Вакансии

Location: Athens, Greece 🔎 Have you already built AI systems that other people use, and do you want to own them end to end, from the first measurement to production? Do you want to apply your machine learning experience to security-relevant AI? 💡 CENSUS Junior AI Engineer is your opportunity to join our AI team and own features in our production AI systems and products. You will build, evaluate, and ship LLM-powered features on security data, and help guide the interns on the team as you grow. Why Join? 🔹 Real Ownership: Own features in production AI systems end to end, from data and a first measurement through evaluation, deployment and iteration. 🔹 Elite Team: Work alongside world-class AI and cybersecurity experts. 🔹 Hands-on AI: High-impact work across LLM features, RAG and agent systems, evaluations, datasets, and fine-tuning . 🔹 Mentorship: A named AI-team mentor for your first months, and code review on every pull request. 🔹 Remote Work Model: Fully remote in Europe . 🔹 Growth: A clear path to AI Engineer as you take on larger, less defined work. What You’ll Do 🔹 Design, build and ship LLM-based features , together with the evaluations that prove they work. 🔹 Own work on retrieval (RAG), agent and tool-routing systems that answer questions over real security data. 🔹 Build datasets and fine-tune open models on security data, and measure the result against a baseline. 🔹 Scope your own tickets with your mentor and back every change with before-and-after results. 🔹 Review your teammates’ pull requests and help guide our interns. Who We’re Looking For 🚀 Required Skills: 🔹 At least 1 year of hands-on experience in AI, Machine Learning or Data Science engineering. Internships count, and so does industry or research-lab work. 🔹 A track record of shipping : at least one ML or LLM feature that went into production or into a codebase other people used. 🔹 Strong Python , with readable, tested code that others can review. 🔹 Experience in a team codebase: Git, pull requests , and both giving and receiving code review. 🔹 Practical experience building LLM applications (prompting, RAG or agents) and evaluating them, not only calling an API. 🔹 A solid grasp of machine learning fundamentals , and the ability to design an experiment and read its results honestly. 🔹 Working knowledge of SQL and Docker . 🔹 The ability to work independently on a well-scoped ticket and to say early when you are stuck. 🔹 Good written English (non-English resumes will be rejected) , and the habit of backing claims with evidence. ✨ Bonus Skills (Make Your Application Stand Out!): 🔥 Fine-tuning LLMs ( LoRA, SFT, DPO ) or building evaluation sets. 🔥 GPU training or model-serving experience (e.g. vLLM). 🔥 Vector databases , cloud or Kubernetes experience. 🔥 Published papers or research experience. 🔥 Interest in security or cryptography (we will teach you the domain). The Details 📌 Who Can Apply? 🔹 Open to graduates (Bachelor’s, Master’s or PhD) in Computer Science, AI, Machine Learning, Data Science or related fields, or candidates with equivalent practical experience, with at least 1 year of hands-on experience, internships included . 🔹 Europe-based candidates are prioritised. 📍 Location: Remote in Europe. 📄 Contract: Full-tiume 🎯 Career Path: Grow into an AI Engineer role as you take ownership of larger parts of our AI systems. About CENSUS CENSUS is a globally recognized cybersecurity firm delivering top-tier IT and OT security solutions. We work with Fortune 500 companies, financial institutions, critical infrastructure, and secure communications providers worldwide. Our expertise spans cutting-edge research, scientific analysis, and deep engineering experience, ensuring unmatched security for products, infrastructure, and organizations. 🔗 Learn more about us at CENSUS | Cybersecurity Engineering

Location: Intellias Meet your recruiter Bohdana Rubets bohdana.rubets@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Engineer Senior Bulgaria, Croatia, Poland Remote APPLY NOW REFER A FRIEND Let’s breathe life into great tech ideas! With 3,000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world. What project we have for you Our client is building the standard path for governed data sharing across product services, analytics, and AI/ML. The Data Platform team owns the contracts, control mechanisms, publication paths, catalog metadata, lifecycle rules, lineage, permissions, and runtime building blocks that make reusable data safe and practical at scale. This is a role for someone who wants to shape a platform early, while working on concrete production problems from the start. Our client already has the production systems, Kafka backbone, PostgreSQL databases, analytical consumers, and AI/ML use cases that need a better data foundation. The challenge is to turn that reality into a standard path that engineers actually want to use. Our first milestone is focused: centrally managed publishing tables in service-owned PostgreSQL databases, captured through Debezium CDC into Kafka, and registered in DataHub with ownership, lifecycle, lineage, and impact-analysis metadata. Longer-term, the platform expands toward self-service data products, governed materialisations, durable shared state, and reusable data across the client’s operational and analytical systems. This is not a role where you only maintain an existing reporting pipeline. You will help design and build the platform path that other engineering teams use when they publish and consume shared data. What you will do Design and build platform services, tools, and workflows for contract-driven data publishing and consumption. Build the first production path for platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and catalog registration. Create GitOps-style workflows where contracts, schemas, ownership, lifecycle, compatibility, policy metadata, and runtime desired state are reviewed, validated, and reconciled as code. Build tooling that gives product engineers fast feedback before they publish or change data products. Help define how client models data products, publishing contracts, schema evolution, field stability, deletion semantics, access policy, lineage, and cost attribution. Operate and improve the CDC runtime model, including Kubernetes workloads, source-specific isolation, offsets, schema history, heartbeats, signal channels, lag visibility, replay, resnapshotting, and recovery. Integrate platform metadata into DataHub so engineers can discover data products, understand ownership, trace lineage, and reason about the impact of changes. Work with product, infrastructure, data engineering, analytics, and AI/ML teams to make the standard path easier and safer than bespoke point-to-point integrations. What you need for this Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments. Deep understanding of distributed systems trade-offs: reliability, idempotency, replay, eventual consistency, ownership boundaries, compatibility, and operational failure modes. Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance. Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies. Direct Debezium experience is valuable, but strong fundamentals matter more. Experience building software that other engineers use: CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows. Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership. Ability to turn ambiguous architectural direction into practical increments, make trade-offs explicit, and deliver useful production systems without waiting for perfect certainty. Clear written and spoken communication in English. This role involves aligning multiple engineering teams around standards, contracts, and ownership boundaries. Nice to have: DataHub or other data catalog, lineage, or governance systems. Open table formats such as Apache Iceberg, object-store-backed data lakes, S3, BigQuery, ClickHouse, or analytical storage systems. GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, or reconciliation-based systems. Data contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field-level metadata, or contract testing. Experience supporting analytics, AI/ML, feature-store-style access patterns, or cross-domain product-service integrations. Experience with JVM languages and Python, TypeScript, Go, or Ruby. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Workplace: hybrid Обязанности Руководить командой из 3–4 разработчиков: ставить цели, формировать и приоритизировать бэклог, декомпозировать инициативы, распределять ответственность и контролировать результат Развивать платформенные компоненты и внутренние сервисы вокруг работы с данными: повышать их надёжность, масштабируемость, производительность, наблюдаемость и удобство для пользователей платформы Находить узкие места в текущем дата-ландшафте, инженерных процессах и пользовательских сценариях; превращать наблюдения в понятные инициативы с оценкой эффекта и планом реализации Самостоятельно разрабатывать и проводить сложные технические прототипы (PoC) для проверки архитектурных решений, новых технологий и подходов к оптимизации Принимать ключевые архитектурные решения, проводить технические ревью, задавать инженерные стандарты и обеспечивать качество реализации Планировать и вести технические инициативы от идеи до промышленного внедрения: цели, метрики успеха, риски, зависимости, этапы и результат Развивать инженеров в команде: менторить, давать регулярную обратную связь, повышать самостоятельность и качество технических решений Выстраивать рабочее взаимодействие со смежными командами — инфраструктурой, аналитикой, ML/AI, инфраструктурой, безопасностью и продуктовыми командами Улучшать процессы разработки: CI/CD, тестирование, документацию, эксплуатационные практики, мониторинг, управление инцидентами и техническим долгом. Условия работы Официальное оформление с белой ЗП Полугодовые премии по результатам работы Возможность работать удалённо или в гибридном формате Удобный офис рядом с м. «Добрынинская» / удобный офис с бесплатной парковкой на м. «Волгоградский проспект» / МЦД «Калитники» Гибкий график работы Широкий пакет ДМС (включая выезд за рубеж и стоматологию), страхование жизни и здоровья Возможность учиться и развиваться за счёт компании: внешние тренинги и семинары по профессиональным тематикам, участие в крупнейших конференциях страны, программы развития цифровых и управленческих навыков (Цифровая академия, Школа Тимлидов), онлайн и офлайн мастер-классы, корпоративный университет «X5 Полка», школа наставников и многое другое Программы мотивации для спикеров и авторов: внутренняя школа Speak Up School, Write Up, ачивки и баллы за выступления, подготовка спикеров к крупнейшим конференциям страны, сообщество авторов на Хабре, возможность шерить опыт с комьюнити внутренних и внешних экспертов Обмен опытом через cообщества: 12 технических комьюнити от java до devops Яркая корпоративная жизнь с большим количеством мероприятий, конкурсов и возможностей для творческой реализации: регулярные внутренние митапы, демо-дни, открытые микрофоны, день IT-специалиста, программы волонтерства, корпоративное предпринимательство X5 Idea Challenge Забота о благополучии сотрудников: 7 спортивных сообществ (бег, футбол, волейбол, баскетбол, хоккей, лыжи, триатлон), ежегодная Неделя здоровья Скидки в экосистеме бизнесов Х5 («Пятёрочка», «Перекрёсток», «Много лосося», «Перекресток Впрок») Программа привилегий Prime-zone (скидки на товары и услуги и специальные предложения от компаний-партнёров) Материальная помощь сотрудникам, попавшим в сложную жизненную ситуацию. Профессиональные навыки Опыт с data stack: Spark, Flink, Kafka, Trino, ClickHouse, Iceberg, Airflow, Kubernetes, Object storage, catalog/governance-системы Опыт разработки и эксплуатации сложных распределённых систем и/или платформ данных Опыт управления инженерной командой либо выраженный опыт технического лидерства с готовностью отвечать за развитие людей и поставку результата Умение совмещать управление и hands-on работу: не только делегировать, но и лично погружаться в архитектурно сложные или исследовательские задачи, прототипировать или брать самые сложные задачи на себя Опыт проектирования и внедрения платформенных компонентов, внутренних сервисов или инфраструктурных продуктов Практический опыт оптимизации производительности, стоимости, надёжности или DX в инженерных системах Умение работать через цели и измеримый эффект: связывать технические инициативы с ценностью для пользователей и организации Навыки декомпозиции, приоритизации и делегирования; умение удерживать баланс между быстрыми улучшениями, развитием платформы и устранением технического долга Умение ясно доносить технические решения до инженеров и руководителей Опыт развития Internal Developer Platform, self-service-подходов или платформы как продукта Опыт миграций, стандартизации дата-ландшафта, построения observability и управления стоимостью обработки данных Опыт формирования технической стратегии и roadmap платформы; это обычно включает архитектурную целостность и взаимодействие со смежными технологическими направлениями.

