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Location: Portugal; Albania; Georgia; Greece; Bulgaria; Kosovo; Bosnia and Herzegovina; Armenia; Italy; Spain; Malta; Romania; Ireland; Croatia; Serbia; Montenegro Workplace: Remote ABOUT BLOCK LABS Block Labs is a premier technology studio operating at the bleeding edge of Web3, Artificial Intelligence, and iGaming. We don't just ship features; we engineer high-scale, production-grade platforms that power the next generation of digital products. We are a collective of senior engineers, product strategists, and builders who refuse to compromise on architecture. Whether we are designing autonomous multi-agent AI systems, building decentralized financial infrastructure, or architecting high-frequency iGaming platforms, our standard is excellence. We move fast, but we build for the long term. If you are looking to work alongside a team that values deep technical expertise, thoughtful system design, and product ownership, Block Labs is where you belong. THE ROLE Data & Intelligence now sits at the centre of several products we are developing, and we need a platform that is both dependable and capable of supporting more advanced intelligence over time. This role reflects that shift. We are designing a new data platform that will act as the backbone for everything from real time decisioning to predictive modelling. As a Data Platform Engineer in the Data Team, you will own the end-to-end real-time pipeline, serving data across a unified analytical warehouse and feature-serving layer. You are not building dashboards. You are engineering the commercial nervous system of a multi-tenant platform designed to scale from one operator to 10x with marginal infrastructure cost. KEY RESPONSIBILITIES: - Design, build, and maintain scalable data pipelines using AWS Glue (PySpark), or equivalent orchestration and transformation tools. - Engineer and optimise the ClickHouse warehouse for sub-second query performance across all back-offices. - Implement data contracts between back-office and the platform. Onboarding a new operator is a config change, not new tables, topics, or feature views. - Build the feature-serving layer providing pre-computed features to AI agents at millisecond latency. - Integrate with third-party databases, back-office APIs, and external systems (CRM, affiliates, acquisition platforms). - Establish monitoring, alerting, and maintenance procedures including pipeline health checks, freshness monitoring, anomaly detection, and data contract SLA enforcement. - Own CI/CD and infrastructure-as-code for data workloads. - Collaborate with data scientists, agent engineers, BI developers, and infrastructure teams to translate data requirements into reliable, production-grade pipelines. ABOUT YOU: - 3+ years building and operating production data pipelines at scale, with hands-on experience across both streaming and batch paradigms. - Expertise in Apache Kafka (or Amazon MSK): topic design, consumer group management, offset handling, schema registry operations, and production troubleshooting of lag, rebalancing, and throughput issues. - Strong SQL and warehouse engineering skills: experience with columnar analytical databases (ClickHouse strongly preferred, or similar: Druid, BigQuery, Redshift). - PySpark / Spark Streaming proficiency: writing transformation jobs that normalise, enrich, and enforce business rules on event streams. Experience with AWS Glue, Apache Airflow, or Apache NiFi is a strong plus. - Data modelling discipline: ability to design normalised, multi-tenant schemas where tenant isolation is a filter, not a fork. Experience with data contracts and schema governance. - CI/CD and infrastructure-as-code experience: automated testing of data pipelines, version-controlled deployments (CloudFormation, Terraform, or CDK), and familiarity with containerised workloads (ECS Fargate or Kubernetes). - Data quality and observability mindset: experience implementing pipeline health monitoring, automated data validation (Great Expectations or equivalent), freshness checks, and anomaly detection. NICE TO HAVE - Experience in iGaming, online casino, poker, or sportsbook platforms. - Exposure to blockchain or crypto-native transaction flows, including on-chain event ingestion, token-denominated accounting, or stablecoin settlement. - Comfortable operating in an AWS-native environment (MSK, Glue, S3, DynamoDB, ECS, IAM). You understand serverless tradeoffs and can size infrastructure for cost efficiency. - Feature store experience (SageMaker, Feast, or Tecton) building offline/online feature pipelines that serve ML models at inference time. - Prior work in regulated industries (financial services, gambling, fintech) where data lineage, auditability, and compliance are non-negotiable. - Experience migrating legacy query engines (Athena, Trino, Presto) to modern analytical warehouses with reconciliation frameworks to validate correctness. HOW WE WORK - Fully remote with asynchronous-first communication. EU time zone overlap is preferred. - Small, high-autonomy team within the Data function. You report to the Head of Data and co-ordinate with the AI, BI, and Infrastructure Teams. - Architecture decisions are documented and debated. You will participate in design reviews and own your domain decisions. - We build for multi-tenant scale from day one. Every pipeline, schema, and contract you ship must absorb a new operator without engineering effort. - On-call rotation will be established in the run phase. During the build phase, the focus is velocity with quality. No firefighting legacy systems. What kind of culture can I expect? Mature, mission-driven, and low-ego. We value clarity over noise, outcomes over theatrics, and pace without chaos. If you’re one of the smartest minds in your craft and want to build with other experts, you’ll feel at home here.

