Вакансии

Задачи: — Автоматизировать тестирование бэкенда на Python; — Писать API-тесты, контрактные тесты; — Проверять консистентность данных при загрузке; — Тестировать A/B эксперименты; — Работать с большими объёмами данных в ClickHouse, PostgreSQL, Kafka; — Тестировать ML-составляющую продукта в общем флоу; — Проверять бизнес-логику на уровне юнит-экономики. Требования: — Коммерческий опыт автоматизации на Python от 3 лет; — Тестирование чистого бэкенда от 80% задач на последнем месте; — Уверенная работа с PostgreSQL, ClickHouse, MongoDB; — Опыт с Kafka; — Понимание CI/CD, опыт с GitLab; — Базовые знания Kubernetes; — Опыт с Grafana, Kibana или аналогами; — Самостоятельность в принятии решений при неполной информации; — Готовность работать в условиях высокой ответственности.

Обязанности: • Проведение учебной практики и учебных занятий для групп 1,2,3,4 курса специальности «Сетевое и системное администрирование» • Технология выполнения работ по профессии рабочего "Оператор электронно-вычислительных и вычислительных машин" • «Технология выполнения работ по профессии рабочего-"Наладчик технологического оборудования"» • «Основы вычислительной техники» • «Основы безопасности на производстве» Требования: • Образование, знания, умения - в соответствии с Профстандартом • Владение навыками работы в специализированных программах, а также: Microsoft Excel, Microsoft Outlook, Microsoft PowerPoint, Microsoft Word, Интернет, электронная почта. • История ОС, архитектура. Диспетчеризация, планирование и взаимодействие процессов ОС, работы с памятью, файловые системы, принципы организации. Установка, настройка и работы в Windows, Linux, Astra Linux. Администрирование ОС и управление безопасностью • Сертификаты Cisco/Huawei либо иных сетевых вендоров. Плюсом будут сертификаты Microsoft и Python, Astra Linux (или иных Linux дистрибутивов) • Знание модели OSI/ Принцип работы протоколов TCP и UDP • Знание сетевых протоколов. FTP, SMTP, POP, IMAP, DHCP, IPv6 адресации. Протоколы удалённого доступа (SSH, Telnet). Принцип работы сети на физическом уровне. Принцип работы технологий IEEE 802.11 (WiFi) Понимание принципа роботы локальных сетей, Ip адресация, SLAAC + DHCPv6. Технологии WPAN, WLAN, WMAN, WWAN. Технологии беспроводной связи BLE, BR/EDR, WiMAX • Медицинская книжка, медицинское освидетельствование психиатр/нарколог, справка об отсутствии судимости Условия: • Работа на территории работодателя • Полный социальный пакет • Отпуск в летнее время

Location: Tallinn, Estonia Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (Applied AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: A Unique Opportunity for a career in a global, fast-growing company. Attractive remuneration package based on qualifications and experience. Opportunities to learn and grow through our “ Employee Training & Development program”. Stebby Sports Compensation or Confido Health Compensation. Multiple events to bond with the team and the group. Birthday and Loyalty benefits . What to expect from our recruitment process: Interview with HR Assessment task Interview with hiring managers Final interview with top management Make your next Career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Limassol, Cyprus Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: A Unique Opportunity for a career in a global, fast-growing company. Attractive remuneration package based on qualifications and experience (including 13th salary and Discretionary Bonuses to reward exceptional performance). Opportunities to learn and grow through our “ Employee Training & Development program”. Medical Insurance Cover , which includes Outpatient, Inpatient, and Dental Care. Multiple events to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company. Participation in our welfare investment and savings plan through our Provident Fund Scheme. Birthday and Loyalty benefits . Collaboration with SportBenefit. What to expect from our recruitment process: First interview with hiring managers or an HR call Task Assessment Technical Interview or home assignment Final interview with top management Make your next Career step and apply NOW! * Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

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.

