Вакансии

Требования к специалисту: — Коммерческий опыт в DevOps или SRE от 4 лет. — Реальный опыт проектирования и построения инфраструктуры с нуля. — Опыт эксплуатации Docker Swarm в production. — Уверенное знание и production-опыт Kubernetes. — Опыт настройки GitLab CI/CD, раннеров и пайплайнов для фронтенда и бэкенда. — Понимание сетевой модели и проксирования через Nginx. — Опыт эксплуатации Percona XtraDB Cluster / Galera в production: кворум и split-brain, SST/IST, bootstrap после падения, бэкапы через Percona XtraBackup. — Опыт работы с Docker, PostgreSQL, Redis и S3-совместимым хранилищем. — Опыт настройки Prometheus, Grafana, Loki и Zabbix. — Готовность участвовать в архитектурных решениях, работе с командами разработки и технических переговорах с подрядчиками. Задачи: — Спроектировать и развернуть инфраструктуру продукта с нуля. — Настроить CI/CD пайплайны для фронтенда и бэкенда. — Поднять и сопровождать кластер Docker Swarm и процессы деплоя. — Спроектировать и провести миграцию на Kubernetes после завершения переезда. — Администрировать Percona XtraDB Cluster: отказоустойчивость, бэкапы и восстановление. — Настроить мониторинг, алертинг и логирование. — Работать с командами разработки и участвовать в технических переговорах с подрядчиками.

Location: Birmingham, Alabama, United States 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 operates large-scale, GPU-dense AI infrastructure across mission-critical data center environments. As a Senior Delivery Deployment Engineer, you will own the end-to-end delivery, deployment, and production readiness of next-generation GPU platforms inside our data centers. This role sits at the intersection of hardware, Linux systems, and operational execution. You will lead on-site rack bring-up, validate NVIDIA-based AI systems, coordinate repairs, and ensure GB-series infrastructure moves from installation to fully operational production environments with precision and reliability. You will collaborate closely with hardware engineering, networking, and infrastructure teams to deploy and stabilize H200 and B200-based GPU systems at scale. Your responsibilities will include: Lead end-to-end deployment of GB-series racks within data center environments Oversee installation, bring-up, validation, and production readiness of NVIDIA H200 and B200-based servers Troubleshoot complex hardware, firmware, Linux OS, and networking issues Execute structured testing and validation procedures during deployment Develop and maintain basic Linux-based hardware health-check and diagnostic scripts Coordinate on-site hardware repairs, part replacements, and vendor escalations Drive root cause analysis and ensure corrective actions are implemented Manage and prioritize deployment timelines across multiple concurrent rollouts Provide technical leadership and guidance to on-site engineers and technicians Partner with networking and infrastructure teams to ensure seamless integration Document deployment processes, validation standards, and operational runbooks What we expect you to have: Strong hands-on experience deploying and operating data center infrastructure Deep familiarity with GPU-dense systems, ideally NVIDIA H-series platforms Experience working with high-density rack deployments (GB-series or similar) Solid Linux experience, including troubleshooting and scripting Ability to diagnose issues across hardware, OS, firmware, and network layers Experience coordinating field repairs and working directly with hardware vendors Proven experience leading technical teams or overseeing field operations High ownership mindset and ability to operate in production-critical environments Clear communication skills and ability to collaborate across distributed teams It will be an added bonus if you have: Experience deploying AI or HPC clusters at scale Familiarity with automated provisioning or infrastructure lifecycle systems Background in hardware qualification, burn-in testing, or factory validation Experience supporting rapid infrastructure expansion Exposure to ARM-based or heterogeneous compute environments Working conditions: Collaboration with globally distributed engineering and operations teams Key employee benefits: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families 401(k) plan: up to 4% company match with immediate vesting Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers Remote work reimbursement: up to $85/month for mobile and internet Disability & life insurance: company-paid short-term, long-term, and life insurance coverage Compensation We offer competitive salaries, ranging from $112k- $140k base + quarterly performance bonuses. Join Nebius today and help build the software that powers the next generation ofAI infrastructure. #LI-AL1 Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $112,000 — $140,000 USD 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.

Location: Limassol Cyprus Workplace: OnSite ABOUT US Scorewarrior is a game developer and publisher based in Limassol, Cyprus. We are working on Total Battle — a cross-platform MMO 4X strategy game with a deep social system and extensive player interaction. We have 2 million monthly active players and continue to grow with the goal of becoming the #1 game in the genre. Our team consists of 200+ passionate, talented, self-driven, and continually developing professionals who love making high-quality games. ABOUT THE POSITION We are looking for a Senior Product Analyst to join our General Analytics team: the analytics lead, an analytics engineer and you. Product teams have their own analysts; we take the research questions they cannot answer on their own, and we own how analytics is done across the company. The core of the role is research: high-uncertainty product questions where the answer is the estimated effect of a specific factor, not a dashboard. Whether to extend the game's lifecycle, how to tell that a new giant feature works, how to run experiments on veteran players spread across hundreds of kingdoms. Alongside it you own the methodology: how experiments and effect estimates are done at Scorewarrior, and whether a number is good enough for a decision and useful to other analysts afterwards. It is a senior individual-contributor role: close work with the analytics lead, short cycles with game designers and product managers. Pilots of the infra components (experimentation platform, visualization system, AI analyst assistant, ELT) are driven by the analytics lead and the infrastructure itself by the data tech lead; you join as the customer, not the builder. Game industry experience is not required. WHAT YOU WILL BE DOING - Take high-uncertainty questions from product teams (Old Players, New Players, Quality of Life, Platform) from a vague question to a decision the team acts on. - Design and analyze experiments in non-standard setups: delayed treatment for veteran players, kingdom-level (cluster) tests, small samples, heavy-tailed revenue. Own variance reduction, outlier handling, permutation tests, MDE and power, reporting rules. - Estimate effects where a classic A/B test is impossible, using causal inference and quasi-experimental designs, and turn one-off solutions into methods other analysts reuse: reference documents, dbt data marts, Tableau dashboards. - Be the last check before the business acts on a number: the assumptions behind a metric, a test read-out or a pilot's output. - Use Python inside research when SQL is not enough: a graph algorithm over clan and kingdom networks, an optimization problem, a simulation. - Specify logging for features shipped by teams without their own analyst, and cover their ad-hoc questions. REQUIRED QUALIFICATIONS - Experience running research with high uncertainty end-to-end, from problem framing to a decision the team acted on. - Hands-on causal inference and quasi-experimental methods (difference-in-differences, synthetic control, matching or similar) on product questions: you can say what breaks an estimate and how you checked it. - Hands-on A/B test design and analysis, and the applied statistics behind it: distributions, power and MDE, variance reduction, heavy tails and outliers. - Strong SQL on an analytical data warehouse; ClickHouse is a plus. - Working Python for research: you can implement an algorithm or a statistical procedure that has no ready-made library call, and you understand what your code, or your AI assistant's code, does and whether it can work. No production services expected. - Clear, concise communication in writing and in person: you fix agreements, and you say so when a result cannot be trusted, including to the people who asked for it. - English at B1 or above. PREFERRED QUALIFICATIONS - Data science background alongside analytics: modeling, segmentation, validating assumptions with statistical tests. - Experience building or improving an experimentation platform, or setting methodology that other analysts followed. - Hands-on experience with dbt and Tableau. - Understanding of F2P economics, network effects, social or competitive systems; you play games and are ready to play Total Battle. WHAT WE OFFER - A team of professionals with a passion for gamedev and a drive to make Total Battle the #1 MMO 4X strategy game. - An excellent remuneration package, including a 13th salary. - Full relocation coverage for you and your family to Cyprus (Limassol). - A modern, sunny office close to the sea. - Private health insurance for you and your family members. - A monthly pre-school, school, and university allowance for employees' children. - Lunch compensation. - A sports and fitness allowance. - Company-funded personal development opportunities (professional and language courses, books, etc.). - Bonuses for outstanding results, years of service, marriage, and childbirth. - Friendly monthly office parties and epic annual offsite company birthday and Christmas celebrations.