Location: Serbia POWER A WORLD OF TRUST Incode is the leading provider of world-class identity solutions that is reinventing the way humans authenticate and verify their identities online to power a world of digital trust. Through our revolutionary identity solutions, we are unleashing the business potential of universal industries including finance, government, retail, hospitality, gaming, and more, by reducing fraud and transforming human interactions with data, products, and services. We’re in the process of rapidly scaling our diverse global team and we’re looking for entrepreneurial individuals and leaders who are curious, driven, and excited by ownership to join a Unicorn-status scale-up! About Incode Incode is a Series B unicorn rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security. Recently named a Leader in the Gartner® Magic Quadrant™ for Identity Verification, we're scaling fast and we're looking for an Analytics Team Lead to make the quality of our identity technology visible, measurable, and relentlessly data-driven. The Impact You'll Make This role sits on the Document Intelligence team — the group behind Incode's industry-leading document processing. Our technology parses identity documents from around the world — passports, visas, driver's licenses, proof of address, and more — for some of the biggest enterprises on the market. Machine learning is the core of the product, and Analytics is what makes its quality visible and its roadmap data-driven. We're looking for a Senior Lead of Data Analytics who is, first and foremost, a sharp hands-on analyst — and who has the leadership experience to grow a small, high-impact team around them. Today the team is three people; you'll be the fourth, owning it end-to-end. This is a true player-coach role: you'll manage and mentor the team while personally writing the pipelines, queries, and analyses. Our analytics is partially built — some data pipelines and testing procedures are already in place, but metric coverage and visibility are far from complete. Your mission is to close that gap. What You'll Own & Drive Lead & Grow the Team — Run the analytics team as a formal manager: own the roadmap, hold 1:1s and performance reviews, develop your analysts, and participate in hiring as the team scales. Stay Hands-On — This role involves a lot of personal execution. You'll write SQL and Python pipelines for data collection, processing, and labeling — and do the analysis yourself. Expand the Metric Tree — Build out the end-to-end metric tree that measures product quality across the document-processing pipeline, closing coverage gaps where the product is currently blind. Build Visibility — Create reporting and dashboards that surface weak points and turn raw signals into clear insights for ML, product, and leadership. Own ML Quality Evaluation — Drive data preparation for ML, model quality assessment, and benchmarking, in tight collaboration with the ML team. Drive Experimentation — Design, run, and interpret A/B tests across mobile and server side, with genuine statistical rigor. Guard Data & Labeling Quality — Monitor accuracy and consistency, and build the controls that keep them high. Bridge to Engineering — When events or data are missing, pinpoint exactly what's needed and where it should come from, write clear and actionable tasks for the backend and data teams, and justify their prioritization in business terms. Systematize — Turn one-off analyses into repeatable, owned pipelines and reporting cadences. Your Background Team leadership experience , paired with a genuine appetite to stay hands-on — you lead and you build. Strong Python , with a bias toward clean, maintainable, well-structured code. Strong SQL and solid experience with columnar / analytical databases. Strong statistics and experimental design — you can design tests (A/B and beyond), reason about significance and power, and interpret results correctly. Modern data tooling — experience with workflow orchestration, data transformation, cloud storage, and experiment-tracking. Our stack is Python, S3, Redshift, ClearML, Airflow, and dbt; equivalent tools are perfectly fine — what matters is that you've worked with this kind of stack. Excellent communication — you can translate a data gap into a prioritized, business-justified requirement, talk to engineers and stakeholders in their own language, and make the case for what gets built. High ownership, autonomy, and pragmatism — comfortable prioritizing impact over perfection in an evolving environment. Bonus points for: Experience with ML-centered products — evaluating model quality and working alongside ML teams. You won't be expected to train production models; at most simple models for data filtering, plus the ability to run existing ones. Familiarity with data labeling processes and quality estimation/maintenance. Domain exposure to identity documents, OCR, or computer-vision pipelines. The Qualities That Set You Apart A player-coach at heart — you draw energy from both growing people and doing the work yourself. Craftsmanship in how you build — clean code, sound pipelines, and analyses others can trust and reuse. Intellectual honesty and statistical rigor — you follow the data where it leads and know when a result is real. A translator's instinct — you turn ambiguous signals into clear insight and make the business case for what to build next. Pragmatism and high ownership — you thrive in an evolving environment and push for impact over perfection. Why Incode? Mission with Meaning — Shape how billions of people prove identity — safely, simply, and ethically. Rocket-Ship Growth — Join at a defining moment where your work compounds in global impact. Elite Team & Technology — Collaborate with top-tier engineers, researchers, and scientists at the forefront of AI. Ownership & Autonomy — Operate with the freedom to test, build, and ship your ideas end-to-end. Global Impact — Your work will shape secure, frictionless identity verification experiences across continents. Aspects of our Culture: High performance Freedom & responsibility Context, not control Highly aligned, loosely coupled Continuous Feedback Promotions & Development Learn more about Life at Incode ! Benefits & Perks: Flexible Working Hours & Workplace Open Vacation Policy Equal Opportunities: Incode is an equal opportunity employer, committed to creating a diverse and inclusive work environment. We take great pride in having an inclusive, diverse, and global team, and we are always looking for talented and passionate individuals from all backgrounds and walks of life. As part of our commitment to inclusion, we ensure that reasonable accommodations are available throughout the hiring process. If you require any accommodation due to a disability or specific need, please let our Talent Acquisition team know—we’ll do our best to support you. Applicant Data Privacy: We will only use your personal information concerning Incode’s application, recruitment, and hiring processes.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level and live longer through a deeper understanding of their bodies and daily lives. Protecting our members’ data and ensuring our systems scale securely and reliably is core to this mission.   The Application Infrastructure team enables iOS, Android, Backend, and Web engineers to reliably and quickly deliver new features to members. We own and operate critical shared infrastructure, including Kubernetes and Kafka, and build the tooling and guardrails that allow teams across WHOOP to ship safely at high velocity.   As a Senior Platform Engineer on the AppInfra team, you will play a key role in driving large-scale architecture projects, collaborating with cross-functional teams to design and implement infrastructure that is highly scalable, resilient, and secure. You will build systems that help increase the safety of deployments to Kubernetes while also increasing the velocity of releasing new features. You will be responsible for ensuring optimal performance and stability for the entire software delivery pipeline. You will help set the direction of the AppInfra team to impact engineers across all WHOOP technology stacks.   RESPONSIBILITIES - Design, develop, and operate WHOOP’s Kubernetes clusters running on AWS infrastructure - Drive architectural decisions to improve scalability, resiliency, performance, and security across the build and deployment platform - Build systems and tooling that increase deployment safety and accelerate release velocity to Kubernetes - Advance CI/CD capabilities to support frequent, reliable production deployments - Lead developer productivity improvements through tooling, automation, and platform integrations - Partner with application, security, and data teams to embed secure-by-default infrastructure practices - Participate in incident response, root cause analysis, and postmortems to continuously improve platform reliability - Mentor and provide technical leadership to engineers on the Application Infrastructure team - Help define and execute the long-term roadmap for infrastructure and Kubernetes management at WHOOP QUALIFICATIONS: - 5+ years of experience in DevOps, Platform, Site Reliability, CloudEngineering, or Backend Software Engineering roles - Deep understanding of Kubernetes architecture and core components - Strong knowledge of container networking concepts, including overlay networking, service meshes, and network policies - Experience with multi-cluster Kubernetes environments and inter-cluster communication patterns - Hands-on experience operating cloud infrastructure, preferably in AWS (e.g., IAM, VPC, EC2, S3, RDS, CloudTrail, Organizations) - Hands-on experience with Infrastructure as Code tools (e.g. Terraform) - Experience developing backend or infrastructure-adjacent services using Java, C#, or Python - Proven ability to evaluate system performance, identify bottlenecks, and use data to drive improvements - Experience collaborating with multiple stakeholders and prioritizing work for maximum business impact BONUS QUALIFICATIONS: - Experience operating Kafka or other large-scale distributed systems - Experience with Kubernetes security best practices, including RBAC, secrets management, and pod security standards - Exposure to service reliability practices such as SLOs, SLIs, and error budgets - Prior experience supporting compliance or security-focused infrastructure initiatives ABOUT YOU: - You bring a security-first mindset to everything you build and operate - You enjoy working on infrastructure that enables hundreds of engineers to move faster - You’re comfortable operating in complex, high-scale production environments - You enjoy teaching, mentoring, and raising the technical bar for those around you - You’re curious, adaptable, and excited to learn across a wide range of systems and technologies Learn more about our Software Org and how to be successful in your engineering career at WHOOP via our Career Framework https://engineering.prod.whoop.com/careerframework.   