Location: London Workplace: remote ⚡️ About Merkle Science Merkle Science provides blockchain transaction monitoring and intelligence solutions for web3 companies, digital asset service providers, financial institutions, law enforcement and government agencies to detect, investigate and prevent illicit use of cryptocurrencies. Our vision is to make cryptocurrencies safe and provide infrastructure for the safe and compliant growth of cryptocurrencies. Merkle Science is headquartered in New York with offices in Singapore, Bangalore and London. The team has combined experience across Bank of America, Paypal, Luno, Thomson Reuters and Amazon. The company has raised over US$27 MM from SIG, Beco, Republic, DCG, Kenetic, GGV and several others. The Role You will design, build and run the systems behind our data products, covering ingestion, processing, analytical storage and serving. You own your work from the design document through to production. The people who design a pipeline also run it and answer for its numbers. Our stack is very wide, and we go deep in every part of it. We don't stop at "it works." We keep measuring, profiling and tuning to make systems faster, cheaper and more reliable. We want engineers who are razor sharp, pay close attention to detail, and care as much about why a query takes 800 ms as whether it returns the right answer. You don't need blockchain experience. If you're a strong data engineer who wants to learn it, we'd like to hear from you. What You'll Do Design and build scalable, high-throughput data pipelines and platform systems for blockchain data across 30+ chains. Build backend data services and loaders in Go and Python. Design and evolve data models and analytical workloads in ClickHouse, and tune them for sub-second queries. Build incremental, idempotent pipelines on Databricks over billions of rows and tens of terabytes. Keep improving the scale, reliability, freshness, performance and cost efficiency of the platform. Investigate hard performance and reliability problems and see them through to resolution. Work closely with the product, analytics and investigations teams that use the data, and turn their needs into platform designs. Help set technical direction through architecture discussions, design reviews and code reviews. Mentor engineers and help set strong engineering and operational practices. What You Bring 5+ years building and operating production data systems, including ETL and ELT pipelines. At least two of those years should be spent owning systems that other engineers depend on. Expert Python and strong SQL. You write typed, tested code, are comfortable with asyncio and concurrency, and have built incremental data models over billions of rows. Go for backend services. You have built and run high-throughput services or data loaders in Go in production. ClickHouse in production. You know MergeTree schema and sort-key design, materialised views, bulk loads and query tuning. Databricks in production. You have worked with PySpark, Delta Lake and Unity Catalog, designed incremental and idempotent tables, and kept an eye on compute cost. Large-scale data. You have hands-on experience with pipelines over billions of rows and tens of terabytes. You understand how partitioning, clustering and file sizing affect cost and latency. Kafka, Airflow and Kubernetes in production. You understand delivery semantics and idempotent writes, have handled backfills and failures, and have run data workloads with Docker and Helm. Google Cloud is preferred; AWS is fine. An operations and communication mindset. You instrument what you build, write runbooks and post-incident reviews, and can write a design document that a reviewer in another time zone can approve.   Nice to Have Blockchain data: EVM, UTXO or non-EVM chain data models, and pulling data from nodes over JSON-RPC or gRPC. Graph or distributed key-value stores: entity resolution or clustering on large graphs. Infrastructure as code, GitOps and observability: Terraform, Helm, ArgoCD, OpenTelemetry, Prometheus and Grafana, and load-test design. Experience building platforms that serve multiple data sources, datasets or product teams. AI-assisted development, and experience in fintech, compliance or AML. How We Work You'll join a small, senior team where everyone owns their work end to end. We make decisions based on measured evidence, not opinion. We keep design notes and runbooks next to the code. We test at production scale and run blameless post-incident reviews. We use AI coding tools every day, and we use judgement when reviewing what they produce. ❤️ Well Being, Compensation and Benefits We care about your well-being. Along with excellent health insurance, we offer flexible time off, learning & development initiatives and hours that are designed to provide work/life balance.  We regularly host team-building sessions and encourage discussions around mental health.   We reward talent and believe in acknowledging people for their contributions.  We offer industry-leading compensation, along with generous equity.  As a rapidly growing business, there are endless opportunities to grow your career with Merkle Science.