Location: Warsaw, Mazowieckie, Poland; Sofia City, Bulgaria; Limassol, Cyprus Workplace: hybrid Capital.com's Product Security team protects our web and mobile applications, infrastructure, and external perimeter in a highly regulated environment. As Senior/Staff Application Security Engineer, you will raise the bar for application security across the organisation. This role is measured by leverage: how well you design, automate, and scale security processes so that many engineering teams can build securely by default. You will lead security architecture reviews and threat modelling, increasingly with the help of AI tooling, and turn one-off security work into repeatable, self-service capabilities. The role combines deep hands-on offensive and defensive security expertise with the engineering mindset needed to automate at scale. You will work closely with development, QA, DevOps, and platform teams. Responsibilities: Security Architecture & Threat Modelling: Lead security architecture reviews and threat modelling for new and existing systems, using AI tools to make reviews faster, more consistent, and scalable across teams Act as a security force multiplier by influencing the standards, patterns, and guardrails that let teams move fast and stay secure Security Automation & Tooling: Design, build, and automate scalable security processes that engineering teams can self-serve, covering secure design review, threat modelling, testing, and remediation workflows Integrate and automate security checks across the SDLC and CI/CD pipelines (SAST, DAST, SCA, secrets, and IaC scanning), tuned for strong signal and low friction Own and evolve security tooling such as DefectDojo and SAST, DAST, and SCA platforms, maximising automation, coverage, and integration Apply AI and LLM-based tooling to architecture review, threat modelling, code review, and vulnerability triage, and help define how the team adopts these tools safely Security Testing & Vulnerability Management: Conduct and oversee security assessments of web and mobile applications, APIs, and cloud infrastructure, including manual testing and PoC development Run vulnerability scans across internal infrastructure and the external perimeter, then analyse findings, define remediation, and track issues to closure Support and triage the Bug Bounty Program and external vulnerability reports, automating triage where possible Participate in and help lead red teaming and offensive security exercises Enablement: Drive knowledge sharing on secure development, mentor engineers, and deliver training for development and QA teams Requirements: Experience: 5+ years in application or product security, or equivalent depth, with a track record of senior or staff-level impact Demonstrable experience leading security architecture reviews and threat modelling (e.g. STRIDE, attack trees, data-flow analysis) across multiple teams or products Proven ability to automate and scale security processes by building tooling, integrations, and self-service workflows that reduce manual effort Technical: Strong hands-on security testing skills, including code review and web, mobile, and API application security assessments, as well as the ability to triage and validate external vulnerability reports and bug bounty submissions Strong software engineering ability in at least one language (e.g. Python, Go, JavaScript), with the ability to build automation, not just scripts Deep understanding of the OWASP Top Ten, secure design, and secure coding best practices Experience with SAST, DAST, SCA, and vulnerability management platforms, and integrating them into CI/CD Strong understanding of modern application architectures: REST APIs, microservices, cloud-based systems, and containers Practical experience applying AI and LLM tooling to security work, or clear enthusiasm and aptitude to do so Collaboration: Excellent communication and influencing skills: you can explain security concepts to technical and non-technical stakeholders and drive change without direct authority A self-starter who enjoys solving complex problems, building leverage through automation, mentoring others, and strengthening security culture Nice to have: Experience securing the AI harness: hardening LLM and agent pipelines, prompts, tool and MCP integrations, and model endpoints against prompt injection, data leakage, and insecure agent actions Experience securing Kubernetes, including cluster hardening, RBAC, network policies, admission control, workload isolation, and image and supply-chain security Experience securing AWS infrastructure, including IAM, network and account architecture, key and secret management, and CSPM Experience building AI-assisted security tooling or internal self-service security platforms Experience mentoring or technically leading a security team Offensive or advanced security certifications such as OSAI, OSEP, OSCP, or OSWE What you'll get in return: You will join the company, that cares about work and life balance Annual Bonus based on the performance review cycle Generous Annual Leave Policy Medical Insurance and Pension fund, with additional benefit packages based on the location Hybrid working model (3 days from our modern office and 2 days fully remotely) Comprehensive Workation Policy with 30 more remote days available. Possibility of taking two additional days of paid leave per year to dedicate to volunteering efforts.

