Вакансии

Задачи: — Создание и поддержка пайплайнов сборки и деплоя (GitHub Actions). — Управление контейнерами (Docker, Nomad/K8s, Podman). — Поддержка, ремонт и масштабирование систем с фокусом на безопасность. — Настройка мониторинга (Prometheus, Grafana, ELK) и Alertmanager. — Участие в проектировании архитектуры и внедрение IaC-подходов. Требования: — От 3 лет коммерческого опыта в DevOps. — Владение Docker, Nomad/K8s, Consul, Traefik, Vault. — Уверенное владение Ansible и скриптингом (Bash, Python). — Опыт работы с MySQL и понимание twelve-factor app. — Навыки создания дашбордов в Grafana. Условия: — Работа в продукте с более чем 10 миллионами пользователей. — 28 дней отпуска + 7 дополнительных Day-off в году. — 100% оплата больничных и компенсация обучения/литературы. — Гибкий старт дня (10:00–11:00). — Комфортный офис в центре Санкт-Петербурга (м. Площадь Восстания).

О КОМПАНИИ «Арт-Финтех» — международный поставщик банковского ПО с 20-летней историей. Мы разрабатываем инновационные решения для финансового сектора. Сейчас мы ищем специалиста для развития виртуальных ассистентов и автоматизации клиентского сервиса первой линии. ОСНОВНЫЕ ЗАДАЧИ — Проектирование и внедрение ветвящихся сценариев для чат-ботов и голосовых ассистентов. — Создание блок-схем и UML-диаграмм диалоговых моделей. — Написание скриптов на JavaScript для обработки данных внутри диалога и интеграционных сценариев. — Работа с NLU-классификаторами: сбор, нормализация и предобработка обучающих выборок. — Оптимизация сценариев на основе метрик CSI/VOC/NPS и проведение A/B-тестов. — Поиск и устранение багов в текущих сценариях обслуживания. — Генерация гипотез по улучшению качества ответов ИИ-ассистентов. ТРЕБОВАНИЯ К КАНДИДАТУ — Гражданство и нахождение на территории РФ. — Высшее техническое или лингвистическое образование. — Опыт разработки чат-ботов или голосовых помощников от 1 года. — Базовое владение JavaScript или Python (опыт работы с API и интеграциями). — Опыт работы с No-Code/Low-Code платформами и понимание принципов работы NLU (intent, entity, context). — Практические навыки проектирования диалогов для автоматизации поддержки. — Системное мышление и понимание продуктовых метрик клиентского сервиса. УСЛОВИЯ — Полностью удаленный формат работы. — Стабильность в группе компаний с многолетней историей на рынке. — Работа над сложными интеграционными проектами в сфере FinTech. — Возможность применения современных LLM и инструментов ИИ.

Location: India Who We Are: Galaxy Digital Inc. (Nasdaq: GLXY) is a global leader in digital assets and data center infrastructure, growing the economy that runs on code. Galaxy delivers the onchain infrastructure that connects institutions to digital assets, including trading, advisory, asset management, staking, self-custody, and tokenization. Galaxy also develops and operates data center infrastructure to power AI and HPC workloads. Anchored by its Helios campus in Texas, Galaxy is building a multi-gigawatt pipeline of more than 5.7 GW of potential capacity, positioning it among the largest and fastest-growing data center developers in North America. The Company is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia. Additional information about Galaxy's businesses and products is available on www.galaxy.com . What We Value: We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be. Seek Excellence. Be Selective To Be Effective. Be Highly Aligned, Loosely Coupled. Disagree Transparently. Encourage Independent Decision-Making. Build Dream Teams. Who You Are: You're a hands-on engineer with several years of experience building and operating production data platforms. You're fluent in Python or Java and comfortable across the modern data stack — AWS, Kubernetes, Terraform, Kafka, and Databricks/Spark. You care about reliability and developer experience, write clean and well-tested code, and like enabling other teams to move fast on infrastructure you own. You're curious about crypto and energized by working at the intersection of finance and emerging technology. What You’ll Do: Build and maintain the tooling and infrastructure that lets data champions ship pipelines autonomously Own monitoring, alerting, and dataops practices that keep the platform reliable as it scales Operate Kafka as the message broker powering cross-team event-driven architecture Deploy, own and maintain infrastructure components (services, OSS helm charts) with Terraform and Kubernetes Run high-throughput, low-latency processing on Databricks/Spark and cloud-native services on AWS Support dbt for transformations and Airflow (or similar) for orchestration across the platform Partner with product, analytics, and infrastructure teams on design and delivery of platform improvements Troubleshoo t production issues and drive the fixes Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes. Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work. What We’re Looking For: Bachelor’s or Master’s degree in Computer Science , Engineering, or related field 5+ years building data or platform engineering systems in production Strong coding skills in Python or Java Experience operating production data platforms on AWS and supporting downstream teams who build on them Hands-on with Kubernetes and Terraform Experience running Kafka (or a similar broker) in event-driven systems Working knowledge of Databricks/Spark, dbt, and Airflow Solid grasp of data modeling, data quality, and relational and non-relational databases (e.g., Postgres, SQL Server) Comfortable with CI/CD, testing frameworks, and observability tooling Bonus Points: Experience with d ashboarding technologies Experience with streaming engine ( flink , kdb ) Full lifecycle development of a commercial system, including: requirements definition, agile planning, releasing, and production support Experience in Crypto What We Offer: Competitive base salary and discretionary bonus Competitive paid time off Hybrid Working Arrangements Company-paid health and protective benefits for employees and their eligible dependents Free coaching and counseling sessions through Headspace Generous paid Parental Leave Opportunities to learn about the Crypto industry Smart, entrepreneurial, and fun colleagues Employee Resource Groups *Benefits may vary depending on location. Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances. We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact careers@galaxy.com.

Location: United Kingdom; Moldova We need someone who understands data deeply and uses Python to wrangle it — not a platform engineer, not a pure pipeline builder, but a data specialist who's comfortable with research, investigation, and the unglamorous work of making messy energy market data actually usable. You'll spend significant time on tasks like: mapping BM units to power plants and fuel types, reconciling legacy data formats with current ones, ensuring consistency between different Elexon message types, and cleaning time-series data (outliers, gaps, overlaps). Some of this requires genuine investigation — cross-referencing sources, making judgment calls, documenting edge cases. There's no API that solves these problems for you. Python is your primary tool (Pandas, Numpy, standard libraries) to minimise manual effort, but you should be comfortable that some detective work is unavoidable. If you find satisfaction in truly understanding a dataset's structure and quirks — rather than just piping data through and hoping for the best — this role is for you. Data Mapping and Research • Map BM units from Elexon to their corresponding power plants, substations, and fuel types — combining API data, public registers, and manual research • Map substations to ETYS zones and grid supply points • Build and maintain reference/master datasets that link identifiers across disparate sources (Elexon, National Grid ESO, TEC register, etc.) • Document mappings, assumptions, and known limitations clearly for downstream users Data Reconciliation and Consistency • Reconcile legacy data formats with current formats (e.g., historical operational data stored in different schemas or granularities) • Ensure consistency between different Elexon message types — understand the market data structure well enough to know why BOALF, BOD, and DISBSAD might not perfectly align and how to handle it • Investigate discrepancies between data sources and determine authoritative values Data Cleaning and Quality • Clean time-series data: detect outliers (price spikes, meter errors), fill gaps appropriately, resolve overlapping or duplicate timestamps • Develop reusable Python-based cleaning routines that can be applied across datasets • Understand why data quality issues occur (settlement reruns, late submissions, format changes) not just patch them Pipeline Development (Supporting the Above) • Write and maintain Python data grabbers for energy market APIs • Build dbt models to transform raw data into clean, analysis-ready datasets • Orchestrate workflows via GitHub Actions • Design PostgreSQL schemas that reflect your understanding of the domain Requirements • Strong Python skills for data work — you're fluent with pandas, comfortable writing clean, testable code, and can build reusable data processing logic. This is not an Excel role. • Solid SQL skills — complex queries, window functions, CTEs in PostgreSQL • Experience with messy, real-world data — you've done reconciliation, cleaning, or mapping work before and understand it's not always automatable • Methodical and detail-oriented — you notice inconsistencies and want to understand root causes • Good documentation habits — you know that undocumented mappings and assumptions are technical debt • Self-directed — you can own ambiguous problems, do your own research, and communicate findings clearly Nice to Have • Experience with energy, utilities, or market data (any geography) • Familiarity with UK energy markets, Elexon data, or grid operations • dbt experience for transformation pipelines • Exposure to time-series data challenges (irregular timestamps, gaps, restatements) Highly Desirable — Agentic AI Coding Experience We value candidates who can build software using agentic AI coding systems. This is fundamentally different from using code completion tools or chat-based assistants. Not What We're Looking For • Platform/infrastructure engineers who prefer to stay above the data layer • People who expect clean, well-documented data as input • Those uncomfortable with research, ambiguity, or "manual" investigation work Practicalities • Remote-first with async collaboration (Slack, GitHub, documented decisions) • Core overlap with UK business hours expected (at least 4 hours daily) • Competitive compensation based on location and experience Benefits Plenty of opportunities for learning and professional growth B2b contract with a paid vacation