Location: New York Workplace: remote ⚡️ About Merkle Science Merkle Science provides blockchain transaction monitoring and intelligence solutions for web3 companies, digital asset service providers, financial institutions, law enforcement and government agencies to detect, investigate and prevent illicit use of cryptocurrencies. Our vision is to make cryptocurrencies safe and provide infrastructure for the safe and compliant growth of cryptocurrencies. Merkle Science is headquartered in New York with offices in Singapore, Bangalore and London. The team has combined experience across Bank of America, Paypal, Luno, Thomson Reuters and Amazon. The company has raised over US$27 MM from SIG, Beco, Republic, DCG, Kenetic, GGV and several others. The Role You will design, build and run the systems behind our data products, covering ingestion, processing, analytical storage and serving. You own your work from the design document through to production. The people who design a pipeline also run it and answer for its numbers. Our stack is very wide, and we go deep in every part of it. We don't stop at "it works." We keep measuring, profiling and tuning to make systems faster, cheaper and more reliable. We want engineers who are razor sharp, pay close attention to detail, and care as much about why a query takes 800 ms as whether it returns the right answer. You don't need blockchain experience. If you're a strong data engineer who wants to learn it, we'd like to hear from you. What You'll Do Design and build scalable, high-throughput data pipelines and platform systems for blockchain data across 30+ chains. Build backend data services and loaders in Go and Python. Design and evolve data models and analytical workloads in ClickHouse, and tune them for sub-second queries. Build incremental, idempotent pipelines on Databricks over billions of rows and tens of terabytes. Keep improving the scale, reliability, freshness, performance and cost efficiency of the platform. Investigate hard performance and reliability problems and see them through to resolution. Work closely with the product, analytics and investigations teams that use the data, and turn their needs into platform designs. Help set technical direction through architecture discussions, design reviews and code reviews. Mentor engineers and help set strong engineering and operational practices. What You Bring 5+ years building and operating production data systems, including ETL and ELT pipelines. At least two of those years should be spent owning systems that other engineers depend on. Expert Python and strong SQL. You write typed, tested code, are comfortable with asyncio and concurrency, and have built incremental data models over billions of rows. Go for backend services. You have built and run high-throughput services or data loaders in Go in production. ClickHouse in production. You know MergeTree schema and sort-key design, materialised views, bulk loads and query tuning. Databricks in production. You have worked with PySpark, Delta Lake and Unity Catalog, designed incremental and idempotent tables, and kept an eye on compute cost. Large-scale data. You have hands-on experience with pipelines over billions of rows and tens of terabytes. You understand how partitioning, clustering and file sizing affect cost and latency. Kafka, Airflow and Kubernetes in production. You understand delivery semantics and idempotent writes, have handled backfills and failures, and have run data workloads with Docker and Helm. Google Cloud is preferred; AWS is fine. An operations and communication mindset. You instrument what you build, write runbooks and post-incident reviews, and can write a design document that a reviewer in another time zone can approve.   Nice to Have Blockchain data: EVM, UTXO or non-EVM chain data models, and pulling data from nodes over JSON-RPC or gRPC. Graph or distributed key-value stores: entity resolution or clustering on large graphs. Infrastructure as code, GitOps and observability: Terraform, Helm, ArgoCD, OpenTelemetry, Prometheus and Grafana, and load-test design. Experience building platforms that serve multiple data sources, datasets or product teams. AI-assisted development, and experience in fintech, compliance or AML. How We Work You'll join a small, senior team where everyone owns their work end to end. We make decisions based on measured evidence, not opinion. We keep design notes and runbooks next to the code. We test at production scale and run blameless post-incident reviews. We use AI coding tools every day, and we use judgement when reviewing what they produce. ❤️ Well Being, Compensation and Benefits We care about your well-being. Along with excellent health insurance, we offer flexible time off, learning & development initiatives and hours that are designed to provide work/life balance.  We regularly host team-building sessions and encourage discussions around mental health.   We reward talent and believe in acknowledging people for their contributions.  We offer industry-leading compensation, along with generous equity.  As a rapidly growing business, there are endless opportunities to grow your career with Merkle Science.