Задачи: — Руководить командой, создающей интеллект для AI-агентов ZoomInfo, отвечая за стратегию B2B data graph, включая классическое машинное обучение, data science, LLM и агентные системы. — Устанавливать технический уровень команды старших инженеров, участвовать в написании кода, прототипировании и ревью. — Отвечать за полный цикл доставки продукта: от постановки задачи до поддержки, включая покрытие графа и управление пользовательской памятью агентов. — Выбирать подходящие методы решения задач (классическое машинное обучение, языковые модели, код) для проблем, таких как оценка доходов компаний, entity resolution, семантическое моделирование намерений. — Определять критерии корректности вывода агента, создавать наборы данных для оценки, регрессионные проверки и дизайн экспериментов. — Управлять затратами на инференс, задержками и мощностями, принимать решения о построении или покупке моделей, дистилляции. — Нанимать и развивать инженеров машинного обучения, data scientists и research engineers, развивая технических лидеров. — Взаимодействовать с продуктом, платформой, безопасностью и юридическим отделом, представлять результаты руководству, включая случаи, когда система не готова к запуску. Требования: — Значительный опыт создания production ML-систем и руководства инженерами, с активным участием в коде и прототипировании. — Опыт найма и развития старших ML-инженеров и data scientists. — Глубокие знания классического машинного обучения и data science (supervised learning, feature engineering, статистический вывод, дизайн экспериментов, SQL) вместе с опытом production LLM и агентных систем. — Опыт принятия решений по стоимости и мощности моделей, включая миграцию с хостинга на дистиллированные или self-hosted модели, с измерением экономии и отчетностью перед руководством. Преимущества: — Предпринимательский опыт: основание компании или участие в запуске продукта с нуля. — Опыт в propensity modeling, ranking and retrieval, clustering, entity resolution в масштабе. — Опыт работы с языковой обработкой на веб-масштабе, многоязычным, шумным текстом, knowledge graphs, пользовательской памятью агентов. — Опыт пост-тренировки и дистилляции моделей, открытого сервиса моделей, практик AI governance и безопасности (ISO/IEC 42001, NIST AI RMF). Условия: — Гибридный формат работы (указан #LI-hybrid). — Годовая базовая зарплата в США от $233,100 до $366,300, возможны бонусы, комиссии, акции и другие льготы. — Компания предлагает комплексные программы поддержки здоровья и благополучия.

Location: Limassol, Cyprus The System & Infrastructure Administrator is responsible for the day-to-day administration, support, security, and reliable operation of the company’s corporate IT environment. The role ensures that user access, infrastructure, internal services, networks, endpoints, and core business systems remain available, secure, and properly maintained to support daily business operations. Responsibilities Manage the full employee access lifecycle (Joiner–Mover–Leaver) across Microsoft 365, Active Directory, GitLab, 1C-related systems, Slack, ClickUp, Vaultwarden, VPN, file storage, and other corporate services. Provision and revoke accounts, access, licences, MFA, SSO, VPN access, equipment, and company assets; update access promptly when employees change roles or leave. Administer Microsoft 365/Entra ID, Windows Server, Active Directory, Group Policy, DNS, DHCP, file services, Linux systems, and SMB-based shared storage. Maintain server and virtualisation infrastructure, storage, backups, internal services, and remote-access solutions. Administer office networks, Wi-Fi, VLANs, VPNs, firewalls, switches, routers, DNS records, domains, and TLS certificates. Monitor infrastructure and backup jobs, perform regular recovery tests, apply patches and updates, and troubleshoot incidents. Operate endpoint protection, EDR, vulnerability-management, logging, and SIEM tools; triage alerts and escalate security incidents when required. Provide infrastructure-level support for SWIFT, 1C-related systems, corporate websites, and internal web services. Provide L2–L3 support for employee endpoints and workplace technology, including advanced troubleshooting, hardware replacement, OS and application issues, access-related problems, encryption, VPN connectivity, and escalated technical incidents. Manage the lifecycle of laptops, peripherals, IT assets, software licences, subscriptions, repairs, and approved purchases. Maintain technical documentation, asset and access records, recovery procedures, and operational runbooks; automate repetitive tasks where appropriate. Requirements 3+ years of hands-on experience in system administration, infrastructure support, or corporate IT operations. Strong practical knowledge of Windows Server, Active Directory, Group Policy, Microsoft 365/Entra ID, DNS, DHCP, and access management. Working knowledge of Linux administration and troubleshooting. Strong understanding of TCP/IP, VLANs, routing, NAT, VPNs, Wi-Fi, firewalls, NAS, and SMB. Experience with virtualisation, Proxmox, ZFS, LVM, storage systems, backup systems, and recovery procedures. Experience with Docker, GitLab CI, and container registries. Understanding of RBAC, least privilege, MFA, SSO, privileged and service accounts, access reviews, patching, endpoint security, and incident escalation. General knowledge of cloud providers and cloud concepts, including compute, storage, networking, IAM, monitoring, backups, shared responsibility, and basic cost awareness. Experience supporting employee devices at L2–L3 level and working with an ITSM/helpdesk system. Basic automation skills in PowerShell, Bash, Python, Ansible, or APIs. Good written English and the ability to maintain clear technical documentation. Nice to Have Hands-on experience with AWS, including IAM, EC2, VPC, S3, Route 53, CloudWatch, or AWS Backup. Experience operating or troubleshooting Kubernetes clusters. Experience with SIEM, EDR, vulnerability scanners, PKI, certificate automation, or secrets-management systems. Experience supporting 1C, SWIFT, financial systems, Microsoft Intune, or ITAM/CMDB platforms. Benefits Competitive salary; Annual performance bonus; Access to our Limassol offices, including daily drinks and snacks, as well as parking facilities; Working hours are from 9:00 to 18:00, with a shorter day on Fridays until 16:30; 24 working days of paid annual leave, in addition to statutory public and bank holidays in Cyprus; 14 working days of paid sick leave per calendar year; Work permit sponsorship and full support with all related arrangements; The opportunity to participate in corporate sports activities and events, and receive corporate gifts.