Location: Mexico; Colombia; South Africa; Argentina; Pakistan About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and EdTech. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor About the Company Our client is a high-ticket coaching, consulting, and implementation company working with founders and CEOs of digital marketing agencies scaling toward seven and eight figures. The business provides strategic consulting while also building acquisition systems directly for clients, including funnels, paid media infrastructure, sales systems, automation, and operational workflows. Job Summary We are hiring a Senior GoHighLevel Specialist / Technical Operations Consultant to own technical builds across client launches and internal systems. This is a hands-on role for someone with deep GoHighLevel expertise, strong automation and integration skills, and real experience building AI-powered workflows. You will build pipelines, funnels, automations, AI agents, attribution systems, and integration layers across GoHighLevel and third-party tools. This role is ideal for someone who can find problems, design clean solutions, build independently, and document everything to a high standard. Key Responsibilities Build and manage GoHighLevel accounts, pipelines, funnels, campaigns, workflows, and automations. Create workflow automations using Zapier, Make, direct webhooks, and API integrations. Build and integrate AI agents using tools such as Cassidy, Custom GPTs, OpenAI, Anthropic, n8n, LangChain, or similar platforms. Connect GoHighLevel with tools such as Stripe, Slack, Calendly, Fathom, ClickUp, and other business systems. Design clean attribution systems from ad click to booked call to closed deal. Troubleshoot technical issues across client accounts and internal systems. Identify workflow inefficiencies and proactively suggest better technical solutions. Document every build clearly through SOPs, Looms, process notes, and technical documentation. Collaborate with media buyers, account managers, technical operators, and leadership teams. Requirements 3+ years of hands-on GoHighLevel experience, including pipelines, funnels, campaigns, and automations. 3+ years of media buying or technical media operations experience. Strong experience with Zapier, Make, webhooks, APIs, and custom integrations. Experience with Meta Pixel, Conversions API, tracking, and lead-generation attribution. Direct experience building AI agents using Cassidy, Custom GPTs, OpenAI, Anthropic, n8n, LangChain, or comparable tools. Experience working with B2B digital marketing agencies or agency-side clients. Ability to read API documentation and solve technical problems independently. Coding or scripting ability in JavaScript, Python, or TypeScript is strongly preferred. Familiarity with ClickUp and Slack. Excellent written and spoken English for internal and client-facing communication. Strong SOP documentation skills. Benefits 💻 Fully Remote: Work from anywhere with international teams 🚀 Career Growth: Join companies in SaaS, MarTech, and B2B services 🤝 Peer Community: Connect with high-performing sales professionals in our network 🧭 Ongoing Support: Receive guidance from Huzzle before and after placement 💰 Tailored Compensation: Salaries vary by client and candidate preference — we’ll match you with options that fit your goals

Location: New York City, NY; San Francisco, CA; Seattle, WA 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 As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world. Responsibilities: Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through your insights and recommendations Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls –  and analyze the results in order make actionable recommendations Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes Present complex technical analyses and recommendations to both technical and non-technical stakeholders Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow You may be a good fit if you have: 7+ years of experience in data science or analytics roles Deep expertise with Python, SQL, and data visualization tools Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments Highly effective written communication and presentation skills A track record of translating complex data into clear, actionable insights for both technical and business stakeholders A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress A passion for the company’s mission of building helpful, honest, and harmless AI Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem 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: $285,000 — $380,000 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.