Location: Sydney Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. As an Infrastructure Support Engineer (AWS), you will play a key role in designing, maintaining, and securing cloud infrastructure to support critical business operations. The team works closely with development teams, DevOps, and system administrators to ensure seamless cloud functionality. Your future role at QRT: Design and implement custom AWS architectures to enhance the quantitative research and modelling processes of the desk Troubleshooting and resolving complex technical issues related to AWS infrastructure. Collaborate with quantitative researchers, developers, and data scientists to understand their needs and translate them into scalable, flexible, and secure cloud solutions Design and implement custom AWS architectures to enhance the quantitative research and modelling processes of the desk Develop automation scripts using Terraform, CloudFormation, and other tools to improve cloud management and efficiency. Work on continuous monitoring and optimizing performance and cost-effectiveness of cloud infrastructure. Evaluate and recommend new technologies to improve the reliability, scalability, and security of the company's cloud infrastructure Your present skillset: Troubleshooting should be core to your skill set and will be extremely useful to have ability to dive into issues without much context and troubleshoot the way to resolution. 8+ years' experience as a Cloud Architect or Engineer with a strong focus on AWS technologies. In-depth knowledge of AWS services, including EKS, EC2, S3, Lambda, RDS, VPC, IAM, CloudWatch, and others Proficiency with scripting languages (e.g. Python, Bash) Hands-on experience with configuration management tools (e.g. Ansible, Terraform). Experience with containers and orchestration technologies (e.g. Docker, ECS, Kubernetes) Experience with monitoring and performance tuning in cloud environments. Familiarity with agile software development methodologies Experience debugging with software development tools. Experience with working and troubleshooting with Windows and Linux OS administration. The ability to duplicate specific software error or AWS configuration to define the cause. Excellent verbal and written communication skills, and the ability to interpret and answer complex technical questions, provide and ensure user follow-up and contribute to knowledge base content. Maintain patience and composure as you help end users through their issues. AWS certifications (Solutions Architect, DevOps Engineer, etc) are a plus QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Задачи: — Создавать и развивать высоконагруженные микросервисы на Java (Spring Boot) и Go; — Проектировать архитектуру распределенных систем, принимать и защищать технические решения; — Разрабатывать API (REST, gRPC) и настраивать асинхронное взаимодействие через Kafka; — Проектировать схемы баз данных, писать и оптимизировать сложные SQL-запросы в PostgreSQL; — Упаковывать сервисы в Docker, работать с Kubernetes и настраивать CI/CD-пайплайны; — Оптимизировать производительность систем, писать Unit/Integration тесты и проводить код-ревью; — Поддерживать production-системы, решать вопросы производительности и отказоустойчивости. Требования: — Общий опыт коммерческой backend-разработки от 7 лет; — Коммерческий опыт разработки на Java от 7 лет (Java Core: Collections, Multithreading, Concurrency, Stream API, Spring Boot, Hibernate); — Коммерческий опыт разработки на Go от 2–3 лет (goroutines, channels, context, sync, interfaces); — Опыт проектирования микросервисной архитектуры и распределенных высоконагруженных систем (Highload); — Уверенное владение PostgreSQL и навыками оптимизации запросов; — Практический опыт работы с Kafka, REST API и gRPC; — Опыт работы с Docker, Kubernetes и CI/CD. Будет плюсом: — Опыт технического лидерства (Tech Lead / Team Lead); — Опыт работы с Event-Driven Architecture, распределенными транзакциями и Eventual Consistency; — Знание Redis, RabbitMQ; — Навыки профилирования Go-приложений (pprof); — Опыт работы с мониторингом и трейсингом (Prometheus, Grafana, Jaeger); — Опыт рефакторинга legacy-систем и опыт работы в финтехе/платежных системах. Условия: удалённая работа.

Location: Malaga Are you an experienced Backend .NET/C# Engineer looking for your next career opportunity? The Gaming Area within Product Development is now hiring! The Gaming Area at Betsson Group focuses on Game Play and Game Discovery across all our brands and markets. We aim to offer the best gaming products in the industry and an exciting user experience when playing on our sites. We cover game lobbies, gaming initiatives, provider integrations and more. What you will be working on Our Gaming platform is the core of everything we do. It supports all our gaming sites and is central to the company strategy. You will be part of preparing our journey to containerization, increasing the scalability of our systems while also maintaining their high quality. To accommodate new requirements, we are constantly re-evaluating our systems design and working on exciting new features. You will be part of a passionate team, which is building an industry leading, scalable, multi-brand platform to support 25+ online brands! Our brands are used by hundreds of thousands of users and growing To sum it up: you will be taking our Gaming platform, which is used by a worldwide audience, to a new level! Your skills and experience Previous experience as a backend developer and relevant experience with some of the core technical skills mentioned below. You are a collaborative person who readily offers help and shares knowledge with your colleagues. C#, .NET Framework, NET Core 8 .NET Core Web API SQL Server and NoSQL databases Messaging services within a microservice architecture GitHub and GitFlow Workflow branching strategy Agile environment experience Confidence in both written and spoken English And/or to have experience working with RabbitMQ/Kafka, Docker containerization and Domain driven design What does our tech stack look like? At Betsson, we pride ourselves on adaptability and keeping up with the latest technologies. Our current tech stack looks like this: Backend: .NET C#, .NET Core, Specflow .NET Core Web API, .NET Web API AWS, Kubernetes, Docker PostgreSQL, MSSQL, Redis, Couchbase Apache Kafka, RabbitMQ GitHub, TeamCity What we offer 25 working days of paid vacation. Private health and life insurance. Flexible compensation package  for transport, meals, and more! Hybrid work policy for the best of office and home. Up to 10 days per year working remotely from abroad. €300 yearly wellness allowance. Office perks to make your day easier. Referral program with a bonus for successful hires. Intensive summer schedule in August for extra flexibility and work-life balance. In addition to all of this, you will be part of the multi-cultural Betsson community enjoying team-building events, our Friday bars, our social clubs, parties and other events. There is always something fun to look forward to! CHALLENGE ACCEPTED? If you are interested to learn more, please apply with your CV in English. Check out the Betsson Group Blog to find out what our employees are talking about By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

Responsibilities: — Build alerting, recovery, telemetry, and incident-management systems for inference fleets. Technologies and practices involved include site reliability engineering, Kubernetes, SLO, PCIe, incident management, Grafana, BMC, Prometheus, Redfish, Infrastructure-as-Code, Go, PagerDuty, Terraform, networking, Rust, firmware, Python, Ansible, error budget, and debugging.