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Account Abuse team is tasked with ensuring Anthropic's computing capacity is allocated fairly, minimizing resources available to bad actors and preventing them from coming back. As a software engineer on this team, you will build the machine learning systems that help us detect and stop abuse at scale. The ideal candidate can see things from opponents' perspectives, understand their means and motives, and anticipate their responses to countermeasures. We're looking for full stack machine learning engineers with experience across model training, productionization, and evaluation. You'll also look for ways to use Claude to speed up how these models get built and maintained. This is classical ML on structured and behavioral data. You do not need a deep learning background or knowledge of LLM internals. What matters is that you have trained and shipped models where the stakes are real, and that you care about building robust production systems as much as the model itself. A false positive here is a legitimate customer locked out, so measurement, precision, and safe rollout are part of the job. Key responsibilities Build and operate a feature computation platform that serves both model training and real-time scoring, with point-in-time correct training data and low-latency online retrieval Train, evaluate, and deploy models that detect account-level abuse and fraud, running them both offline and online Build tooling that automates more of the model development lifecycle, including using Claude to speed up feature development, training, and evaluation Make backtesting, shadow deployment, and staged rollout the default path to production, with monitoring for training / serving skew, drift, and adversarial adaptation Work with our data scientists and our Policy & Enforcement team to improve label coverage and quality Partner with product and platform teams to gather signals and integrate model decisions with minimal impact on their systems' latency, stability, or overall architecture Minimum qualifications Proficiency in Python and SQL Experience training machine learning models and deploying them to production Experience building data pipelines with a batch processing engine (e.g., Spark, Beam) and a workflow scheduler (e.g., Airflow) Working understanding of point-in-time correctness and training / serving skew, and how to prevent both Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders Preferred qualifications Experience building or operating a feature platform such as Chronon, Feast, or Tecton Experience with stream processing engines such as Flink, Beam / Dataflow, or Kafka Streams Experience training ML models in a production setting with demanding serving requirements, such as fraud, risk, or ranking Experience with tree-based models on tabular data Experience building unsupervised, clustering-based or graph-based detection systems to surface coordinated account abuse Experience in integrity, spam, fraud, or abuse detection Experience working with scarce, delayed, or noisy labels Experience with AutoML or other approaches to automating the ML workflow Care about the societal impacts of AI and want your work to make powerful systems safer The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Andorra la Vella, Andorra; Buenos Aires, Argentina; Brasilia, Brazil; Rio de Janeiro, Brazil; Barcelona, Spain; Madrid, Spain; Milano, Italy; Rome, Italy; Abu Dhabi, United Arab Emirates; London, United Kingdom; Lugano, Switzerland; Warsaw, Poland; Amsterdam, Netherlands; Lisbon, Portugal; Dublin, Ireland; Bucharest, Romania; Bangalore, India; Kuala Lumpur, Malaysia Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio. We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios. Responsibilities Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint. Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms. Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions. Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems. Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements. A degree in Computer Science  or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch. Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms. A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios. Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required. Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency. Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters. Deep understanding of the math and structure behind Diffusion Models and Vision Transformers Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc. Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles: Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/ Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website. Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms. Double-check email addresses. All communication from us will come from emails ending in @ tether.to or @ tether.io We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately. When in doubt, feel free to reach out through our official website.

Location: India 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 We’re looking for an experienced leader to own data center IT operations across APAC, covering both Nebius-owned and colocation sites. You will lead operations for GPU and high-performance computing (HPC) infrastructure, including high-density and liquid-cooled platforms. In this role, you will build and scale the regional operations organization and own the full operational lifecycle: preparing new sites for service, delivering reliable 24/7 support, managing hardware assets and returns, and overseeing changes to infrastructure in production. Your responsibilities will include: Full-stack IT operations Define and run the support model per site: 24/7 L1/L2 on-site, L3, on-call/duty coverage; final escalation point for critical incidents; RCAs and preventive actions. Own post-acceptance change management: upgrades, migrations, maintenance windows, decommissioning. Ensure availability and performance of compute, storage and network infrastructure in operation. New sites into operations Own operational readiness for every new DC : staffing, access, tooling, monitoring, ticketing, spares, documentation. Define acceptance criteria and handover from the Project team; sign off on acceptance into operations. RMA , asset & spare management Own the global asset lifecycle: intake, CMDB accuracy, audits, decommissioning and e-waste. Own RMA end to end: OEM channels, warranty terms, partner/franchise RMA integrations. Set spare-zone standards and stock levels per site; balance spares against failure rates and SLAs. Service governance & vendors Own SLAs and OLAs with platform, storage, network, internal teams. Manage colocation, field-service, outsourcing and OEM relationships: scope, SLAs, performance, disputes. Manage and report operational KPIs, risks and capacity to senior management and colocation tenants. Team, processes & compliance Org design and headcount forecasting from the DC launch pipeline; own the hiring pipeline (JDs, interview loops, recruiters, outsourcing, internships). Own ITDC processes, SOPs/runbooks, documentation and Jira/Confluence standards; competency and training frameworks. Ensure audits readiness, security posture reviews, DC access management and EHS adherence. We expect you to have: 10+ years in data center IT operations including hands-on infrastructure support; 5+ years leading managers across multiple sites or countries. Experience taking new data centers or clusters from build into operations. Deep operational knowledge of RMA , asset management and spare planning at scale. Familiarity with GPU/ HPC infrastructure and its failure modes. Experience owning SLAs/OLAs and RACI between infrastructure teams; strong ITIL / ITSM grounding. Vendor and contract management with colocation providers, field-service vendors and OEMs. Experience building and scaling teams; fluent English; readiness to travel. It Will Be an Added Bonus If You Have Experience with GB200 / GB300 -class liquid-cooled deployments ( DLC , CDU operations). Experience with franchise or outsourced DC operating models. Audits experience; ITIL or PMP certification. 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.