Location: Munich, Germany; Berlin, Germany What client look for: You apply statistical, machine learning, and Generative AI techniques to solve business problems and generate actionable insights. You analyse and synthesise complex datasets, incorporating unstructured data and GenAI outputs into clear visualisations and narratives. You collaborate with cross-functional teams and clients to design data-driven and GenAI-enabled solutions. You build, test, and deploy models, including prompt-based and LLM-powered applications. You translate analytical and Generative AI outputs into actionable recommendations for stakeholders. You guide less experienced team members and contribute to best practices in analytics and AI. Requirements What the client requires: You hold a Bachelor’s or Master’s degree in a quantitative field such as Data Science, Computer Science, Mathematics, or Engineering. You have 2–6 years of experience in data science, machine learning, or advanced analytics, including exposure to Generative AI. You have strong programming skills in Python and are familiar with ML and LLM frameworks such as Scikit-learn, LangChain, or Hugging Face. You have a solid understanding of machine learning techniques and Generative AI use cases. You are able to work in client-facing environments and communicate complex topics clearly. You are fluent in English; additional local language skills are a plus. 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.

Location: Munich, Germany; Berlin, Germany What Client look for: You help clients unlock the full potential of their data strategy, by combining strategic thinking, hands-on implementation, and close collaboration with clients and internal teams. You advise leading companies on the organizational and technical optimization of data management. You support change management and data strategy initiatives to ensure sustainable success. You design and implement data strategies, architectures, and scalable data processes. You work closely with clients to co-create pragmatic and impactful solutions that drive digital transformation. You develop innovative data products that create real business value. You conduct data analyses and visualizations to uncover insights and identify improvement opportunities. You facilitate workshops, perform process assessments, and deliver tailored training sessions. You contribute to developing best practices, innovative solutions, and continuously challenge the status quo. Requirements What the client requires: You hold a completed university degree with excellent academic performance in Computer Science, Data Science, Information Systems, or a related field. You have gained first professional experience in data management, analytics, or digital transformation consulting. You possess strong knowledge of SQL and Python as well as hands-on experience with cloud platforms such as AWS, GCP, or Azure. You are familiar with visualization tools such as Power BI, Tableau, or Looker, as well as modern data platforms. You demonstrate excellent communication and presentation skills and are able to convey complex topics in a clear and practical manner. You bring a proactive, service-oriented mindset and stand out through a high level of ownership and commitment. You feel comfortable working in a collaborative and agile environment where you can fully develop your potential. You are fluent in English; additional local language skills are a plus. 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 - client concern: 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, and 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.

Location: Yerevan, Armenia Description We are seeking an experienced Senior Business Data Analyst to lead analytical initiatives within our Partner Performance Analytics Team. This role plays a critical part in driving partner success through advanced business analysis, strategic recommendations, performance optimization, and cross-functional collaboration. The successful candidate will act as a trusted business partner for senior stakeholders, helping shape strategic decisions through data-driven insights and deep understanding of the iGaming business ecosystem. Responsibilities Lead analysis of partner performance, profitability, retention, and business growth opportunities Own and continuously improve the analytical framework used to evaluate partner success Analyze the effectiveness and ROI of bonus campaigns, promotional mechanics, loyalty initiatives, and retention activities Identify business risks, performance bottlenecks, and emerging trends across partner portfolios Deliver strategic recommendations that improve partner engagement, player value, retention, and profitability Design and develop advanced dashboards, KPI frameworks, and performance monitoring systems Conduct deep-dive investigations into business issues and provide root-cause analysis Support senior management with decision-making through analytical insights and business cases Mentor junior analysts and contribute to the development of analytical standards within the team Requirements 4+ years of experience in Business Analytics, Commercial Analytics, Business Intelligence, Performance Analytics, or related fields Strong experience within iGaming, Sportsbook, Online Casino, or Retention Analytics environments Advanced SQL expertise Advanced proficiency in Power BI Strong experience with KPI design, performance measurement, forecasting, and business performance management Proven ability to transform analytical findings into strategic business recommendations Experience working directly with senior stakeholders and decision-makers Strong understanding of business drivers, profitability metrics, and customer lifecycle analytics Upper-Intermediate or higher English level Deep understanding of iGaming KPIs including GGR, NGR, Bonus Cost, Retention, Churn, ARPU, ARPPU, LTV, CPA, ROI, and Player Segmentation Experience with predictive analytics, forecasting, and statistical modeling Knowledge of Python is a plus Experience leading analytical initiatives or mentoring analysts Excellent communication and presentation skills Ability to explain complex analytical findings to non-technical audiences Ability to challenge assumptions and drive data-driven decision-making Strong business partnering mindset