Location: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. Key Responsibilities Cloud Security Architecture and Hardening Design, implement, and continuously strengthen security architectures across public cloud environments, including AWS, Tencent Cloud, Huawei Cloud, and Alibaba Cloud. Areas of focus include container isolation, Identity and Access Management (IAM), VPC network segmentation, and security policies. Security Operations and Incident Response Build and continuously improve cloud security monitoring and operations capabilities, including Security Information and Event Management (SIEM) and Cloud Security Posture Management (CSPM). Detect, investigate, and respond to security incidents, conduct root cause analysis and post-incident reviews, and drive remediation through to closure. Infrastructure Security and Vulnerability Management Assess and harden cloud compute instances, containers, cloud services, and supporting infrastructure. Develop and enhance host and cloud vulnerability scanning capabilities, and track remediation to completion. Identity and Access Management Design and maintain cloud IAM and Cloud Access Management (CAM) permission frameworks. Establish lifecycle management policies for credentials, including access keys and secret keys (AK/SK), API keys, and access tokens. Enforce least-privilege access and conduct periodic access reviews. Compliance and Risk Management Conduct regular security baseline assessments and risk assessments across cloud environments. Produce security compliance reports against industry standards such as CIS Benchmarks, and support internal and external security audits, compliance reviews, and remediation activities. Security Standards and Technical Enablement Develop and maintain cloud security policies, technical standards, and best-practice documentation. Provide security guidance, technical support, and training to engineering and operations teams to strengthen the organization’s overall cloud security capabilities. Qualifications A solid foundation in Linux systems administration, with a strong understanding of networking protocols such as TCP/IP, DNS, and TLS, as well as common network security principles. Familiarity with major public cloud platforms, including AWS, Tencent Cloud, and Alibaba Cloud, with hands-on experience in cloud resource management, security configuration, or operations. An understanding of cloud-native technologies and their security models, with familiarity with Docker, Kubernetes, microservices, serverless architectures, and associated security practices. Familiarity with public cloud IAM/CAM frameworks, with practical experience in permission model design, account governance, key management, or least-privilege implementation. An understanding of common cloud security threats and attack paths, including lateral movement, privilege escalation, server-side request forgery (SSRF), and abuse of the Instance Metadata Service (IMDS). Experience in vulnerability scanning, risk assessment, or security tool integration. Hands-on experience deploying, integrating, and operating Tenable, Orca, or comparable solutions is preferred. Experience managing north–south and east–west traffic, reducing exposed network boundaries, or designing and implementing zero-trust network architectures is preferred. Strong security risk awareness, analytical and problem-solving skills, and effective communication and collaboration abilities, with a demonstrated ability to drive cross-functional security initiatives and remediation efforts to completion. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Задачи: — Разрабатывать в рамках методологии SDD (Specification-Driven Development): проектировать и описывать контракты сервисов (gRPC/Protobuf, OpenAPI) перед написанием кода. — Разрабатывать и развивать микросервисы на Golang для платформы Data Management Platform. — Участвовать в проектировании архитектуры сервисов и интеграции различных компонентов системы. — Совместно с командой улучшать и поддерживать существующие решения, обеспечивая высокие показатели надежности и производительности. — Проводить ревью кода коллег и поддерживать качество разработки. — Взаимодействовать с DE и Frontend-разработчиками, а также бизнес заказчиком для обеспечения согласованности контрактов и корректности бизнес-логики. Требования: — Опыт коммерческой разработки на Golang от 2 лет. — Понимание и опыт работы по методологии SDD: разработка на основе контрактов (contract-first), умение проектировать и описывать спецификации сервисов до начала реализации. — Опыт работы с gRPC и Protobuf, понимание принципов REST API. — Знание SQL и опыт работы с реляционными БД. — Навыки работы с контейнерами и написания Dockerfile, понимание принципов оркестрации в Kubernetes. — Владение Linux, Git, понимание принципов CI/CD. Будет плюсом: — Опыт работы с брокерами сообщений: Kafka, RabbitMQ. — Опыт написания сервисов с нуля и участия в проектировании архитектуры, в том числе сервисов с высокой нагрузкой. — Знание и приверженность DevOps-практикам. — Хорошее понимание и опыт работы со стеком эксплуатации сервисов (Grafana, ELK, Prometheus, Jaeger). — Опыт работы в рекламных технологиях или AdTech-проектах. — Понимание специфики работы с большими объемами данных и профилями пользователей. Условия: — Внутренние семинары, митапы, обучение новому. — ДМС со стоматологией для сотрудников и скидка на покупку ДМС для ближайших членов семьи. — Техника для комфортной работы. — Сессии профессионального развития персонала с планом индивидуального развития каждого сотрудника.