Location: United States Workplace: Remote About Cantina: Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning. If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future! About the Role: Cantina is a place where people create AI characters and the videos those characters star in, and the catalog grows far faster than anyone can browse. Search and recommendations are what turn that catalog into a product: they decide which characters a new user meets in their first minute, which creators get discovered, and what appears in every feed, leaderboard, and discovery surface we ship. We are hiring a Senior Staff Software Engineer to own that area end to end — retrieval, ranking, relevance quality, and the roadmap for all three. This is the first dedicated hire for search and recommendations, so you will inherit a real production system serving live traffic along with a large amount of unclaimed ground, and you will set the technical direction rather than execute someone else’s. What you'll do: - Own the architecture and roadmap for search and recommendations end to end — query understanding, retrieval, ranking, and the surfaces they feed: search, discovery, the home feed, and our trending and creator leaderboards. - Make relevance a measured discipline rather than an opinion: define the quality metrics per surface, build the offline evaluation and golden-set tooling, and run the online experiments that decide whether a ranking change ships. - Design and evolve the ranking stack — engagement signal pipelines, decay and freshness models, and the pattern we use to combine pre-computed index-time signals with live re-ranking at query time. - Own OpenSearch in production: index and mapping design, reindex and cutover safety, query performance, cost, and the operational headroom of the clusters behind every discovery surface. - Build candidate generation and personalization for recommendation surfaces, and partner with data and ML on the feature pipelines and models behind them. - Work directly with Product and Trust & Safety on what “good” means for each surface — quality gates, cold-start behavior for brand-new creators and characters, and what must never be recommended. - Set the engineering standard for the area: instrumentation, flag-gated rollouts, and runbooks that let other teams change ranking behavior without breaking it. - Act as the technical point of contact for discovery across backend teams, and mentor the engineers whose work touches it. What you'll bring: - 10+ years building production software, with substantial depth in search, ranking, recommendations, or ML-driven relevance on a consumer-scale product. - Hands-on expertise with a production search engine — OpenSearch, Elasticsearch, Lucene, Vespa, or similar — covering index and analyzer design, relevance tuning, and operating the cluster, not only querying it. - A rigorous approach to relevance measurement: you have owned offline evaluation, golden sets, and A/B or interleaving frameworks, and you can explain what moved a metric and why. - Fluency across the recommender stack — candidate generation, feature pipelines, embedding retrieval, re-ranking — and a working understanding of the serving constraints that make an offline win fail online. - Strong distributed systems and backend fundamentals, with production experience in Go or a comparable systems language, and comfort in the data layer behind it (SQL warehouses, streaming and batch pipelines). - Demonstrated ownership of an ambiguous area: you have picked up something with no dedicated owner, decided what mattered, and can show the result. - Clear written communication and the judgment to work with Product on real tradeoffs between relevance, freshness, safety, and latency. - Preferred: experience with AI-generated or rapidly growing content catalogs, severe cold-start conditions, or ranking under trust-and-safety constraints. Compensation: The anticipated annual base salary range for this role is between $250,000 - $320,000 (USD). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.   Benefits: - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!

Location: Paris; Zurich; Warsaw; London ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE RESEARCH ENGINEERING TEAM   The team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the research↔production spectrum as needs or interests evolve.   As a Research Engineer – ML track, you’ll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you’ll either join:   - Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or - Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, Safety …) and turn fresh ideas into repeatable, scalable code.     What You Will Do   • Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools. • Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs. • Design, implement and benchmark ML algorithms; write clear, efficient code in Python. • Deliver prototypes that become production-grade components for Vibe and our enterprise API.   What We're Looking For   • Master’s or PhD in Computer Science (or equivalent proven track record). • 4 + years working on large-scale ML codebases. • Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s). • Experience in deep learning, NLP or LLMs; bonus for CUDA or data-pipeline chops. • Strong software-design instincts: testing, code review, CI/CD. • Self-starter, low-ego, collaborative.   WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris; Amsterdam; Linz; Munich; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is looking for a Domain Expert in crashworthiness simulations to help build AI-accelerated simulation capabilities for industrial engineering. You will work at the intersection of industrial simulation, physics modeling, machine learning, and engineering workflows. Your role is to bring deep solid-mechanics expertise into the design, training, evaluation, and deployment of AI Physics Models for real engineering use cases. This is a hands-on technical role. We are looking for someone who understands industrial structural simulation not only conceptually, but through direct experience with simulation models, solver workflows, data generation, validation, and engineering decision-making. You will work with research, product, and customer-facing teams to ensure that our models are useful against real engineering standards — not only benchmark metrics. Relevant application areas may include automotive crashworthiness, aerospace structures, consumer-electronics drop/reliability, manufacturing, durability/fatigue, and other nonlinear structural mechanics problems. WHAT YOU WILL DO - Work with our research team to define, generate, and iteratively improve simulation datasets for training and evaluating crashworthiness foundation models, balancing coverage of relevant physical scenarios, simulation fidelity, and computational cost. - Design and run high-fidelity simulation campaigns using structural mechanics solvers such as Abaqus, LS-DYNA, Ansys Mechanical, Radioss or equivalent tools. - Define the relevant variation space for training data: geometry, mesh resolution, material behavior, boundary conditions, loading, contact, joints, failure modes, and engineering KPIs. - Build or guide automated pipelines for simulation setup, execution, post-processing, dataset creation, and model evaluation. - Work with research teams to train and evaluate AI models on simulation data, and diagnose failure modes caused by data gaps, poor coverage, numerical artifacts, or model limitations. - Evaluate model outputs against industrial engineering needs, including field-level accuracy, scalar KPIs, deformation modes, load paths, energy absorption, stress/strain fields, failure indicators, uncertainty, and out-of-domain behavior. - Work with industrial customers to understand their simulation workflows and engineering priorities, define use cases and success criteria, and incorporate their feedback into model development and validation. ABOUT YOU - You have deep expertise in crashworthiness, solid mechanics, and structural mechanics, with substantial experience in industrial simulation workflows. - You have a Master’s degree or equivalent technical depth in mechanical engineering, aerospace engineering, civil/structural engineering, computational mechanics, applied physics, or a related field. - You have 4+ years of relevant industrial experience (or PhD +1 years) in domains such as automotive, aerospace, and consumer electronics. - You have hands-on experience with explicit dynamics for crash or impact simulation and understand