О ПРОЕКТЕ VADAROD расширяет команду! Мы ищем эксперта, который усилит нашу работу с данными и поможет вывести КХД на новый уровень. Если ты мастерски владеешь DBT и знаешь, как строить отказоустойчивые модели данных — нам по пути! ТВОИ КЛЮЧЕВЫЕ ВЫЗОВЫ — Transformation: Создание эффективного слоя трансформации сырых данных. — Modeling: Проектирование концептуальных, логических и физических моделей данных для КХД. — Architecture: Прямое участие в разработке архитектуры решений. — Quality: Участие в Code Review и внедрение лучших практик разработки. МЫ ЖДЕМ ОТ ТЕБЯ — Tooling: Уверенный опыт работы с DBT, CDC или Databricks. — Coding: Знание Python и умение писать/отлаживать действительно сложные SQL-запросы. — Design: Практические навыки проектирования баз данных и хранилищ (DWH). БУДЕТ ПЛЮСОМ — Опыт в финтех-домене или понимание процессов финансовых организаций. — Работа с Apache Airflow, Debezium или Greenplum.

Location: United Kingdom; Brazil; Ireland; Peru; Costa Rica; Latvia; Argentina; Romania; Cyprus; Portugal; Slovenia; Lithuania; South Africa; Czech Republic; Panama; Estonia; Canada; Hungary; Mexico; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. Kraken is building a dedicated AI Compute and Infrastructure team to power the next generation of model training, inference, evaluation, and experimentation across the exchange. This team sits within engineering leadership and owns the infrastructure layer that lets Kraken run AI workloads with control, speed, reliability, and cost discipline. The team is responsible for GPU and accelerator infrastructure, cluster operations, scheduling, model serving, observability, capacity planning, and cost-efficient compute at scale. This is the backbone that allows Kraken to train, serve, evaluate, and iterate on AI systems in-house where it matters for privacy, latency, reliability, cost, or product differentiation. You will join a small, senior, high-impact team working directly with AI/ML researchers, platform engineers, security teams, and product teams. The mandate is simple: make Kraken's AI ambitions real by building compute infrastructure that is fast, dependable, efficient, and production-grade.   THE OPPORTUNITY - Own and operate GPU and accelerator clusters used for training, inference, evaluation, and experimentation, including drivers, runtimes, kernels, device plugins, node configuration, scheduling primitives, and workload isolation. - Design infrastructure that enables Kraken teams to run models locally on GPUs where it is strategically and economically preferable, reducing unnecessary dependency on external providers and containing compute costs. - Build and improve scheduling, orchestration, placement, quota management, and utilization systems across heterogeneous accelerator environments. - Optimize inference pipelines for latency, throughput, reliability, memory efficiency, and cost using frameworks such as vLLM, Triton Inference Server, TensorRT, or equivalent serving stacks. - Partner with ML engineers and researchers to remove bottlenecks in training, evaluation, batch inference, online inference, deployment, and production debugging workflows. - Build observability for GPU utilization, memory pressure, queue depth, saturation, token throughput, request latency, failed workloads, capacity pressure, and spend. - Drive reliability, incident response, alerting, runbooks, and post-incident improvements for always-on AI compute infrastructure. - Evaluate and integrate new hardware, cloud instance families, specialized accelerators, runtimes, schedulers, and serving frameworks as the AI infrastructure landscape evolves. - Build tooling that makes GPU usage visible, accountable, and easier for internal teams to consume without needing to become infrastructure experts. - Contribute to long-term architecture decisions that balance performance, cost efficiency, scalability, operational simplicity, and production safety.   WHAT YOU BRING - 5+ years of infrastructure engineering experience, with significant time spent on GPU compute, ML infrastructure, distributed systems, high-performance computing, or large-scale production platforms. - Hands-on experience operating GPU clusters or accelerator-backed infrastructure in production or production-like environments, including scheduling, orchestration, utilization monitoring, and cost optimization. - Strong systems engineering fundamentals across Linux, networking, storage, containers, Kubernetes, distributed runtimes, and production debugging. - Experience with ML serving frameworks such as vLLM, Triton Inference Server, TensorRT, TorchServe, KServe, Ray Serve, or equivalent systems. - Proficiency in Python for infrastructure automation, tooling, debugging, integration, and operational workflows. - Practical understanding of performance tradeoffs across batching, concurrency, memory usage, GPU utilization, model size, latency, throughput, availability, and cost. - Track record of optimizing compute costs while maintaining clear performance, reliability, and availability expectations. - Experience building observable systems with useful metrics, logs, traces, dashboards, alerts, and incident workflows. - Comfortable working in high-stakes, always-on environments where uptime, throughput, correctness, and operational discipline are critical. - Clear communicator who can translate infrastructure tradeoffs for researchers, product teams, platform engineers, security stakeholders, and engineering leadership.   