Location: Intellias Meet your recruiter Karolina Sowa karolina.sowa@intellias.com https://www.linkedin.com... Vacancy details Software Engineering Python Engineer Senior Bulgaria, Colombia, Croatia, Poland, Portugal, Spain, Ukraine Remote APPLY NOW REFER A FRIEND We are looking for a Senior Interoperability Engineer to build and scale healthcare integrations for a Digital Health platform connecting providers, payers, clinical systems, and external healthcare networks. This is a hands-on engineering role focused on Python, Kafka, high-scale APIs, healthcare interoperability, and secure data exchange . What project we have for you The platform connects healthcare data from multiple clinical and administrative systems and makes it available through secure, standards-based APIs. The Interoperability domain is responsible for building and operating integrations with external healthcare systems, processing high-volume data exchange, and providing reliable APIs consumed by internal products and partners. The engineering environment is based on Python, event-driven architecture, Kafka, REST/FHIR APIs, OAuth-based security, and cloud-native services . What you will do Design and develop scalable healthcare interoperability services and APIs . Build event-driven integrations using Python and Kafka . Implement and support FHIR-based healthcare data exchange. Develop secure APIs using OAuth 2.0/OIDC and JWT . Integrate external healthcare systems, data providers, and partner APIs. Implement data validation, transformation, mapping, and error-handling logic required for interoperability workflows. Troubleshoot complex integration, authentication, and distributed-system issues. Improve API performance, scalability, reliability, and observability. Build automated tests covering API behavior and integration scenarios. Participate in architecture discussions, code reviews, and engineering standards. What you need for this Requirements: 5+ years of professional backend or integration engineering experience. Strong hands-on experience with Python in production environments. Experience designing and operating high-scale REST APIs and backend services . Strong experience with Kafka or comparable event-streaming technologies. Solid understanding of distributed and event-driven architectures . Strong experience with API authentication and authorization, including OAuth 2.0, OIDC, and JWT . Experience integrating external systems and APIs in complex enterprise environments. Hands-on experience with FHIR or healthcare interoperability APIs . Strong understanding of API reliability, error handling, retries, idempotency, and observability. Experience with SQL and/or NoSQL databases. Experience with Docker, cloud-native environments, and CI/CD. Strong troubleshooting and production problem-solving skills. Nice to Have: Experience with FHIR R4, SMART on FHIR, US Core, or USCDI . Knowledge of HL7 v2 or CDA/C-CDA . Experience integrating EHR/EMR, payer, HIE/HIN, pharmacy, or laboratory systems. Experience with Patient Access APIs, Bulk FHIR, or CMS interoperability requirements . Experience with Kubernetes and AWS. Healthcare or Digital Health domain experience. Experience using AI-assisted engineering tools in day-to-day software development. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Поддержка и развитие процессов безопасной разработки. Проведение аудитов безопасности и ревью продуктовых сервисов и приложений.