nonlinear FEM and related topics such as contact, plasticity, structural dynamics, buckling, material modeling, fracture/damage, fatigue, crashworthiness, or durability. - You have direct experience with simulation validation, correlation, model quality, numerical sensitivity, and engineering KPI definition. - You are a strong Python developer who can build and maintain reliable tools for simulation automation, data processing, and model evaluation. You apply sound software engineering practices, including version control with Git, automated testing, code review, and clear documentation. - You have hands-on experience working in Linux and HPC environments, including submitting and monitoring batch jobs, selecting appropriate compute resources, and troubleshooting simulation workflows. You can run simulation campaigns efficiently across a compute cluster. - You are comfortable operating in ambiguous technical environments and turning poorly defined industrial problems into scoped datasets, experiments, metrics, and execution plans. - You communicate clearly with both deep technical experts and non-specialist stakeholders. IT WOULD BE GREAT IF YOU - Have experience applying machine learning, surrogate modeling, reduced-order modeling, optimization, or data-driven methods to simulation problems. - Have contributed to reusable internal tools, open-source code, simulation automation frameworks, or production-quality engineering workflows. - Have experience working directly with industrial customers, product teams, or engineering decision-makers. - Have publications, patents, internal technical leadership, or recognized contributions in engineering, simulation, computational mechanics, or ML-for-physics communities. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Singapore ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is seeking Applied Scientists and Research Engineers focused on robotics. You will design, train, and deploy SOTA robotics models (VLM, VLA models for navigation and manipulation) and apply them to diverse use cases. You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions. WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on large clusters. - Generate and curate datasets (image-text, video-text), and build evaluators/benchmarks for perception, navigation and manipulation tasks. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. ABOUT YOU - Fluent in English with excellent communication skills. - Expert with PyTorch or JAX. - Experience with Vision Language Models (VLM), Vision-Language-Action (VLA) models, perception, navigation and manipulation, simulation tools (e.g. Isaac SIM). - Clean, readable, high-performance Python code. - Doesn't need roadmaps. Ships. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - PhD / Master in a relevant field (Robotics, Machine Learning). - Research experience in robotics navigation, perception, manipulation. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Ireland, Dublin Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Kubernetes Platform Engineer (Controllers) Sony Interactive Entertainment At PlayStation, we're leading the revolution in cloud gaming as we push the boundaries of what's possible! Would you like to use your skills, time, and passion for meaningful projects that are building the future? We're looking for a Platform Engineer who enjoys building Kubernetes-native systems and automation that operate reliably at global scale. If you're passionate about software engineering, Kubernetes, and solving challenging distributed systems problems, we'd love to hear from you. Come help us deliver a unique gaming experience to millions of players around the world. Responsibilities Design and develop Kubernetes controllers and operators that automate the lifecycle of platform services. Contribute to the development of our global workload placement system, enabling intelligent scheduling across Kubernetes clusters running in both public cloud and on-premises data centers. Develop Kubernetes APIs and Custom Resource Definitions (CRDs) that provide clean, maintainable interfaces for platform capabilities. Build and maintain reconciliation logic that safely manages distributed system state. Develop controllers and operators that automate provisioning, configuration, upgrades, and lifecycle management of Kubernetes-based platform components deployed across hybrid cloud environments. Work closely with platform and service teams to build automation that simplifies operating large-scale distributed systems. Improve the reliability, scalability, observability, and maintainability of the platform through thoughtful engineering and continuous improvement. Investigate production issues and participate in root cause analysis to improve platform reliability. Requirements Solid understanding of Kubernetes architecture, lifecycle and core concepts, including workloads running across cloud and on-premises environments. Experience developing software in Go or another modern programming language, with an interest in Go development. Experience building software for Linux-based environments. Experience with Kubernetes development, including controllers, operators, or Kubernetes APIs. 3+ years of professional software engineering experience. Strong problem-solving skills and a desire to learn new technologies. Skills & Knowledge Understanding of Kubernetes reconciliation patterns and declarative system design; especially understanding the principals of Communicating Sequential Processes (CSP). Experience using Kubernetes in production environments. Familiarity with controller-runtime, Kubebuilder, Custom Resource Definitions (CRDs), Common Expression Language (CEL) rules, or Kubernetes API extension mechanisms. Experience building or operating distributed systems spanning public cloud and on-premises infrastructure. Familiarity with Infrastructure as Code (IaC) and GitOps workflows. Experience working with bare metal infrastructure, hybrid cloud environments, or multi-cluster Kubernetes deployments is highly desirable. Experience with Cluster API (CAPI), SIG Multicluster, Karmada, or other Kubernetes ecosystem projects is a plus. Additional Attributes Strong communication and collaboration skills. Comfortable working as part of a distributed engineering team across multiple time zones. Takes ownership of assigned work and follows through to completion. Curious, pragmatic, and eager to learn from teammates while sharing knowledge with others. Enjoys solving the unique engineering challenges of operating software across globally distributed cloud and on-premises infrastructure. Passionate about building reliable systems and improving the user experience. Contributions to open source projects, particularly within the Kubernetes or CNCF ecosystem, are a plus. Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to race, color, religion, gender, pregnancy, national origin, ancestry, citizenship, age, legally protected physical or mental disability, covered veteran status, status in the U.S. uniformed services, sexual orientation, gender identity, marital status, genetic information or membership in any other legally protected category. We strive to build an inclusive environment, empower employees and embrace diversity. We encourage everyone to apply. We sincerely appreciate the time and effort you spent in contacting us, and we thank you for your interest in PlayStation. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Espoo Workplace: Hybrid ROLE HIGHLIGHTS: - Sovereign Infrastructure Operations Engineer - Location: Espoo - Department: IT - Reports to: Head of IT - Employment type: Permanent - Workplace model: Onsite - Employment is subject to applicable security screening (incl. SUPO, where required) WHY THIS ROLE MATTERS:   As a Sovereign Infrastructure Operations Engineer, you'll take operational ownership of ICEYE's secure bare-metal infrastructure, virtualization platforms, and production Kubernetes environments, keeping the dedicated air gaped collaboration platform reliable, secure, and audit-ready under some of the strictest information security frameworks in Europe.   WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth.   ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system.   ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future.   Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. YOUR DAY-TO-DAY RESPONSIBILITIES   - Manage configuration state across physical and virtual assets using GitOps with Infrastructure as Code tools (Git/Gitlab, Ansible, Terraform, or Puppet), removing manual configuration drift in secure environments in alignment with the strict change policies of the given security controls - Maintain and support production Kubernetes clusters in restricted environments, covering upgrades, storage integration, and registry management - Administer secure platform core services (Mattermost, Nextcloud, Keycloak, OpenBao), including deployment, upgrades, and integration with local IAM and storage - Run weekly meetings (change management, vulnerability management) with stakeholders on the infrastructure side - Maintain technical security controls to satisfy Finnish Katakri, German VS-NfD, and related European frameworks (e.g. NIS2, ISO 27001), including patch management, hardening, and access control - Maintain secure infrastructure networking (VLAN isolation, mTLS, PKI) and identity integrations, in coordination with network and security teams - Execute backup and disaster recovery procedures and routine hardware maintenance across air-gapped or high-security sites   WHAT WE’RE LOOKING FOR Must haves: - 5+ years hands-on experience in Systems Administration, IT Systems Engineering, or Infrastructure Operations, with a focus on Linux environments - Practical experience running and maintaining production Kubernetes clusters - Expert-level Linux administration (Debian/Ubuntu or RHEL/Rocky), including system hardening and vulnerability patching - Practical knowledge of Katakri, VS-NfD, or equivalent European security/compliance frameworks (ISO 27001, NIS2) - Solid understanding of enterprise networking fundamentals (VLAN segmentation, firewalls, DNS/DHCP, VPN protocols, PKI) - Eligibility to obtain and maintain a high-level national security clearance in Finland   Nice to haves: - Experience with Ceph or ZFS storage systems - Experience with at least one Infrastructure as Code tool (Ansible, Terraform, or Puppet), with the ability to manage configurations - Experience with Keycloak, Vault, or internal PKI management - Familiarity with Kubernetes operations specifically in secure or air-gapped environments   APPLICATION PROCESS - TA Screen (30 mins) - Interview with Hiring Manager (30 mins) - Technical Deep-Dive Interview with Team (60 mins) - Stakeholder & Security Alignment Interview (30 mins) WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process.   OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Location: Serbia; Latvia; Lithuania; Ljubljana; Moldova; Belarus; Georgia; Kyrgyzstan; Uzbekistan; Azerbaijan; Armenia; Czech Republic; Portugal; Spain; Dubai Workplace: remote About the Team We are Quadcode, a fintech company excelling in financial brokerage activities and delivering advanced financial products to our global clientele. Our flagship product, an internal trading platform, is offered as a Software-as-a-Service (SaaS) solution to other brokers. About the role We're looking for a Linux Administrator to join our Infrastructure team, responsible for building, operating and continuously improving all of our infrastructure services — from core services to observability and private clouds. Our infrastructure supports the stable operation of a large-scale trading platform and includes 2,000+ virtual machines and 300+ physical servers, running predominantly on Ubuntu. The stack ranges from core services like LDAP, PowerDNS and NTP, to an observability stack (Prometheus, Thanos, Loki, Grafana, Jaeger) and private clouds based on OpenStack and Kubernetes, as well as services such as GitLab, Artifactory and Vault. You’ll work in a team of experienced infrastructure engineers, using Scrum and Agile practices, with two-week sprints and a strong focus on automation, reliability and continuous improvement. The position is full-time remote, with a flexible start time — anytime before 12:00 pm EET/EEST. Why this role? You’ll be part of the team responsible for the production environment behind products used by millions of users, working directly with development teams, helping them troubleshoot infrastructure-related issues and keep their services running reliably in production. It’s a good fit for an engineer who enjoys troubleshooting, automation and making infrastructure more reliable and scalable, rather than simply maintaining servers. Tasks Oversee various services and associated infrastructure components, including DNS, Gitlab, Artifactory, Vault, Loki, Prometheus etc; Perform day-to-day operational tasks such as upgrades, CVE patching, backup and restore, security scans, and monitoring; Manage and support private clouds (Openstack and Kubernetes); Design, configure, maintain and troubleshoot Linux systems across different environments, including bare metal, virtual machines and containers. Resolve incidents, provide support coverage, categorize issues, conduct post-mortems, and perform root cause analysis; Ensure environments are stable and adhere to availability SLAs; Work towards reducing operational effort; Automate repetitive operational tasks and continuously reduce manual effort; Collaborate with development teams to troubleshoot infrastructure-related issues in production; Keep infrastructure documentation and operational procedures up to date; Engage in constant upskilling to stay updated with industry best practices. Requirements 3+ years of professional experience as a Linux System Administrator, DevOps Engineer, or Site Reliability Engineer, with a focus on infrastructure. Extensive experience in designing, building, configuring, and troubleshooting Linux servers across various environments (bare metal, container, cloud); Experience with Linux server configuration, maintenance and troubleshooting in production. Understanding of process control, logging and Linux service management. Experience with infrastructure services such as Vault, Artifactory, DNS and similar platform components. Proficiency with automation tools such as Chef, Ansible, or Salt; Experience with Docker, Kubernetes and containerized environments; Experience with monitoring and log aggregation tools like Grafana, ELK, or Graylog; Experience in deploying and maintaining systems on cloud solutions such as OpenStack, VMware, Proxmox, or public cloud platforms such as AWS, GCP, Azure. Skilled in scripting languages such as Bash and Python; Familiarity with configuring various servers and databases, including Apache Tomcat, Nginx, MySQL DB, PostgreSQL, Kafka, RabbitMQ, etc; Experience with DevOps tools and CI/CD workflows. At least C1 in Russian and B1 in English. Nice to have Hands-on experience with Kubernetes, including troubleshooting workloads and cluster-related issues. Hands-on experience with OpenStack, including deployment, configuration, maintenance or troubleshooting of private cloud environments. Hands-on experience with Chef. Experience with GitLab CI/CD, Jenkins or GitHub Actions. Experience working with fintech/trading, or other high-load and mission-critical systems. We offer Full-time remote work (service provider contract). Competitive compensation (EUR). Flexible working hours. Corporate AI subscriptions (Claude, Gemini, GPT, etc.). Access to a rewards marketplace offering products and language courses, redeemable using the company’s internal currency. A strong team of engineers. Positive and friendly atmosphere. With a team of 500+ creative and tech-driven people across the globe, Quadcode is the place where ideas turn into impact, where every project is a chance to grow, innovate, and make your mark. Join us today, and let's shape the future of fintech together! Note: All applications will be treated with strict confidence. We thank all applicants for their interest, however, only those candidates selected for interviews will be contacted. #LI-JM1