NICE TO HAVES - Experience at a frontier AI lab, hyperscaler, high-frequency trading firm, research platform, or high-scale ML organization. - Familiarity with custom silicon or specialized accelerators such as TPUs, AWS Trainium, Gaudi, or similar platforms. - Background in capacity planning, procurement input, reserved capacity strategy, cloud accelerator economics, or GPU fleet cost management. - Experience with distributed training frameworks such as DeepSpeed, Megatron-LM, FSDP, Ray, or equivalent systems. - Experience debugging CUDA, NCCL, kernel, driver, runtime, memory, networking, or low-level performance issues. - Experience with Rust, C++, Go, CUDA, or other systems languages used for performance-critical infrastructure. - Crypto, financial services, trading infrastructure, or security-sensitive production infrastructure experience. Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: London, UK 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 Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major cloud providers and from datacenters custom-built for Anthropic, stand up and scale the clusters behind one of the industry's largest AI compute fleets, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic's frontier AI research. Key responsibilities Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy Establish and evolve operational excellence practices (incident response, postmortem culture, on-call) Support the growth of engineers around you through technical mentorship and coaching Minimum qualifications Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure) Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform. Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium) Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems Ability to build alignment across senior stakeholders and communicate effectively at all levels Preferred qualifications 7+ years of software engineering experience, including time as a technical lead setting direction for a team Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads. Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.) Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems 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: £325,000 — £485,000 GBP 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: London, UK 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 We run one of the industry's largest AI compute fleets, spanning multiple cloud providers and datacenters, to train, research, and serve frontier AI models. Those fleets run on Kubernetes, and the Kubernetes Platform team owns the control plane that makes them work. We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure. We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow. Key responsibilities Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on Build and maintain custom controllers, operators, and CRDs Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities Collaborate with cloud providers on required features and escalations Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures Minimum qualifications Significant software engineering experience building and operating production distributed systems Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++) Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on Strong written and verbal communication; comfort building consensus with internal stakeholders Preferred qualifications Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents) Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments) Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF 12+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects 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: £325,000 — £485,000 GBP 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: London, UK 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 Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world. Key responsibilities Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning Partner across teams to ensure new compute capacity is ingested on time Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity Collaborate with security owners to ensure clusters are provisioned secure-by-default Define and drive strategy on cluster scalability, homogeneity and fault tolerance Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health Support the growth of engineers around you through technical mentorship and coaching Minimum qualifications Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure) Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform. Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems Ability to build alignment across senior stakeholders and communicate effectively at all levels Preferred qualifications 10+ years of software engineering experience, including time as a technical lead setting direction for a team Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes) Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like) Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield) Experience with cluster and host networking: CNI (Cilium), eBPF, NetworkPolicy, multi-NIC, sFlow, service mesh (Istio/Envoy/Linkerd, mTLS) Experience with cluster security: pod security standards and admission control, RBAC and least-privilege IAM, node and container hardening, supply-chain/image provenance Deep experience with infrastructure-as-code (Terraform, Atlantis), workflow orchestration (Temporal, Argo Workflows) Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems 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: £325,000 — £485,000 GBP 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: Salt Lake City, Utah, United States About the Role iCapital’s Distributed Ledger Technology team is looking to hire a Senior Blockchain Backend Engineer to develop an industry-wide distributed ledger solution for the alternative investment ecosystem to facilitate access to private markets investments for advisors and their high-net-worth clients using innovative technology solutions. The ideal candidate is able to understand complex business problems, scope projects, identify business opportunities, optimize workflows, and communicate their findings across all levels of the organization. This role is highly visible and involves working closely with other teams in Engineering, Product, senior leadership, and industry partners. Responsibilities Design and implement a private and permissioned distributed ledger using DAML or Canton and other open source blockchain frameworks. Build and maintain a RESTful API using Python and FastAPI. Provide technical leadership to motivate and guide team members and mentor junior engineers. PArticipate in daily stand-up meetings and peer code reviews as part of the standard SDLC. Stay current with the latest developments in blockchain technology and incorporate them into the iCapital ecosystem. Qualifications 5+ years software engineering experience building enterprise SaaS cloud-based solutions 2+ year technical leadership and management experience Experience with DAML, Solidity, or other blockchain programing languages Experience with Python, Toke and FastAPI Demonstrated understanding of relational database concepts and modeling practices Experience building APIs for large scale applications using AWS Benefits The base salary range for this role is $120,000 to $145,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Location: European Union Workplace: Remote ABOUT THE ROLE We’re looking for a Senior Integration Engineer to take full ownership of partner integrations - from initial onboarding through to go-live and beyond. This is a delivery-focused, highly technical role where you’ll act as the key bridge between partners, commercial teams, and engineering. You won’t just coordinate - you’ll drive integrations forward, solve complex issues, and ensure partners are successfully launched.   KEY RESPONSIBILITIES - Own end-to-end partner integrations: kickoff, implementation, testing, and go-live - Drive multiple integrations in parallel, ensuring timely and high-quality delivery - Act as the main technical point of contact for partners (from engineers to C-level stakeholders) - Lead technical discussions and solution design, ensuring alignment between partner requirements and our platform - Work closely with internal teams to ensure smooth integrations and resolve technical challenges along the way - Translate partner needs into clear technical requirements and push back when needed - Collaborate closely with Commercial, Onboarding, and Engineering teams to support business goals - Ensure successful delivery and provide technical sign-off before go-live - Contribute to improving integration processes, documentation, and scalability REQUIREMENTS - 3+ years of experience in: - Integration Management - Technical Account Management - Solutions Engineering - Strong understanding of: - REST APIs, JSON, HTTP - Webhooks, idempotency, error handling - Solid understanding of networking fundamentals: - TCP/IP, DNS - Experience with API security: - API keys, OAuth, JWT - Request signing (HMAC), replay protection - Hands-on experience with: - Logs and monitoring tools (ELK, Kibana, Grafana, or similar) - Ability to review, understand, and create technical documentation, including API documentation - Strong analytical thinking with the ability to identify root causes in complex systems - Excellent communication skills - comfortable working with both technical and business stakeholders - Ownership mindset - proactive, accountable, and delivery-driven NICE TO HAVE - Experience in iGaming, fintech, or SaaS environments - Experience working with aggregators or platform integrations - Exposure to high-scale environments with multiple concurrent integrations - Experience handling partner negotiations or technical discussions at a senior level - Experience writing scripts or working with a programming language (e.g. Python, JavaScript, Bash) - Leadership potential (opportunity to grow into a lead role) WHAT WE OFFER - Competitive Salary - Quarterly Bonuses - Unlimited Paid Time Off - Unlimited Paid Sick Leave - Remote & Flexible Working - Private Medical Insurance - Financial Support for Life Events - Professional Development Budget - International Exposure - Regular Company Events *Benefits may vary depending on location and contractual agreement RECRUITMENT PROCESS 1. HR Interview (45 minutes) 2. Technical & Hiring Manager Interview (90 minutes) 3. Final Interview with C-level (60 mins) By submitting your application, you acknowledge that your personal data will be processed in accordance with our Privacy Policy https://playson.com/privacy.