This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility.  It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.   The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The U.S. base salary range for this full-time position is $150,000 - $215,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.    In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.   These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: Aarhus 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 our 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. You will join a quantitative development function that works closely with Researchers, Traders and Cloud Engineering teams to build applications, data pipelines and analytics that support research and trading workflows. The role combines software engineering, quantitative development and data engineering, with responsibility for developing production applications, supporting research infrastructure and integrating large scale datasets. Your future role within QRT Design, develop, deploy and maintain cloud native Python applications supporting research and trading workflows, including market data dashboards, risk analytics, profit and loss reporting, weather analytics and performance analysis Develop quantitative tools including backtesting frameworks, optimisation tools, pricing libraries and ETL pipelines for integrating and validating alternative datasets Build and maintain scalable data pipelines that support model development and production workflows Monitor, support, debug and enhance existing research and trading infrastructure Work closely with Researchers, Traders and Engineering teams to deliver production quality solutions that meet evolving business requirements Provide support for traders and production trading systems as part of a support model that provides continuous coverage across global markets. Your present skillset At least three years of professional Python development experience Strong knowledge of Python, including numerical libraries such as NumPy, Pandas, Polars and Xarray Strong quantitative mindset with an interest in working closely with trading and research functions Experience developing user interfaces or an interest in building data visualisation applications such as Plotly, Dash or Streamlit is beneficial Experience with AWS or another cloud platform together with infrastructure as code technologies (e.g. Lambda, S3, DynamoDB, RDS or AWS CDK is advantageous) Good knowledge of relational databases such as PostgreSQL together with object storage technologies Experience developing ETL pipelines and working with large scale datasets Strong understanding of software engineering practices including version control, automated testing, packaging and deployment Ability to work independently while collaborating closely with business and technology stakeholders to deliver production solutions Experience with parallel or distributed computing is advantageous 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.

Location: Lagos, Nigeria Who We Are We’re a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role The Cloud Network and Infrastructure Engineer is responsible for designing, implementing, securing, and optimizing the Bank's hybrid infrastructure across Amazon Web Services (AWS) and on-premises environments. The role ensures the availability, reliability, performance, scalability, and security of enterprise infrastructure while supporting business-critical systems, cloud adoption, disaster recovery, and operational excellence. This role is ideal for someone who has strong expertise in cloud infrastructure, enterprise networking, systems administration, and infrastructure security, with the ability to manage hybrid environments in a fast-paced financial services organization. What You Will Do Design, deploy, administer, and support AWS cloud infrastructure, including compute, networking, storage, identity, monitoring, backup, and security services. Manage on-premises infrastructure, including Windows and Linux servers, virtualization platforms, storage, firewalls, switches, wireless infrastructure, and data center environments. Configure and maintain secure hybrid connectivity between AWS and on-premises environments using VPN, Direct Connect, routing, DNS, load balancing, and network segmentation. Monitor infrastructure performance, availability, capacity, and security using appropriate monitoring and alerting tools. Support business-critical applications through proactive incident management, troubleshooting, and root cause analysis. Implement and maintain infrastructure security controls, including IAM, access management, patch management, vulnerability remediation, encryption, logging, and firewall administration. Develop and maintain backup, disaster recovery, high availability, and business continuity solutions. Automate infrastructure provisioning and operational tasks using scripting and Infrastructure-as-Code (IaC) tools. Maintain infrastructure documentation, architecture diagrams, asset inventories, configuration baselines, and operational procedures. Participate in change management, incident management, problem management, audit activities, and compliance remediation. Optimize infrastructure and cloud costs through resource utilization reviews and capacity planning. Collaborate with Security, Applications, Database, Service Desk, and Business teams to deliver reliable infrastructure services. Requirements What You Bring Educational Qualification Bachelor's degree or Higher National Diploma in Computer Science, Information Technology, Engineering, or a related discipline. Professional Certifications AWS Certified Solutions Architect (Associate or Professional). AWS Certified SysOps Administrator. CCNA or CCNP. CompTIA Network+ or Security+. Microsoft Certified (Azure Administrator), VMware, Linux, or equivalent certifications. ITIL Foundation certification is an added advantage. Experience Minimum of 3–5 years of experience in Cloud, Network, Systems, or Infrastructure Engineering roles. Hands-on experience managing AWS cloud infrastructure and enterprise on-premises environments. Experience supporting hybrid cloud infrastructure within financial services, fintech, banking, or other regulated industries is an added advantage. Professional Competencies Strong knowledge of AWS services, including EC2, VPC, IAM, S3, RDS, CloudWatch, CloudTrail, Route 53, ELB, Auto Scaling, AWS Backup, and Systems Manager. Strong networking knowledge covering TCP/IP, routing, switching, VLANs, VPNs, DNS, DHCP, NAT, firewalls, wireless networks, and network security. Experience administering Windows Server, Linux, Active Directory, virtualization platforms, storage, backup, and patch management. Knowledge of infrastructure automation using PowerShell, Bash, Python, Terraform, CloudFormation, or similar tools. Strong understanding of infrastructure security, access controls, vulnerability remediation, hardening, encryption, logging, and compliance. Experience with infrastructure monitoring, capacity planning, incident response, performance tuning, and root cause analysis. Excellent analytical, troubleshooting, communication, and stakeholder management skills. Strong ownership mindset with attention to detail and the ability to work effectively under pressure. Ability to collaborate across Infrastructure, Security, Applications, Audit, and Business teams while driving continuous improvement. This Role Is Ideal For You If: You enjoy designing, managing, and optimizing cloud and hybrid infrastructure. You are passionate about cloud technologies, networking, and infrastructure security. You enjoy troubleshooting complex technical issues and improving system reliability. You thrive in highly available, mission-critical environments. You enjoy automating infrastructure and improving operational efficiency. You work well across cross-functional teams and can effectively manage multiple priorities. You May Not Enjoy This Role If: You prefer purely application development over infrastructure and platform engineering. You are uncomfortable responding to production incidents or participating in on-call support. You dislike troubleshooting complex infrastructure and networking issues. You are not interested in security, compliance, or operational governance. You prefer highly repetitive work with limited opportunities for continuous improvement. Benefits What's In It For You Opportunity to build and manage enterprise-grade cloud and hybrid infrastructure in a leading fintech organization. Hands-on experience with modern AWS technologies, automation tools, and enterprise networking solutions. Exposure to large-scale infrastructure modernization and cloud transformation initiatives. Opportunity to collaborate with Security, Product, Engineering, and Operations teams on business-critical platforms. Continuous learning, professional certifications, and career development opportunities. Competitive compensation and the opportunity to solve complex, real-world technology challenges.