Задачи: — Анализировать и повышать эффективность закупки рекламного трафика из in-app, social и web-источников: оценивать источники, каналы, кампании, аудитории и связки по ключевым закупочным метрикам, определяя зоны для масштабирования и оптимизации. — Проводить когортный и сегментный анализ, ad hoc-анализ закупки трафика. — Системно находить точки роста, формулировать, приоритизировать и тестировать growth-гипотезы на основе данных: от оптимизации закупки трафика, креативов и рекламных платформ до улучшения монетизации, удержания и окупаемости пользователей. — Анализировать и улучшать эффективность алгоритмов автоматизации закупки трафика: оценивать качество решений, искать причины просадок, формулировать требования к доработкам и адаптировать логику под новые источники, рекламные платформы и бизнес-цели. — Проводить предиктивную и инициативную аналитику, помогая заранее выявлять риски, просадки эффективности и новые возможности для роста. — Строить и поддерживать аналитические и функциональные dashboards. — Проверять точность ключевых отчетов, данных, трекинга и аналитических систем; работать с данными из рекламных платформ, BI, CRM, MMP, attribution tools и внутренних баз. — Координировать аналитические задачи в рамках своего направления: взаимодействовать с analytics team, следить за качеством аналитики и помогать переводить результаты анализа в бизнес-рекомендации. — Анализировать и улучшать продуктовые метрики собственных приложений, находя точки роста в удержании, монетизации, пользовательском поведении и общей эффективности продукта. Требования: — Опыт работы в data analytics от 7 лет. — Опыт в mobile app analytics и рекламной медиации для приложений с рекламной монетизацией: понимание работы mediation-платформ, ad networks, waterfall / bidding-логики, eCPM, fill rate, ARPDAU, impressions, ad revenue и влияния рекламной монетизации на продуктовые метрики. — 4+ года опыта с digital marketing, performance marketing, paid acquisition или growth marketing. — Глубокая экспертиза в ключевых закупочных и продуктовых метриках и их практическом применении: LTV, ROAS, ROI, CPA, CPC, CPM, CPI, CTR, CR, retention, ARPU и др. — Опыт проведения когортного анализа, ad hoc-анализа, оценки экспериментов и проверки гипотез. — Умение находить неочевидные инсайты в данных и превращать их в конкретные бизнес-рекомендации. — Опыт работы с MMP, attribution и tracking tools: Adjust, Voluum, Amplituda, MixPanel, Firebase или аналогичными платформами. — Опыт работы с SQL для проведения ad hoc-анализа, извлечения данных и моделирования. — Знание Python или R для аналитики, автоматизации и моделирования. — Понимание принципов маркетинговой атрибуции, tracking, conversion measurement и качества данных. — Навыки работы и построения отчетностей, dashboards в BI-инструментах (Looker). — Опыт работы с BigQuery и другими инструментами современного data stack: GitLab, Docker, Google Cloud (Container Registry, Workflows, Cloud Run). — Опыт работы с большими объемами данных и способность самостоятельно выстраивать аналитическую логику. — Сильные аналитические способности и системное мышление. — Внимание к деталям, высокий уровень самоорганизации и ответственность за результат. — Умение понятно доносить технические выводы до нетехнических команд. — Высшее образование в области математики, прикладной математики, статистики, data science, информационных технологий или смежных дисциплин. Условия: — Удаленный формат взаимодействия. — График: с 10:00 до 19:00 по времени Кипра. — 20 дней отпуска и оплачиваемые больничные. — Зарплата - по договоренности, в зависимости от Вашего уровня и опыта. — Работаем по праздничному календарю Кипра. — Испытательный срок - 3 месяца.