Location: Colombia; Brazil; Argentina Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. What you will do - Deliver end-to-end data science projects using classical machine learning (e.g., regression, classification, time series forecasting) and deep learning approaches — from data exploration and modeling to deployment and performance tracking. - Collaborate closely with business stakeholders to identify opportunities and translate them into measurable data-driven solutions. - Present complex analytical findings in a clear, actionable way to both technical and non-technical audiences. - Contribute to analytical planning and ensure alignment with overall business objectives. - Support presales activities by preparing data/ML solution concepts, participating in client meetings, and estimating project scope and potential value. - Help shape the Data Science practice by contributing to its strategic development and supporting recruitment initiatives. What you bring - Proven experience as a Data Scientist delivering end-to-end projects — from exploratory data analysis to model deployment, performance evaluation, and experimentation (e.g., A/B testing). - Strong expertise in working with tabular and time-series data, including EDA, feature engineering, predictive modeling, and model evaluation. - Proficiency in Python and common data-science libraries (e.g., pandas, scikit-learn, TensorFlow/PyTorch). - Experience leading or mentoring analytics teams and coordinating with business stakeholders. - Excellent communication skills, able to translate between technical and business perspectives effectively. - Solid understanding of business processes and data structures. - Confidence in client-facing settings: gathering requirements, shaping analytical roadmaps, and delivering measurable business value. - Fluency in English for meetings with international clients. Nice to have - Hands-on experience with deep learning, computer vision, or generative AI projects. - Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps tools. - Experience with data visualization or BI tools for communicating insights. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: San Francisco, CA | New York City, NY | Seattle, WA 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 We run one of the industry's largest AI compute fleets, spanning multiple cloud providers and datacenters, to train, research, and serve frontier AI models. Those fleets run on Kubernetes, and the Kubernetes Platform team owns the control plane that makes them work. We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure. We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow. Key responsibilities Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on Build and maintain custom controllers, operators, and CRDs Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities Collaborate with cloud providers on required features and escalations Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures Minimum qualifications Significant software engineering experience building and operating production distributed systems Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++) Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on Strong written and verbal communication; comfort building consensus with internal stakeholders Preferred qualifications Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents) Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments) Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF 10+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects 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: AU: Sydney (45 Clarence St) Workplace: Hybrid The role / impact As a Senior Engineer within the Internal AI Accelerator Squad, you will be at the forefront of Xero’s transformation into an AI-native company. You will act as a forward-deployed engineer, embedding yourself within various internal business teams to co-design and operationalise agentic AI workflows that remove manual toil and fundamentally reshape how our people work end-to-end. Your impact extends beyond the code; you will lead the delivery of high-stakes AI agents from discovery to production, while acting as a technical partner and evangelist. By defining the patterns, guardrails, and tooling for intelligent automation, you will create the blueprint that enables the rest of Xero to harness the power of AI safely and effectively. The team / how they connect You will join a dedicated, high-velocity squad focused on boosting the adoption of agentic AI and intelligent automation across the global business. The team connects through a shared mission of rapid experimentation and "vibe-coding," working closely with product owners and SMEs to turn complex, messy workflows into elegant, automated solutions. The team is currently working on / Initially, you will focus on - Designing and iterating on AI agents and workflow orchestrations using tools like Claude, Gemini, and MCP. - Integrating AI systems with core enterprise platforms including Salesforce, Workday, Slack, and NetSuite. - Developing reusable automation patterns and shared templates to be used by the business - Building evaluation and monitoring frameworks to measure performance and ensure the safety of AI-native workflows. Where and how you can work At Xero, we embrace a hybrid way of working that prioritises both flexibility and meaningful connection. You will have the autonomy to work from home, supported by regular boost days in our modern office spaces designed to foster collaboration, brainstorming, and team bonding. Here are some of the things we are looking for - You bring a wealth of experience in building and operating applications or automations within production environments, particularly involving APIs and cloud infrastructure. - Your background includes hands-on delivery of AI-driven solutions such as agents, copilots, or RAG systems using LLMs like Claude or Gemini. - You possess proficiency in programming languages such as Python or TypeScript and feel comfortable navigating SDKs and webhooks. - A systems-thinking approach is part of your toolkit, allowing you to design agents with security, auditability, and controlled blast radius at the forefront. - You have a track record of partnering with non-technical stakeholders to translate business pain points into technical solution designs. - You are a natural coach who enjoys uplifting the AI fluency of those around you through pairing, workshops, and clear communication. Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: United States; New York; San Francisco Workplace: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy. - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE As a Solutions Engineer, you'll work as part of a driven team to unlock the full potential of our voice AI platform for a growing customer base. Your mission is to efficiently scale our technical solutions to many enterprise customers, both directly and by improving our internal processes and supporting our sales teams. As a Solutions Engineer, you can expect to: - Collaborate strategically with Account Executives to enhance the technical aspects of the sales process. - Work directly with technical contacts from our customers and prospective customers to provide bespoke support and architect solutions. - Craft compelling technical demonstrations that clearly communicate our product's value proposition. - Create technical enablement resources that amplify our sales team's effectiveness and technical fluency. - Build self-service tools and documentation that empower customers to implement solutions independently. - Identify opportunities to productize common integration patterns or features, and work with our product teams to make these real! REQUIREMENTS We're looking for exceptional individuals who excel at working with customers on technical problems and excited to work with us to scale this efficiently. You'll thrive with us if you: - Are passionate about AI, technology and ElevenLabs products. - Enjoy working directly with customers, iterating on solutions and providing tailored support - Have a talent for identifying patterns that can be standardized and scaled. - Have strong empathy for customers, sales and product teams. - Have a strong technical background in order to help customers architect integration between our solutions and their existing solutions - Experience working with customers. It’s ok if you only worked with customers in student clubs or side projects, as long as you are interested in working closely with them on a technical capacity - Proficiency in Python, inclusive of a deep understanding of software development, software architecture, and common integration patterns. - Excellent communication skills with the ability to adapt messaging to different audiences. LOCATION This role is remote-first, so it can be executed from anywhere in the United States. There is a preference for candidates to be based in New York or San Francisco, with the option to work out of our office. Expect regular travel for customer onsites. #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Location: Montreal, Canada; United States; United Kingdom The company provides full relocation support, including immigration assistance, and offers a relocation bonus upon arrival in Montreal. Selected candidates may work remotely during the initial months while their immigration process is being completed; however, the long-term expectation is for the individual to transition to onsite work in Montreal once relocation has been finalized. Role: As part of the System Engineering Department, the Senior Mission and Operations Satellite System Engineer will participate, and coordinate the work needed for the analysis, planning and definition of the constellation operations ConOps, and the preparations, testing and execution of the operations procedures. Tasks: The Satellite Flight-Operations engineer will perform and participate in the following tasks and activities, depending on the background and experience of the candidate. Trade-off studies to design, develop and simulate the overall Satellite LEOP plan. Development of Spacecraft In-Orbit Operations Procedures and oversight of their execution and associated trainings. Development of Satellite Operation Manuals, test procedures and oversight of their execution and associated trainings. Verification & Validation Matrices of the operations procedures for on-orbit commissioning, routine, and contingency operations of the mission. Support In-Orbit Test (IOT), anomaly resolution + FDIR. Support the ICD development activities both HW and SW/DB Support the Operations DevOps environment and tool-chain integration. Support the ConOps Mission Design, Trade Space Analysis, Modeling and Automation Support the Satellite Simulator Operation and script development. Must haves Bachelor’s degree in engineering in a relevant field At least 10 years of relevant practical experience Previous mission design and analyses experience with LEO/MEO satellite systems. Experience with automated satellite operations, especially design. Systems Engineering experience in concepts of space and ground segment design, specification and integration, knowledge of Flight Software role in operations, Satellite Database Operations concept and telemetry structure concepts. Experience creating or using models and/or simulation software. Knowledge of Python or other scripting languages Knowledge of Matlab Knowledge of AG1's Systems Tool Kit (STK) Complementary skills/knowledge Previous experience in Constellation Operations Development and testing of new automated operations Knowledge of MS Excel, for the purposes of engineering analyses Knowledge of requirements Management tools such as DOORS/Windchill/Jama Demonstrated capability to efficiently work with little to no supervision Strong written and verbal communications skills in English, knowledge of French will be considered favorably