Location: Amsterdam 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. Your future role within QRT: Design, build, and operate high-throughput distributed data systems that power quantitative research and production trading workflows. Develop production-grade Python services and pipelines to acquire, process, validate, and distribute large volumes of market and reference data. Build systems supporting both large-scale historical data processing and time-critical overnight pipelines on the path to trading. Design scalable processing architectures that partition work across QRT’s on-premises compute infrastructure and AWS. Build comprehensive observability and operational tooling to monitor data freshness, completeness, quality, and pipeline health. Collaborate closely with quantitative researchers, trading teams, software engineers, and infrastructure teams to onboard new datasets and improve research productivity. Take ownership of systems end-to-end, from architecture and implementation through deployment, production operation, and incident resolution. Your present skillset: 5+ years of experience building and operating production-grade data platforms, distributed systems, or large-scale data-processing applications. Strong Python software engineering experience, including the design of maintainable, tested, and performance-conscious production applications. Strong understanding of distributed processing concepts such as partitioning, parallelism, concurrency, fault tolerance, idempotency, and failure recovery. Experience designing systems that process large data volumes with demanding throughput or completion-time requirements. Hands-on experience with workflow orchestration technologies such as Apache Airflow. Experience with AWS services including S3, EC2, AWS Batch, IAM, CloudWatch, and cloud SDKs. Experience operating business-critical pipelines and diagnosing data, performance, and reliability issues in production. Excellent problem-solving skills and the ability to collaborate effectively across research, trading, engineering, and infrastructure teams. Nice to have: Experience building market-data platforms or other high-throughput financial data systems. Knowledge of non-equity asset classes such as futures, fixed income, commodities, or FX. Experience with time-sensitive overnight processing or systems operating on the path to production trading. Familiarity with Apache Parquet, Apache Arrow, or distributed processing frameworks such as Spark, Ray, or Dask. Experience with Docker, Kubernetes, and Infrastructure-as-Code tools such as Terraform or CloudFormation. C++ development experience. Experience working in high-performance computing or hybrid cloud environments. 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: — Проектирование, разработка, оптимизация и поддержка ETL процессов для загрузки данных из различных источников — Управление потоковой обработкой данных с использованием Apache Kafka (разработка продюсеров/консьюмеров, управление топиками, обеспечение надежности и отказоустойчивости) — Разработка и оптимизация структур данных, схем и запросов в PostgreSQL для операционных и транзакционных задач — Построение, администрирование и тонкая настройка ClickHouse кластеров для обеспечения высокой производительности аналитических запросов на больших объемах данных — Разработка и поддержка решений на базе ClickHouse (или связки PostgreSQL + ClickHouse) — Интеграция данных между PostgreSQL, Kafka, ClickHouse и другими компонентами инфраструктуры (API, очереди, S3) — Мониторинг производительности, отказоустойчивости и безопасности data pipeline и баз данных — Автоматизация процессов обработки данных и развертывания (CI/CD) — Взаимодействие с аналитиками, разработчиками и product owner'ами для понимания потребностей в данных и их реализации — Устранение неисправностей в pipeline данных и базах данных Требования: — Опыт работы от 2-х лет на Python, знание Golang (будет плюсом) — Опыт разработки и администрирования ClickHouse (знание особенностей движков таблиц, оптимизация запросов, кластеризация, репликация, шардирование) — Глубокое понимание и практический опыт работы с Apache Kafka, настройка и обеспечение надежности потоков данных — Опыт работы с PostgreSQL (написание сложных SQL-запросов, оптимизация производительности, понимание механизмов транзакций, репликации) — Понимание принципов построения ETL процессов — Знание SQL на продвинутом уровне — Понимание принципов DevOps (Docker, Kubernetes, Linux, CI/CD) применительно к инфраструктуре данных

Location: Mexico Company Background Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia. Project Description The role is focused on developing and modernizing real-time DSP serving services that process bid requests, deliver ads, integrate with third-party platforms, and record measurement events used for reporting and billing. The team works on high-throughput, low-latency systems processing millions of requests per second, with a strong focus on availability, data correctness, performance tuning, and scaling the platform for future growth. Current initiatives include splitting a monolith into microservices, improving deployment automation, and moving measurement pipelines from batch processing to real-time streaming with Kafka. Technologies Java Kafka / Kinesis Redis S3 Tomcat Docker, K8S Git, CI/CD What You'll Do Develop critical high-performance, large-scale services for DSP programmatic integrations and platform products; Work closely with the Product team to understand business needs and translate product requirements into technical solutions; Write clean, efficient, and production-ready code with a strong focus on high throughput and low latency; Design, develop, test, and improve new and existing platform features; Contribute to building large-scale distributed systems processing billions of transactions per day under strict SLAs; Improve test coverage, monitoring coverage, automation, and overall system observability; Follow Agile methodologies and work in a fast-paced engineering environment with quick delivery cycles; Job Requirements 5+ years of commercial experience in Java backend development, with a focus on scalable backend systems; Strong knowledge of the JVM ecosystem, including garbage collection, profiling, and performance tuning; Experience with distributed REST APIs, fault tolerance, scalability, consistency, and resilience; Hands-on experience with low-latency and high-throughput services; Experience with real-time streaming pipelines using Kafka, Kinesis, or similar technologies; Strong knowledge of data structures and algorithms; Experience with web/application servers such as Tomcat; Solid understanding of networking and load balancing concepts; Production experience with Docker and Kubernetes; Experience with Git and CI/CD pipelines, such as GitLab CI/CD or similar tools; Interest in applying modern technologies and AI-assisted development tools; Readiness to participate in PagerDuty rotation (1 week per quarter); Strong verbal and written communication skills, including the ability to explain complex technical trade-offs to both technical and non-technical stakeholders; English: B2 or higher; Nice To Have Prior experience in the AdTech industry; Familiarity with Python or Scala; What Do We Offer The global benefits package includes: Technical and non-technical training for professional and personal growth; Internal conferences and meetups to learn from industry experts; Support and mentorship from an experienced employee to help you professional grow and development; Health insurance; Sports activities to promote a healthy lifestyle; Flexible work options, including remote and hybrid opportunities; Referral program for bringing in new talent; Work anniversary program and additional vacation days.

