a style guide to follow. Build the tools that make the marketing work. A scraper that watches what our market is saying. An agent that drafts case studies from delivery artifacts. A microsite for a launch. A dashboard showing which stories moved pipeline. You write the code. You do not file a ticket and wait. Own channels outright. Write, publish, and measure across LinkedIn, YouTube, X, and whatever channel matters six months from now that does not matter today. Run experiments and kill the ones that lose. Real budget, real autonomy, in exchange for showing your numbers. What we are looking for: You have shipped things people used. A side project, a channel with an audience, a tool, a launch. We care more about what you made than where you worked. You write well, and you have a point of view. You can hold attention for 90 seconds on video and 900 words on a page. You are curious about how companies make money. You can read a business case and find the part that actually matters. You can sit with a CFO or a PE operator and not reach for features. You code. Python or TypeScript, comfortably. You use Claude Code, Cursor, or equivalent every day and you have opinions about them. You have built something agentic that does actual work. You are interested in AI for real. You read the papers, or the people who read the papers, and you have changed your mind about something in the last six months. You are anywhere from your first job to your tenth year. Three levels, one bar: what have you made. If you are early, show us an internship where the bar was high and a portfolio with range. If you are senior, tell us what you built with your own hands in the last 90 days. You are in New York or San Francisco, or you will be. What we offer: Base salary of $80,000 to $180,000 depending on level and location, plus a performance bonus. Direct access to the people building the systems and the executives selling them. Small team, no layers between you and the work. A budget for tools, models, and experiments, with no approval chain under a threshold. Promotion tied to output, not tenure. 401(k) profit sharing plan after probation period Unlimited PTO policy Medical, Visual and Dental insurance How to apply: No cover letter. Send three links: something you wrote, something you built, and something you posted that got a reaction. One paragraph on why the third one worked. Then, two sentences on a company whose positioning you think is wrong and what you would change. Base salary depends on level and location, plus a performance bonus.

Задачи: — Документировать и наполнять базы знаний (Jira/Confluence) — Разработка и актуализация HLD/LLD — Решать типовые задачи, обрабатывать инциденты совместно с архитекторами/экспертами — Осуществлять подготовку deplоyment-приложений для установки их в кластер — Автоматизировать рутинные процессы — Поддерживать пользователей и помогать им в выполнении шаблонных задач — Разработка автоматизации и средств мониторинга на Python Обязательные навыки: — Опыт в роли от 3 лет — Установка и администрирование ОС Linux/Ubuntu — Создание и поддержка кластеров K8s, Kafka, Greenplum, Cassandra — Понимание принципов работы DevOps, процессовCI\CD — Опыт работы с системой управления конфигурацией (Ansible) — Опыт работы с оркестраторами — Опыт настройки мониторинга и алертинга — Автоматизация на Python, bash — Навыки работы с Docker — Умение работать c git — Опыт написания веб сервисов (api) на python — Написание скриптов по автоматизации на python — Опыт работы с реляционными БД (Oracle, ClickHouse, PostgreSql) на уровне администратора

AI Research Lab 42 разрабатывает автономного AI Scientist — систему, способную самостоятельно формулировать гипотезы, проводить эксперименты и находить решения. Первый фокус лаборатории — финансовые рынки: AI-система работает как автономный трейдер, а полученный капитал финансирует дальнейшие исследования. Параллельно лаборатория ведёт исследования в области биологии человека, нейротехнологий и фундаментальной физики. В trading research открыто 3 позиции: TradFi Research Lead Задача — построить и возглавить research-направление в traditional markets: разрабатывать MFT-стратегии, строить портфели и risk/execution models, выводить стратегии в production. Требования: 5+ лет в systematic quant research, подтверждённый track record прибыльных MFT-стратегий, опыт с equities / futures / options / FX, опыт лидерства обязателен. AI Researcher — Autonomous Research Задача — перейти от ручного quant research к автономной agent-driven системе, которая сама генерирует гипотезы, тестирует и оптимизирует стратегии. Требования: MFT/HFT researcher с сильным пониманием market microstructure, статистики и Python/ML, способный формализовать research-процесс для автоматизации. Quantitative Researcher — Crypto MFT Задача — полный цикл разработки medium-frequency crypto strategies: от поиска alpha и backtesting до production и мониторинга live performance. Требования: 2+ лет в systematic trading, опыт запуска стратегий в live, глубокое понимание crypto market structure (spot, perps, funding), сильные Python, statistics и ML/DL. Условия: — Работа удалённо по B2B контракту — Через полгода релокация в Амстердам по high skilled migrant visa — Оформление в голландскую компанию с 30% налоговым рулингом

Требования: — Опыт работы DevOps от 7 лет — Установка и администрирование ОС Linux/Ubuntu/Talos — Обновление прошивок сетевых карт, настройка бондинга — Создание и поддержка кластеров Kubernetes, Kafka, Greenplum, Cassandra, Hadoop, Apache Ozone — Понимание принципов работы DevOps, процессов CI/CD — Опыт работы с системой управления конфигурацией Ansible — Опыт работы с оркестраторами — Автоматизация на Python, bash — Навыки работы с Docker — Умение работать с git — Опыт написания веб сервисов (api) на Python — Написание скриптов по автоматизации на Python — Опыт работы с реляционными базами данных на уровне администратора