Location: Remote - Spain Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Machine Learning Engineer. About the job This position is to design and engineer AI powered features that makes every customer conversation smarter. As a Machine Learning Engineer on the Conversation Intelligence team, you'll develop and deploy solutions that extract meaning from voice and messaging data at Twilio scale. You'll work alongside experienced ML practitioners to ship real features - from model pipelines to production inference - that directly shape how businesses understand their customers. Responsibilities In this role, you’ll: Design and development of machine learning solutions, ensuring accuracy, performance, security, and scalability. Implement and maintain end-to-end AI/ML pipelines - from data ingestion and feature engineering through to model development, validation, and deployment with guidance from senior engineers on complex architectural decisions Instrument AI/ML services with appropriate metrics, logging, and telemetry to monitor model performance and operational health against defined SLOs Participate in on-call rotations, executing progressive rollouts and applying standard mitigation strategies to keep production inference services healthy Collaborate across planning, design, and code review phases contributing to product and technical discussions, while helping raise overall code quality through thoughtful review feedback Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! *Required: Bachelor's degree in Computer Science, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience 2+ years of experience in machine learning engineering or applied ML, with demonstrated proficiency in Python and at least one ML framework (PyTorch, TensorFlow, or JAX) and familiarity with NLP libraries such as Hugging Face Transformers, NLTK, or SpaCy. Experience developing, testing, and deploying small-to-medium scoped ML services or features in a collaborative engineering environment, including model versioning, experiment tracking, and cloud-based infrastructure (AWS, GCP, or Azure) Proficiency in Python (preferred) or similar OO language. Experience utilizing Large (or Small) Language Models within software systems. Excellent written and verbal communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences. Desired: Hands-on experience with conversational AI, or LLM fine-tuning and prompt engineering in a production  context Exposure to agentic AI frameworks such as LangGraph, AutoGen, CrewAI Familiarity with MLOps/LLMOps tooling related to maintaining models in production such as testing, versioning, model registry, retraining, and monitoring. Location This role will be remote from Ireland. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Обязанности: • Проведение уроков для учеников 4-11 классов • Обучение программированию и технологиям: изучение алгоритмов, основ кодирования (Python, C++), работы с базами данных, сетями и офисными программами • Подготовка к аттестациям: организация учебного процесса для сдачи ОГЭ и ЕГЭ по информатике и ИКТ • Организационно-методическая работа: разработка программ; ведение отчётности (заполнение электронного классного журнала, составление отчётности по успеваемости) • Внеурочная деятельность: руководство проектной деятельностью, ведение кружков • Посещение педсоветов, родительских собраний, методических объединений • Обеспечение работоспособности компьютеров, проекторов и интерактивных досок в классах • Совмещение с должностью системного администратора • Администрирование МЭШ, техническое сопровождение ВСОШ, диагностик МЦКО, ФИС ФРДО, базы "Контингент" и т.д. Требования: • Высшее педагогическое образование (или профессиональная переподготовка по специальности). • Практический опыт знания рабочих программ по предмету, рекомендованных для работы в образовательной школе, а также программ профильного обучения; опыт подготовки учащихся к олимпиадам и конкурсам. Владение языком программирования Python или С++. Ответственность; коммуникабельность.