Location: Москва Мы развиваем GigaChat и ищем сильного руководителя направления RL Efficiency. Это роль для человека, который возьмёт на себя эффективность всего RL-контура: обучающий цикл, rollout, reward-сигналы, взаимодействие с инференсом и инфраструктура под онлайн-эксперименты. Цель направления — сделать так, чтобы online RL / RLHF / RLVR обучение GigaChat было максимально быстрым, стабильным и дешёвым: сократить time-to-feedback по экспериментам, поднять утилизацию кластера и упростить запуск новых RL-рецептов на масштабе. Обязанности Развивать направление RL Efficiency целиком •  Определять, как должно развиваться направление эффективности RL: какие места критичны на данный момент, как измерять прогресс и что в первую очередь ограничивает скорость экспериментов. •  Вести направление целиком: от постановки гипотез и плана работ до внедрения результатов в регулярный цикл обучения. •  Принимать решения о приоритетах между ускорением rollout, оптимизацией обучающего цикла, инфраструктурой и системой оценки качества. Ускорять цикл online RL •  Оптимизировать пайплайн online RL: генерация rollout'ов, сбор reward-сигналов, обновление весов модели, overlap этапов. •  Выстраивать эффективное взаимодействие между обучающим контуром и инференс-движком (vLLM / SGLang / собственные решения), добиваясь высокой утилизации и низкой задержки. •  Работать с весами и KV-cache: быстрое обновление весов между итерациями, снижение overhead синхронизаций, оптимизация памяти. •  Повышать стабильность больших RL-прогонов: контроль деградаций, автоматическое восстановление, диагностика сбоев. Развивать инфраструктуру под RL-эксперименты •  Развивать фреймворк обучения, поддерживающий RLHF / RLVR / PPO / GRPO / DPO и их вариации на масштабе. •  Делать так, чтобы новые RL-рецепты можно было быстро и безопасно запускать на больших моделях без ручной поддержки для каждого эксперимента. •  Обеспечивать воспроизводимость RL-экспериментов: версионирование данных, конфигов, чекпоинтов, reward-моделей. Писать ключевой код и оставаться сильным инженером •  Самостоятельно писать и дорабатывать критичные части RL-пайплайна. •  Профилировать обучение на всех уровнях стека и находить узкие места в rollout, обучении и коммуникациях. •  Оставаться сильным инженером и исследователем, а не только руководителем: при необходимости самому разбирать узкие места в коде, экспериментах и взаимодействии с hardware. Руководить сильной технической командой •  Руководить командой инженеров по эффективности RL, задавать высокую планку по качеству решений и перфу. •  Помогать команде превращать исследовательские идеи в работающие решения, которые можно встроить в основной цикл RL-обучения. •  Удерживать баланс между глубиной оптимизаций, инженерной надёжностью и практическим результатом для модели. Требования •  Отличное владение Python и PyTorch (DDP/FSDP, distributed training). •  Практический опыт с обучением LLM и понимание механики RL post-training: RLHF, RLVR, PPO / GRPO / DPO. •  Опыт оптимизации обучения и инференса LLM: профилирование, узкие места, параллелизм, mixed precision. •  Понимание архитектуры LLM: Transformer, attention (MHA/GQA/MLA), MoE и их влияние на rollout. •  Способность самостоятельно взять направление и довести его до результата: от постановки задач до внедрения в продакшн-RL. •  Опыт руководства сильной технической командой и готовность лично писать важные части системы руками. Будет плюсом •  Опыт работы с современными RL-стэками: verl, TRL или собственные решения. •  Опыт работы с large-scale inference (vLLM, SGLang, TRT-LLM) и оптимизацией генерации. •  Опыт написания CUDA / Triton ядер и понимание особенностей NVIDIA GPU. •  Понимание коммуникационного стека больших обучений: NCCL, NVSHMEM, RDMA/IB. •  Опыт работы с кластерными системами: Slurm, Kubernetes, Ray или собственные оркестраторы. •  Публикации, open-source вклад или сильный прикладной research track record. Условия •  Сильные и сложные задачи на переднем крае развития русскоязычных LLM. •  Большую степень влияния на архитектуру решений, методы обучения и качество итоговой модели. •  Команду сильных инженеров и исследователей. •  Возможность совмещать управление направлением с глубокой технической работой. •  Конкурентную компенсацию, премии и расширенный соцпакет.

Location: Москва Мы ищем сотрудника в команду сопровождения LLM продуктов. На данной позиции требуется поддержка самих моделей (как opensource, так и разработанных нашими командами), и api слоя. Чем предстоит заниматься? Обязанности * настраивать и сопровождать LLM модели и их окружение * участвовать в решении инцидентов, восстанавливать работоспособность и прорабатывать решения по повышению стабильности в работе стендов * настраивать CI/CD Требования * отлично знаете Linux * имеете опыт внедрения и сопровождения highload систем * понимаете принципы построения высоконагруженных и отказоустойчивых систем * опыт работы с системами контейнеризации (OpenShift / Kubernetes) * опыт работы с системами мониторинга и логирования (Zabbix, Grafana, ELK) * опыт работы с инфраструктурными компонентами (Nginx, Redis) * опыт написания скриптов на Python / Bash * опыт работы с Gitlab/Jenkins/Bitbucket Условия * комфортный современный офис рядом с м.Кутузовская * возможность выбрать удобный график – офис/гибрид * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте (для Junior позиций) * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * льготная ипотека для каждого сотрудника * бесплатная подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера. * корпоративная пенсионная программа * отсутствие строгого дресс-кода.

• Использование платформенных сервисов безопасности облака; • Формирование и внедрение secure-by-default настроек для используемых облачных сервисов;

Разрабатывать и поддерживать микросервисы на Go (REST API, консьюмеры, воркеры).

Задачи: построение инфраструктуры с нуля, Docker Swarm в production, GitLab CI/CD, администрирование Percona и последующий переход на Kubernetes.