Location: Singapore 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: Network Engineering Manager APAC / Network Team Lead APAC We are looking for a Staff Network Engineer / Player-Coach Team Lead to lead the growth, deployment, and operational execution of our APAC Network Infrastructure emerging team . In this role, you will combine direct people leadership with high-end technical expertise. You will lead a growing regional team of 2–5 jun/mid-to-senior network engineers , driving their professional development, cross-project prioritization across our Global Network , and overall execution aligned with global business objectives, with a priority on the APAC Region and backbone network development across EU and the US for APAC. As a hands-on technical manager, you will remain deeply embedded in engineering execution, dedicating approximately 50–70% of your time to hands-on engineering during your first year, with the role evolving naturally alongside organizational scale and regional team expansion. Crucially, this position demands a high degree of operational autonomy . Due to the timezone differences, you will serve as the primary regional networking authority, bridging global network architecture defined with our EU/EMEA/the US engineering headquarters and regional execution across APAC colocation sites, cable landings, and data centers. This position is remote within the APAC region (with preferred hubs in India, Singapore), with regular visits to regional DC facilities and our European headquarters in Amsterdam. Your responsibilities will include: Team Leadership & People Management Deploy APAC network part and BackBone. Lead, mentor, and structurally develop a regional engineering team of 2–5 jun/mid-to-senior network engineers across the APAC. Own regional task planning, backlog prioritization, change review governance, and end-to-end execution within the team. Drive and owning the Launch and Deploy process of New DataCentre and Customer in it Drive technical coaching, and personalized career roadmaps for team members. Foster a disciplined culture of radical ownership, engineering excellence, comprehensive runbook documentation, and Git-driven automation. Act as the regional net escalation point for production network incidents Global Follow-the-Sun Alignment: Co-own operational hand-off workflows and shared incident coverage with EMEA (HQ in Amsterdam) and the US network teams to guarantee seamless, round-the-clock global production network stability and customer workability. Cross-Functional Alignment & Strategic Autonomy Serve as the primary regional network owner for the next teams in APAC: datacenter operations team, site expansion teams. EU/EMEA Coordination: Actively partner with the Global Network Architecture and R&D to adapt core architectural standards (Clos fabrics, SRv6, backbone routing policies) to APAC market realities and carrier ecosystems. Autonomously drive regional connectivity delivery: partner closely with Technical Program Managers (TPMs) on submarine cable systems, cross-border DCI circuits, local Internet Exchanges (IXs), and regional transit providers. Coordinate with HWaaS, Compute, and Cloud Platform engineering teams to guarantee timely site bring-up, Day-0 Out-of-Band (OOB) readiness, and high-throughput fabric availability for production workloads. Bridge the gap between global strategic roadmaps and autonomous local incident resolution, ensuring APAC operations execute reliably during EMEA off-hours. Technical Leadership & Hands-on Work (50–60%) Full Regional Network Ownership: Own and guarantee overall network infrastructure readiness, capacity, and availability across emerging APAC network infrastructure, ensuring alignment with HQ blueprints and processes Actively contribute to the design, deployment, and operation of massive data center fabrics and backbone infrastructure. Support and participate in the evolution high-performance Ethernet-based GPU cluster interconnects. Participate in complex, high-severity troubleshooting and root-cause analysis (RCA) for critical infrastructure incidents. Oversee and contribute to network automation pipelines, tooling, and telemetry/observability development. We expect you to have: Expert-Level Technical Background: Service Provider or/and Data Center Clos networks. BGP, IS-IS, Segment Routing (SR-MPLS / SRv6), and advanced traffic balancing Ethernet switching, EVPN-VXLAN architectures, and L3 VPNs. Leadership Experience: Proven track record as a Tech Lead, Lead/Staff Engineer, or People Manager leading mid-to-senior engineering teams. Vendor Ecosystem: Juniper, Arista, Cisco, NVIDIA It will be an added bonus if you have: Hands-on experience with GPU cluster, RoCEv2/ECN or InfiniBand networks Solid understanding of Public Cloud networking models and Software-Defined Networking (SDN) overlays. Proficiency in Python or Go for infrastructure automation and production tooling within Linux environments. 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.

Location: Zurich, Switzerland 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 As a Senior Machine Learning Engineer on the Applied AI team at Nebius Token Factory, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization and model compression, speculative decoding, KV-cache optimization, inference engines, serving architecture, and benchmarking to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving quality and reliability. You will work with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions. You will evaluate model- and engine-level optimizations together with distributed inference designs, including request routing, scheduling, prefill/decode coordination, and multi-node GPU execution. Your improvements will be validated through reproducible benchmarks and safe production rollouts under real-world workloads. Your responsibilities Own optimization projects for specific model families, customer endpoints, or serving backends. Compare inference engines and recommend serving configurations suited to individual workloads. Diagnose model-quality and performance regressions during production rollouts. Improve LLM and VLM endpoint latency, throughput, memory efficiency, GPU utilization, quality, and cost per token. Deploy, configure, benchmark, and extend engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, and NVIDIA Dynamo. Develop production model-compression workflows covering quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery. Implement or integrate speculative decoding, draft-model approaches, KV-cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving. For prefill–decode disaggregation (PDD), evaluate KV-cache transfer, worker placement, and capacity balancing to determine which workloads benefit from the architecture. Design and improve LLM request routers and scheduling policies that balance worker utilization, queueing, request characteristics, and KV-cache locality while meeting latency and reliability targets. Scale dense and mixture-of-experts inference across multiple GPU nodes. Select and tune tensor, pipeline, data, and expert parallelism—including wide expert parallelism (WideEP)—with attention to hardware topology, expert load balance, and communication overhead. Build reproducible benchmark harnesses measuring TTFT, TPOT, tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token. Validate architecture choices under representative traffic and consistent GPU budgets. Collaborate with GPU kernel and platform engineers to trace bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers. Produce design documents, performance reports, rollout plans, and customer-facing technical explanations. Must-haves Strong engineering skills in Python and PyTorch. Hands-on experience deploying or optimizing LLM, VLM, or high-throughput transformer inference. Practical knowledge of at least one modern inference stack, such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or an equivalent internal system. A strong understanding of transformer inference bottlenecks involving KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving. Ability to quantify trade-offs among latency, throughput, quality, utilization, and cost. Experience designing or optimizing distributed inference system architecture, with hands-on work in one or more areas such as request routing, distributed scheduling, PDD, multi-node inference, or expert parallelism. Strong communication and collaboration skills across research, kernel, infrastructure, product, and customer teams. Nice-to-haves Experience with quantization-aware training, post-training quantization, FP8, INT8, INT4, NVFP4, MXFP4, AWQ, GPTQ, or SmoothQuant. Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or related inference acceleration methods. Experience supporting agentic workloads involving tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. Familiarity with CUDA or Triton; the role does not require kernel engineering to be the candidate’s primary specialization. Contributions to open-source projects such as vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, or KServe. Implementation experience with cache-aware request routing, PDD, or WideEP, including diagnosing communication bottlenecks and load imbalance. Familiarity with GPU communication libraries and interconnects, such as NCCL, NVLink, InfiniBand, or RoCE. 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.