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: Barcelona, Spain; Madrid, Spain; Tenerife, Spain; Bolzano, Italy; Rome, Italy; Budapest, Hungary; Miskolc, Hungary; Petten, Netherlands; Krakow, Poland; Krosno, Poland; Lublin, Poland; Poland; Poznan, Poland; Warsaw, Poland; Bratislava, Slovakia; Bucharest, Romania; Bucuresti, Romania; Ljubljana, Slovenia; Vilnius, Lithuania; Nicosia, Cyprus; Pilsen, Czechia; Podgorica, Montenegro; Praha, Czechia; Banská Bystrica, Slovakia; Sofia, Bulgaria; Zagreb, Croatia Workplace: remote At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently looking for a dedicated Lead AI Aplication Engineer to join one of our clients' teams . If you're looking for an exciting opportunity to grow in an innovative environment, this could be the perfect fit for you. Key Responsibilities: Build & Run the Shared AI Platform Architect and maintain a multi-tenant AI Platform that supports the full ML lifecycle across cloud and on-premises environments. Ensure high availability, low latency, and cost-efficiency for all shared AI resources. Implement LLMOps/MLOps best practices, including automated deployment pipelines for models. 2. Curate the AI Services Catalogue Develop and expose "as-a-service" capabilities: Inference-as-a-Service, Embeddings-as-a-Service, and RAG-as-a-Service. Standardize how squads interact with LLMs, providing unified APIs and abstraction layers to prevent vendor lock-in. 3. Manage AI Data Infrastructure Own the deployment and scaling of Vector Databases (e.g., Pinecone, Milvus, Weaviate) and Feature Stores (e.g., Feast, Tecton, Hopsworks). Optimize data retrieval patterns to support real-time AI applications and agentic workflows. Oversee Model Hosting environments, utilizing Kubernetes (K8s) and GPU orchestration to manage compute resources efficiently. 4. Enable Developer Self-Service Build and maintain a Self-Service Portal or CLI that allows product squads to provision AI environments, models, and data stores independently. Reduce "Time-to-Inference" for new features by providing pre-configured templates and blueprints. Conduct internal workshops and provide documentation to empower squads to use the platform effectively. Must-Have Technical Skills Infrastructure: Deep experience with Kubernetes (K8s), Docker, and Terraform/Pulumi. Hybrid Cloud: Proven experience managing workloads across AWS/Azure/GCP and On-Premises (NVIDIA AI Enterprise, OpenShift). AI/ML Tooling: Hands-on experience with vLLM, TGI (Text Generation Inference), or NVIDIA Triton for model serving. Databases: Expertise in Vector DBs and traditional SQL/NoSQL databases. Languages: High proficiency in Python and Go or Rust for platform tooling. Experience 8+ years in Platform Engineering, DevOps, or Site Reliability Engineering (SRE). 2+ years specifically focused on building AI/ML infrastructure or platforms. Experience building Internal Developer Platforms (IDP) is a massive plus.

Обязанности: • проведение углубленного анализа данных розничного кредитования • разработка, совершенствование и поддержка дашбордов и регулярной отчетности по ключевым метрикам риска • автоматизация рутинных процессов и аналитических задач • интерпретация результатов анализа для руководства и смежных подразделений, формулирование рекомендаций для управленческих решений Требования: • глубокие практические знания в области управления розничными кредитными рисками. Обязателен успешный опыт работы на всех этапах жизненного цикла кредита: от скоринга заявок до управления проблемной задолженностью и работой с дефолтами. • продвинутое владение SQL (написание и оптимизация сложных запросов, построение и поддержка структур данных для аналитики). • опыт применения Python для анализа данных (Pandas, NumPy, SciPy и т.д.). • навыки визуализации данных и презентации аналитических выводов. Способность ясно и структурированно доносить сложную информацию до различной аудитории, включая технических специалистов и топ-менеджмент • навыки работы с генеративными AI-моделями; опыт создания AI-агентов и использования их в работе будет преимущество • опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов • инструментальное владение AI для анализа, генерации и автоматизации Условия: • комфортный современный офис • офисный формат работы • ежегодный пересмотр зарплаты, годовая премия • корпоративный спортзал и зоны отдыха • более 400 образовательных программ СберУниверситета для профессионального и карьерного развития • расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа • бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров • вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: - Разработка ML-моделей на различных типах данных: табличные, графовые, NLP и событийные последовательности для прогнозирования отказов и сбоев в оборудовании; - Решение задач дискретной оптимизации; - Участие в исследовании новых источников данных и развитии feature store (в Apache Doris); - Поддержка полного цикла разработки DS/ML-продуктов - от идеи до продакшена; - Участие в создании и развитии AI-агента на базе LLM - от экспериментов до реального применения. Требования: - Опыт в роли Data Scientist от 1.5 лет; - Опыт end-to-end разработки ML-решений: от постановки задачи и работы с бизнесом до внедрения в production и поддержки моделей; - Отличное знание Python и глубокое понимание классических алгоритмов машинного обучения, опыт работы с NLP, временными рядами, задачами детекции аномалий; - Опыт работы с deep learning, включая RNN-like архитектуры и трансформеры; - Умение работать с БД (SQL), собирать и обрабатывать данные; - Уверенное понимание A/B-тестирования; - Высшее техническое образование.