Location: EMEA What you’ll be doing Work with a team of DevOps and DBA professionals Improve existing infrastructure and processes across the countries we’re deployed in, as well as streamlining processes to deploy to new countries in the future Continuously improve Kubernetes platform stability and efficiency, with a focus on optimising resource utilisation, reducing costs, and streamlining environment provisioning through GitOps-first practices Monitor and maintain cloud infrastructure through autoscaling, alerting pipelines, and Grafana dashboards covering metrics, logs, traces, and real user monitoring (RUM) Own weekday on-call operations, triaging and responding to production incidents, performing root cause analysis, and driving post-incident reviews Design and manage alert pipelines to ensure actionable signal quality, with attention to preventing alert fatigue, waterfall alerting, and notification flooding Define and maintain SLIs and SLOs for critical services, and use them to drive reliability improvements and on-call prioritisation Take ownership and responsibility for our cloud operation activities Liaise with external security agencies for annual audits as well as perform our own internal security sweeps Aid in reconfiguring existing architecture to allow for rapid deployments to new countries Mentoring less experienced team members What you’ll bring 3+ years DevOps / SRE / platform engineering experience Must be based in Europe Experience independently leading the planning and deployment of a project Experienced with cloud platforms, especially AWS, including solid knowledge of how to utilise cloud resources to fulfil the demand from other teams and production Strong understanding of Kubernetes and container orchestration, with experience in EKS and GitOps tooling such as ArgoCD and Helm being highly valued Experience with Infrastructure-as-Code, particularly Terraform Proficiency in scripting and automation with Bash, Python, or Golang; experience with Rust is a plus Hands-on experience with observability stacks covering metrics, logs, distributed traces, and profiling, for example Prometheus, Loki, Tempo, Pyroscope, and OpenTelemetry Experience with real user monitoring (RUM), with familiarity in Grafana Faro or OpenTelemetry SDK instrumentation being a plus Proven on-call and incident response experience, comfortable triaging production issues under pressure, leading post-mortems, and driving follow-up actions Ability to design and maintain alert frameworks that minimise noise, prevent alert fatigue, and avoid waterfall alerting patterns Experience defining SLIs and SLOs and using them to inform reliability work Familiarity with service mesh concepts is a plus, as we are actively evaluating Cilium-based service mesh in non-production environments Solid networking knowledge, especially the TCP / IP stack and HTTP protocol Experience handling high HTTP request volumes and designing systems for high availability and high traffic environments A strong understanding of cache, including CDN, HTTP cache, Redis / Memcached Excellent troubleshooting skills, including Linux OS issue diagnosis and OS parameter optimisation, JVM optimisation would be highly advantageous Our stack Languages: Java / Spring Boot, Node.js, Python, JavaScript Database: Aurora MySQL & PostgreSQL, MongoDB, MySQL Community Cache: ElastiCache, Redis, Valkey Messaging: Apache RocketMQ, AutoMQ, Kafka Networking & Proxy: Nginx, Kong, Cilium, eBPF Orchestration & GitOps: Docker, Kubernetes (EKS), ArgoCD, Helm Computing & Storage: AWS EC2, VPC, AWS Lambda, EBS, S3 CI/CD: Jenkins, GitHub Actions Metrics: Prometheus, Mimir, Grafana, Alertmanager Logs: Loki, Vector Traces: Tempo, OpenTelemetry, Alloy Profiling: Pyroscope RUM: Grafana Faro, OpenTelemetry SDK Infrastructure as Code: Terraform CDN & Edge: Cloudflare, AWS CloudFront AWS CloudWatch What’s in it for you Sporty is a remote first company in pursuit of sustainability A competitive salary + individual performance based bonuses every quarter 28 days paid annual leave Our core working hours are 10am-3pm in your local time zone with flexibility outside of this Referral bonuses & flash bonuses Top of the line equipment Annual company retreats to provide great internal networking opportunities Interview process Remote video screening with our Talent Acquisition Team Online assessment via Hackerrank Remote video interview with 3 x Team Members (45 mins each, not separate days) If you’re interested, we encourage you to apply! Every application is reviewed by a member of our team (AI is not used in our recruitment process), and we aim to respond within 48 hours.

Задачи: — Разработка backend на Python с использованием Django и Django REST Framework — Создание REST API — Работа с AWS сервисами: S3, RDS, SNS, SQS, CloudFront, CloudFormation — Реализация OAuth потоков — Использование AI инструментов и LLM — Работа с Celery (4.x/5.x) и брокерами сообщений (Redis или RabbitMQ) — Использование Docker (Dockerfile, docker-compose) и базовых CI/CD (GitHub Actions или аналогичные) — Работа с SQL и реляционными базами данных (PostgreSQL) — Использование Git (pull/merge requests, code reviews, Git Flow) Требования: — Опыт работы не менее 5 лет — Экспертные знания Python и Django (ORM, миграции, админка) — Опыт создания REST API с Django REST Framework — Опыт работы с AWS сервисами: S3, RDS, SNS, SQS, CloudFront, CloudFormation — Знание OAuth — Владение AI инструментами / LLM — Опыт работы с Celery и брокерами сообщений (Redis или RabbitMQ) — Опыт работы с Docker и CI/CD — Хорошее знание SQL и PostgreSQL — Владение Git — Свободное владение английским языком Желательно: — Знакомство с платежными шлюзами (Mollie, Stripe, PayPal) — Настройка и оптимизация Sentry, логирование и мониторинг — Инструменты тестирования и качества кода: Pytest, Flake8, Bandit, wemake-python-styleguide — Интернационализация и интеграции с внешними CRM/API — Базовые знания Vue.js или работа с фронтендом на Vue — Feature flags (django-waffle), расширенные админ-плагины (CKEditor, image-cropping, sortable2) — Poetry, Fabric, Django Channels (WebSockets) — Обработка PDF и изображений (PyMuPDF, Pillow, heif-image-plugin) Условия: — Полностью удалённая работа с гибким графиком — Конкурентная оплата (полный рабочий день или фриланс) в зависимости от опыта — Возможности профессионального роста и долгосрочного сотрудничества

