Вакансии

Own full-cycle recruiting for a subset of Clover's technology teams. Partner with hiring managers to understand role scope and business needs in order to build out effective job descriptions, hiring/interview plans and targeted sourcing strategies.

Задачи: — развивать стратегические отношения с промышленными клиентами — создавать дорожные карты AI-решений — вести техническую валидацию — руководить масштабируемыми внедрениями AI Работа удалённая.

Nscale is looking for a Principal Technical Product Manager Hardware and AI Infrastructure to define and deliver scalable hardware infrastructure products.

Robinhood is looking for a Senior Technical Recruiter Infrastructure to manage full-cycle hiring and build pipelines for specialized engineering roles.

Ключевые требования: опыт в платежах, финтехе или подписочных продуктах.

Задачи: — Развитие и сопровождение платежной платформы, анализ требований и внедрение нового функционала. — Интеграция мерчантов и взаимодействие с платежными провайдерами. — Настройка и поддержка платежной инфраструктуры (шлюзы, маршрутизация, каскадирование, antifraud). Требования: — Практический опыт интеграции платежных решений, работы с REST API/JSON и настройки платежной инфраструктуры. — Английский язык от B2. Условия: — Оформление по труд.договору в Сербии, страховка, техника, компенсации.

Задачи: — Полный цикл рекрутинга для технических ролей в инженерной и продуктовой командах, от поиска до предложения и закрытия вакансий — Поиск и вовлечение высококвалифицированных кандидатов в инженерные и продуктовые команды по регионам Северная Америка, Латинская Америка, Европа, Ближний Восток и Африка, Азиатско-Тихоокеанский регион — Обеспечение высокого качества взаимодействия с кандидатами, отражающего ценности и культуру компании — Тесное сотрудничество с менеджерами по найму для определения критериев и профилей успешных кандидатов — Еженедельное предоставление отчетов менеджерам по найму о прогрессе, проблемах и ключевых метриках — Организация интервью и обеспечение их гладкого проведения с учетом разных часовых поясов — Построение кадрового резерва для текущих и будущих потребностей в технических и смежных командах — Оценка соответствия кандидатов техническим требованиям, коммуникационным навыкам и успешной работе в быстро меняющейся удаленной среде — Постоянное улучшение процессов рекрутинга, инструментов и отчетности — Представление компании как продуманного и энтузиастичного бренда в каждом взаимодействии с кандидатами Требования: — Успешный опыт найма на технические позиции, включая backend, frontend, data/ML, управление продуктом и дизайн продукта — Проактивность, самостоятельность, ответственность и умение доводить дела до конца — Гибкость и отзывчивость к потребностям кандидатов, включая организацию интервью в разных часовых поясах — Опыт работы в быстрорастущих стартапах или динамичной среде — Высокий уровень удержания нанятых сотрудников и доверия со стороны команд по найму — Уверенное использование LinkedIn Recruiter и адаптация к новым инструментам — Отличная организация и внимание к деталям — Превосходные письменные и устные коммуникативные навыки, умение работать с людьми — Эмпатия, вдумчивость и ясность в общении с кандидатами и внутренними заинтересованными сторонами — Опыт работы с системами отслеживания кандидатов (ATS) — Умение использовать и совершенствовать AI-инструменты для оптимизации рекрутинга и поиска кандидатов — Возможность работать полностью удаленно с пересечением часовых поясов США и Европы (например, Португалия, Лондон, Испания) Плюсы: — Опыт работы с Ashby — Опыт работы с Juicebox Условия: — Неограниченный отпуск, рекомендуется минимум 3 недели в год — Конкурентный компенсационный пакет, включая опционы на акции — Полностью удаленная команда, возможность выбора места жительства — Стипендия на обустройство домашнего офиса — Предоставление Apple ноутбуков новым сотрудникам — Бюджет на обучение и развитие, обновляемый ежегодно — Отпуск по беременности и родам для квалифицированных сотрудников — Работа с умными людьми, способствующими профессиональному росту и значимому вкладу

Vultr is looking for a Senior Technical Writer GIOC to create operational documentation, training, knowledge-transfer materials, and readiness artifacts.

Vultr is looking for a Technical Program Manager GIOC to drive the build, delivery, and operational readiness of the command center.