Задачи: — Поддерживать, развивать и мониторить существующие Kubernetes-кластера; — Поддерживать, мониторить, выявлять узкие места СУБД/Key-value хранилищ (PostgreSQL, Redis, Clickhouse); — Поддерживать бесперебойную работу систем очередей на базе (Kafka, RabbitMQ); — Поддерживать и развивать систему мониторинга/алертинга на базе Prometheus, Thanos, Alertmanager, Grafana; — Внедрять AI в системы мониторинга; — Участвовать в устранении и расследовании инцидентов инфраструктуры; — Улучшать и развивать существующий CI/CD процесс на базе GitOps (ArgoCD, Gitlab, Jira); — Автоматизировать развертывание приложений (используется Helm + ArgoCD); — Самостоятельно искать новые возможности для улучшения инфраструктуры и внедрения новых DevOps практик; — Консультировать и поддерживать команды разработки и тестирования. Требования: — Понимание целей внедрения DevOps; — Понимание особенностей эксплуатации Python приложений; — Опыт разработки CI/CD пайплайнов с использованием GitLab; — Опыт работы с Docker/Kubernetes и понимание устройства Kubernetes; — Понимание основ сетевых технологий (семейство TCP/IP); — Опыт администрирования linux-инфраструктуры; — Умение работать самостоятельно, брать на себя ответственность, инициативность. Будет плюсом: — Опыт работы с методологией GitOps; — Знание английского языка; — Большой плюс — знание языков программирования Python, Golang. Условия: — Обязательная релокация в Куала-Лумпур (Малайзия) после успешного прохождения испытательного срока (3 месяца).

Задачи: - Проектировать и согласовывать архитектуру AI-агента, приложений и интеграций. - Развивать и разрабатывать backend-компоненты AI-агента, общие библиотеки и интеграционные взаимодействия. - Реализовывать решения на базе LLM, ReAct и RAG, включая поиск и подбор релевантных «шагов» из существующей библиотеки. - Интегрировать систему с внутренними сервисами, репозиториями, базами знаний и корпоративной инфраструктурой. - Формировать требования для построения CI/CD, мониторинга, логирования, трассировки и контроля качества для AI-агента. - Проводить ревью кода, поддерживать код-стандарт и участвовать в командных коммуникациях. - Взаимодействовать с специалистами по автоматизированному тестированию, QA-инженерами и разработчиками для уточнения требований и сценариев использования. - Участвовать в разработке пользовательской поверхности решения, в формате IDE plugin. Требования: - Опыт работы от 3-4 лет в разработке. - Высшее образование. - Практический опыт построения RAG-систем и работы с векторными хранилищами, желательно PostgreSQL + pgvector. - Опыт работы с LangChain, Python. - Опыт разработки ReAct агентов. - Понимание принципов ООП, SOLID и паттернов проектирования. - Понимание базовых принципов многопоточного и асинхронного программирования, включая GIL и asyncio. - Практические знания и навыки работы с LLM. - Опыт работы с инструментами контейнеризации приложений, включая Docker. - Лидерские качества: умение принимать решения и брать на себя ответственность. Условия: - Возможность участия в интересных проектах. - Возможность профессионального и карьерного роста в компании. - Опыт работы в команде профессионалов. - Специальные тарифы для сотрудников в спортивные клубы и языковые курсы и пр. - Удаленный и гибридные форматы работы.