Workplace: remote Requirements Strong experience in Python development Experience building LLM or agent-based applications using LangChain, LangGraph, or similar frameworks Hands-on experience with AWS Bedrock, including models, Agents, and tool/function calling Experience with AWS SageMaker and Bedrock Knowledge Bases Understanding of LLM limitations and practical challenges, including hallucinations, context management, and cost/latency trade-offs Experience designing end-to-end AI systems, including agent workflows and scalable AI services At least one real-world project involving AI agents deployed to production with measurable business impact or automation outcomes Experience creating custom tools/functions for AI agents Familiarity with evaluation, testing, and monitoring of LLM systems Strong communication and problem-solving skills English skills sufficient for technical communication and participation in project discussions Nice to have Hands-on experience with UiPath platform, including classic RPA and Agentic Automation Experience building and optimizing RAG pipelines (chunking, embeddings, retrieval tuning) Experience integrating AI agents with APIs, databases, and enterprise systems Familiarity with OpenSearch, vector databases, or semantic search solutions Experience with AWS Lambda, API Gateway, and S3 Experience deploying and supporting AI solutions in production environments Familiarity with AI governance, observability, or GenAI security practices Responsibilities Design and develop LLM and agent-based applications using modern AI frameworks and AWS AI services Build scalable AI workflows and agent orchestration solutions using LangChain, LangGraph, or similar technologies Develop and maintain integrations between AI agents, APIs, databases, and external systems Work with AWS Bedrock services, including models, Agents, and tool/function calling capabilities Support implementation of RAG-based solutions, including embeddings, chunking, and retrieval optimization Create custom tools/functions for AI agents and automation workflows Contribute to architecture decisions for scalable and production-ready AI systems Support evaluation, testing, monitoring, and continuous improvement of LLM-based applications Collaborate with cross-functional teams to prototype and deliver AI-powered automation solutions We offer Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota; Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Flexible working hours aligned to your schedule Options to work remotely Corporate medical insurance covering services of private and public medical centers English courses online Corporate parties and events for employees and their children Internal conferences, workshops and meetups for learning and experience sharing Gym membership compensation 5 days of paid sick leave per year with no obligation to submit a sick-leave certificate Any questions? Aliya hh@itransition.com

Location: Hybrid - San Francisco About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role The CDN Content team is responsible for serving all content that flows through Vercel's global CDN — static assets, optimized images, incrementally regenerated pages, partially prerendered shells, and everything in between — to billions of requests for millions of developers. Our focus is performance: ensuring content is served globally as fast as possible. Caching plays a big role in making that happen, and the team operates a multi-tier caching architecture spanning in-process caches, regional cache services, and object storage across 20+ regions. As a Software Engineer on the team, you'll take on well-scoped projects with real production impact and grow into owning larger pieces of the system. The work spans the serving path end to end, and everything ships through careful, progressive rollouts validated with production data. You'll learn how a planet-scale CDN works from engineers who built it. This is a team where infrastructure meets product: we work in close partnership with frameworks such as Next.js, bringing framework-defined infrastructure to life on Vercel's CDN, and the serving and caching behavior we ship directly shapes the performance and cost that millions of developers see. You'll develop strong instincts for distributed systems, careful production rollouts, and data-driven engineering. If you're based within a pre-determined commuting distance of one of our offices (SF or NY), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote. For location-specific details, please connect with our recruiting team. What you'll do Build and improve the services behind ISR, PPR, and image optimization — working in Go, Lua, and TypeScript across the serving path. Execute well-defined projects independently, from implementation through safe rollout (feature flags, shadow modes, progressive deployment) and post-ship validation. Monitor and maintain your work in production: build dashboards, add metrics and alerts, and develop ownership of what you ship. Contribute to the team's observability and testing surface — the dashboards, log views, and e2e test suites that keep a high-change system trustworthy. Participate in the on-call rotation with support from senior engineers, and contribute to incident follow-ups that make the system more resilient. Collaborate with teammates and partner teams (Next.js, CI/CD) through design discussions, code review, and pairing. What you need 2+ years of experience building and operating backend services in production. Proficiency in at least one of Go, TypeScript/Node.js, or a comparable systems language, and enthusiasm for working across a polyglot stack. Solid understanding of HTTP and web fundamentals — caching headers, request/response lifecycle, what a proxy does. You write code you're willing to operate: tested, instrumented, and documented. Curious about how large-scale systems work, and motivated to dig into unfamiliar code and production data to figure things out. A collaborative teammate who communicates clearly, asks good questions, and follows through reliably. Bonus if you Have experience with caching systems (CDNs, Redis/Memcached, application-level caches) at any scale. Have AWS experience, particularly S3 or ElastiCache. Have used Next.js or another modern web framework and understand rendering modes like SSR/SSG/ISR. Have experience with observability tooling (Datadog, Honeycomb, or similar). Have experience with Terraform or Kubernetes. Compensation & Benefits: Competitive compensation package, including equity. Inclusive Healthcare Package. Learn and Grow - we provide mentorship and send you to events that help you build your network and skills. Flexible Time Off. We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed. The San Francisco, CA base pay range for this role is $172,000 - $258,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. Disclosures: Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data. Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

Location: Austin; Yerevan Workplace: OnSite About the role Teza's Data Platform team owns the data the firm trades on: every backtest, every live strategy, every portfolio decision starts with data we ingested, cleaned, stored, and served. The scale, in plain numbers: - 1 PB of raw historical vendor data, growing by ~150 GB every day - 120 TB of processed, query-ready data in historical storage - Thousands of scheduled jobs: run by cron today, actively migrating to Apache Airflow - Alternative data delivered directly into the real-time feeds of live trading strategies This is a hands-on position on a small team of data engineers with growth potential. The firm is looking for outstanding technical skills, strong attention to detail, and a desire to architect and build data platforms. Location Austin, TX / Yerevan, Armenia (in-office requirement) Key Responsibilities - Work directly with Portfolio Managers and Quantitative Developers: turn their requirements into datasets and pipelines, and be the person who knows every nuance of the data they trade on. - Design and onboard new data sources into our warehouse; improve the robustness, speed, and scalability of our systems; manage data entitlements. - Build automated systems for data cleansing, anomaly detection, monitoring, and alerting, bad data must never reach a strategy. - Evaluate new tools and technologies for