- Обеспечение L2 технической поддержки в нерабочее время для корпоративных видеопотоков и рабочих процессов кодирования. - Управление жизненным циклом инцидентов от начала до конца: триаж, регистрация тикетов, глубокий анализ первопричин (RCA), внедрение обходных решений и разрешение проблем в рамках строгих SLA-целей.

Location: Stockholm ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you’ll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You’ll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You’ll own durability and cost at petabyte scale, from streaming and batch replication between origins to garbage collection over billions of objects. You’ll work across the stack, from local disk and page cache to distributed blob storage and garbage collection, and you’ll help shape what storage becomes next as we push storage closer to workloads. WHAT YOU’LL WORK ON: - Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicate data across multiple blob storage providers - Automate garbage collection across hundreds of petabytes of data - Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better) - You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - You’re willing to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVE: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte scale - Prior experience with Rust

Perplexity is looking for a Machine Learning Engineer to develop search, retrieval, LLM training, and multi-agent systems.

Perplexity is looking for a Senior QA Web Engineer to test web products, identify issues, and maintain quality across product experiences.

- Own shift and inbox performance, ensuring efficient workload distribution, timely responses, effective prioritisation, and consistent support quality. - Monitor frontline operations, review complex cases, shift handovers, unresolved issues, and recurring mistakes.

Задачи: — сопровождение и настройка интеграций с PSP — мониторинг стабильности платежной инфраструктуры — работа с инцидентами и координация их решения — взаимодействие с партнерами и внутренними командами Требования: — опыт с PSP/платежными шлюзами от 1 года — базовое понимание API, логики запросов/ответов — опыт работы с логами и технической документацией — английский B2+ Условия: — техника — компенсации (спорт, психолог, языки, обучение) — медицинская страховка.

‼️ Qo`shimcha: Unreal engine-da, complex material, shader, optimization, procedural generation qila oladigan technical artist kerak. muhi m: unreal engine ni shunchaki bilish yoki unda ishlay olishi yetarli emas!

Location: United States; Canada Workplace: OnSite WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models. Key Responsibilities - Build and maintain data pipelines for SFT, preference, and RL post-training data. - Own dataset quality, versioning, and reproducibility. - Turn research data recipes into production-grade, reusable components. - Scale model inference for data generation and model-based grading. - Design data formats and schemas that keep post-training datasets consistent and efficient to train on. - Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models. Qualifications - Strong software engineering skills. - Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training. - Track record of running distributed data processing and model inference at scale. - Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour. - Excellent communication skills. This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We value diverse backgrounds and perspectives at Cohere   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Europe; New York; Toronto Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Key Overview: As a Member of Technical Staff in Post-Training, you will train our large language models (LLMs) with reinforcement learning and develop methods that help them generalize beyond the distribution they were trained on. You will design the training recipes, environments, and evaluations that tell us whether a model has truly learned a skill or has only fitted its training tasks, and turn what works into the recipes behind our production models. You will work closely with the post-training data infrastructure, evaluation, and pre-training teams. Key Responsibilities - Design, run, and analyse large-scale RL post-training experiments (e.g., RLHF, RL from verifiable rewards). - Research and develop methods that improve out-of-distribution generalization, such as reward design, environment and task diversity, curricula, and regularization. - Build held-out evaluations that measure generalization to unseen tasks, domains, and formats, and that catch reward hacking and benchmark overfitting. - Diagnose training dynamics and failure modes, including instability, reward over-optimization, and capability regressions. - Turn successful research into robust, reproducible training recipes for production models. Qualifications - Strong research and software engineering skills, with hands-on experience training LLMs. - Experience applying reinforcement learning to LLMs (e.g., PPO, GRPO, RLHF, RLVR), ideally at scale. - Track record of work on generalization, robustness, or distribution shift, through publications or shipped models. - Rigorous experimental practice: clean ablations, careful controls, and sound conclusions from noisy results. - Experience with distributed training (e.g., JAX, PyTorch, FSDP, Megatron) is a plus. - Excellent communication skills. - Deep understanding of data quality principles and best practices: demonstrates willingness to dive deep into data while possessing strong intuition for assessing the quality of datasets and anticipating how different data characteristics will impact model training outcomes. Working Location This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.