organizing, querying, and streaming large datasets, and when nothing on the market fits, build it. That's how the bitemporal store happened. - Support the production data warehouse the firm depends on. - Develop and maintain vendor relationships aligned with our business objectives. What we're building right now - A bitemporal data store, designed and written in-house from scratch. Every dataset answers both "what did we know then?" and "what do we know now?", which is what lets researchers trust a backtest. - A Python 3.14 migration of a large, long-lived codebase. - Adoption of the latest Apache Airflow: writing DAGs for the thousands of jobs moving off cron. - Pipelines for market data and alternative data: everything from exchange feeds to weather. - Real-time delivery: alternative data flows straight into strategies' live feeds. Pipelines you build sit in the trading path. - CI/CD for all of it, in GitHub Actions. Our Stack Python and Java · Apache Airflow · Slurm · NATS · PostgreSQL · MongoDB · S3 · NFS · GitHub Actions   Basic Requirements - Proficiency in Python and Unix/Linux for data manipulation, scripting, and automation. - Strong SQL, including query optimization and performance tuning, and familiarity with NoSQL. - A solid grasp of data modeling: normalization and denormalization, and the judgment to know when each applies. Nice to have - Financial industry experience or internships. - Java (part of our platform is written in it). - Experience with on-premises data infrastructure. - Familiarity with a cloud platform (AWS or GCP). - Apache Airflow or similar workflow orchestration tools. Benefits - Health, visual and dental insurance - Flexible sick time policy

Задачи: — Разработка и поддержка backend на Python с использованием Django и Django Rest Framework. — Создание REST API, работа с Django ORM, миграциями и админ интерфейсом. — Настройка и поддержка AWS сервисов: S3, RDS, SNS, SQS, CloudFront, CloudFormation. — Реализация OAuth потоков аутентификации. — Использование AI инструментов и LLM. — Работа с Celery (версии 4.x/5.x) и брокерами сообщений Redis или RabbitMQ. — Использование Docker (Dockerfile, docker-compose) и базовые знания CI/CD (GitHub Actions или аналогичные). — Работа с SQL и реляционными базами данных, предпочтительно PostgreSQL. — Использование Git, проведение Pull/Merge Requests, Code Reviews, Git Flow. Требования: — Опыт работы с Python не менее 5 лет. — Опыт работы с Django, Django REST Framework. — Знание PostgreSQL. — Опыт работы с Django ORM моделями. — Знание архитектурных паттернов RESTful API. — Опыт работы с брокерами сообщений Redis или RabbitMQ. — Опыт работы с кэшированием Redis. — Опыт работы с инструментами мониторинга Sentry (желательно Pytest, Flake8, Bandit, wemake-python-styleguide). — Опыт работы с AI инструментами (OpenAI, Claude, RAG / Knowledge Base Tools, Zapier, Make.com). — Профессиональное владение английским языком. Желательно: — Опыт DevOps: настройка и поддержка AWS сервисов. — Опыт настройки и поддержки CI/CD пайплайнов (GitHub Actions или аналогичные). — Знание платежных шлюзов Mollie, Stripe, PayPal и подобных. — Опыт настройки и оптимизации Sentry, логирования и мониторинга. — Опыт тестирования и работы с инструментами качества кода: Pytest, Flake8, Bandit, wemake-python-styleguide. — Опыт работы с интернационализацией и внешними интеграциями (CRM, API). — Базовые знания Vue.js или опыт взаимодействия с фронтендом на Vue. — Использование feature flags с django-waffle и продвинутых админ плагинов (CKEditor, image-cropping, sortable2). — Знание Poetry, Fabric, Django Channels. — Опыт обработки PDF и изображений (PyMuPDF, Pillow, heif-image-plugin). Условия: — Полностью удалённая работа с гибким графиком. — Конкурентная оплата, полная занятость или фриланс, в зависимости от опыта. — Возможности профессионального роста и долгосрочного сотрудничества.

Задачи: — Развертывание и поддержка облачной инфраструктуры в AWS (IaC через Terraform) — Администрирование кластеров Kubernetes (EKS) и управление деплоем через Helm — Настройка, оптимизация и защита пайплайнов в GitLab CI и GitHub Actions — Внедрение инструментов сканирования уязвимостей (SAST/DAST) и управление секретами в HashiCorp Vault — Настройка сквозного мониторинга и логирования (Prometheus, Grafana, ELK/Loki, Sentry), оперативное реагирование на инциденты — Участие во внедрении и поддержании практик информационной безопасности по стандарту ISO 27001 — Настройка и поддержка веб-серверов (Nginx), управление VPN, SSL/TLS сертификатами и DNS Требования: — Уверенное знание Linux (Ubuntu/RHEL) и владение Bash для автоматизации — Практический опыт работы с AWS (EKS, IAM, S3, RDS) и Ansible — Глубокое понимание процессов контейнеризации (Docker, Kubernetes) и автоматизации CI/CD — Понимание принципов сетевой безопасности, опыт работы с криптографическими протоколами и системами управления секретами — Знание принципов и практический интерес к внедрению стандартов безопасности ISO 27001 Условия: — Официальное оформление в соответствии с регламентом МФЦА (AIFC) — График работы 5/2, гибкий гибридный формат (сочетание офиса в Алматы и удаленки) с гибким началом дня — Стабильная заработная плата — Интересные и динамичные digital-проекты (включая AI-интеграции и масштабные веб-платформы) — Сильная техническая команда, минимум бюрократии и открытость к вашим технологическим инициативам

О компании Nexters: международная компания по разработке игр, входящая в холдинг GDEV, с офисами на Кипре, в Армении и Казахстане, а также возможностью удалённой работы. Обязанности: — Проектирование, создание и поддержка масштабируемых конвейеров данных (batch и streaming) — Поддержка и рефакторинг существующих решений — Основная зона ответственности — Bronze и Silver слои платформы данных — Разработка и поддержка моделей data lake / data warehouse — Оптимизация производительности Spark-джобов — Разработка и поддержка dbt моделей и контрактов данных — Внедрение и поддержка мониторинга, наблюдаемости и проверок качества данных — Работа с Kafka-стриминговыми конвейерами — Взаимодействие с командами аналитики, маркетинга, платформы и бэкенда Требования: — Уверенные навыки SQL и Python — Опыт создания ETL/ELT конвейеров в продакшене — Практический опыт работы со Spark/PySpark, особенно в стриминговых сценариях — Понимание распределённых систем обработки и хранения данных — Опыт работы с архитектурами data lake / data warehouse — Практический опыт с Delta таблицами, Parquet и S3 — Опыт работы с оркестраторами, такими как Airflow или аналогичными — Опыт работы с Kafka и стриминговыми конвейерами — Опыт поддержки и улучшения конвейеров данных в продакшене — Опыт с практиками наблюдаемости, мониторинга и качества данных Условия: — Медицинская программа (включая стоматологию) или компенсация, доступная в любом месте работы — Медицинская программа для членов семьи при работе в офисах на Кипре, в Армении и Казахстане — Оплачиваемый отпуск и больничные — Возможность работать в офисах или удалённо — Спортивные активности в офисах (йога, футбол, волейбол) — Пакет поддержки релокации при переезде в официальные локации — Курсы английского языка онлайн, уроки греческого и армянского для сотрудников в соответствующих офисах — Участие в гейм-джемах, хакатонах, конференциях и митапах — Поддержка социальных инициатив и участие в благотворительных проектах Формат работы: в офисах компании на Кипре, в Армении и Казахстане или удалённо.

Location: Amsterdam, Netherlands; Remote - Europe About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Role Nebius is looking for a deeply technical Technical Product Manager – Storage to join the team. In this role, the candidate will own the vision, roadmap, and priorities for storage services in Nebius Cloud , including block storage, file and parallel file systems, object storage, and the storage capabilities that underpin AI/ML and HPC workloads . The candidate will be responsible for shaping and managing backlogs for storage service teams and leading company-wide initiatives related to storage. This is a hands-on, technically demanding role: the candidate is expected to reason about storage internals, data paths, and performance trade-offs directly with engineers. It requires strong technical depth combined with the ability to coordinate across engineering, development, product, technical support, and go-to-market teams. Responsibilities Own and manage the product backlog for storage service teams (block, file, parallel/HPC, and object storage) Lead and coordinate cross-company initiatives involving storage, including data durability, performance, capacity, and cost initiatives Work closely with engineering and architecture teams to define product requirements at the level of data paths, consistency models, replication and erasure coding, and performance characteristics , and deliver new storage features Make informed technical trade-offs on durability, availability, latency, throughput, and cost, and defend them with data Partner with product marketing and technical pre-sales/post-sales teams on technical publications, go-to-market activities, customer engagement, acquisition, and retention related to storage Ensure the delivery of storage services that meet high standards for durability, availability, performance, scalability, and cost efficiency , including storage for AI/ML training and inference and HPC Requirements Hands-on experience building storage products in the cloud is the single most important requirement: the candidate must have designed, built, or operated cloud storage services (not just used or integrated them), in senior engineering, architecture, or technical leadership roles at hyperscalers, cloud providers, storage vendors, or other advanced technology companies Deep understanding of storage systems internals : block, file, and object storage architectures, distributed storage, replication and erasure coding, consistency and durability models, and the read/write data path Hands-on familiarity with technologies and interfaces such as NVMe/NVMe-oF, iSCSI, POSIX and parallel file systems (e.g., Lustre, GPFS/Spectrum Scale, BeeGFS), Ceph, S3-compatible object storage, and RDMA-based data paths Ability to reason quantitatively about IOPS, throughput, latency (including tail latency), and cost per usable TB , and to read and interpret benchmarks Strong technical expertise in at least two of the following areas: Block storage and virtualization (volumes, snapshots, replication, NVMe-oF) File and parallel file systems for HPC/AI (Lustre, GPFS, BeeGFS, NFS) Distributed storage internals (replication, erasure coding, consistency, repair) Storage performance engineering and benchmarking Object storage at scale (S3-compatible APIs, metadata, multipart, lifecycle) Proven track record of delivering complex technical initiatives requiring coordination across multiple teams or stakeholders Technical leadership experience is a strong plus Product management experience is not required , but a strong willingness to learn and grow into the role is essential Nice to Have Experience with storage for AI/ML training pipelines and large-scale HPC (checkpointing, data loading at scale, high-throughput sequential and random access patterns) Experience creating technical documentation, guides, tutorials, or reference architectures for storage products Ideal Candidate The ideal candidate is a technically strong professional with a background in cloud or cloud storage products at hyperscalers (AWS, GCP, Azure), other public cloud providers, storage vendors, their partners, or highly digitalized enterprises . The candidate may come from a background in storage engineering, distributed systems, architecture, SRE, or technical leadership , with hands-on experience building cloud storage services, distributed storage systems, or high-performance storage for ML and HPC . Experience in technical product or platform ownership or technical leadership is highly valued, even if the candidate has not held a formal manager title. Relevant experience in ML and HPC environments is strongly desirable given the storage demands of these workloads, though the candidate is expected to adapt quickly and learn new domains. About Nebius Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023). Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us! Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

MDiet — early-stage HealthTech стартап, разрабатывающий AI-powered платформу, которая помогает снижать количество повторных госпитализаций пациентов. Продукт ориентирован на рынок здравоохранения США. Возможна релокация в США при успешном росте компании, обсуждается индивидуально. Tech Stack: • LangGraph + LangChain / Agentic AI • vLLM + Hugging Face • PyTorch + PEFT / LoRA / QLoRA • Vector databases: pgvector, Qdrant, Weaviate, Chroma, Pinecone • Advanced RAG, Prompt Engineering, Embeddings • FastAPI + PostgreSQL • Docker + Kubernetes + async processing: Arq / Celery / Redis Streams • Apache Airflow для data pipelines • AWS Cloud: EC2, S3, SageMaker, Lambda, RDS, Bedrock • Structured output: Outlines / Guidance / Instructor • Evaluation & observability: Langfuse, RAGAS / DeepEval, Prometheus + Grafana • MLOps practices Задачи: • Проектирование и разработка multi-step LLM agents и pipelines для обработки медицинских данных • Разработка production RAG-систем с высоким уровнем grounding и качеством citation • Деплой и оптимизация self-hosted LLM inference через vLLM с фокусом на cost и throughput optimization • Fine-tuning open-source моделей на domain-specific medical data с измеримым улучшением результата • Построение data pipelines и versioning для документов, embeddings и training data • Создание evaluation frameworks, guardrails и систем контроля hallucinations • Реализация reliable structured output и data extraction • Тесное взаимодействие с physicians и Platform Architect Требования: • Сильный hands-on опыт с production LLM systems: RAG, agents, inference • Опыт fine-tuning open-source LLMs: LoRA / QLoRA / PEFT, с измеримыми результатами • Опыт построения data pipelines и versioning для LLM / RAG workloads • Сильные навыки в evaluation, hallucination reduction и structured output • Production Python + FastAPI + async processing • Опыт с self-hosted inference: vLLM или аналогичные решения • Опыт GPU optimization • Английский язык на уровне C1: strong written and spoken communication skills • Bachelor’s degree или выше в Computer Science, Artificial Intelligence, Machine Learning, Data Science или смежной технической области • 5+ лет опыта в ML/AI • 1.5–2+ года опыта в production LLM projects • Опыт с MLOps Будет плюсом: • Опыт в medical / clinical NLP или regulated domains • Cost modeling и optimization of LLM workloads • MLOps и production fine-tuning pipelines • Apache Airflow, Prometheus / Grafana или AI Solution Architecture • Publications in relevant fields Условия: • Работа в early-stage HealthTech startup с продуктом для US healthcare market • Возможность участвовать в создании AI-powered платформы с реальным влиянием на healthcare-процессы • Офисный формат в Астане первые 7–9 месяцев, далее возможен hybrid/remote • Зарплата $4 000 – $5 000 USD gross + equity • Возможность релокации в США при успешном росте компании, обсуждается индивидуально