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Location: Portugal ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - Developer Experience: Design and implement developer tools, SDKs, and documentation that enable users to leverage ClickHouse’s AI/ML capabilities. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Backend development experience in TypeScript or Python, with a focus on API design and service architecture - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus #LI-Remote PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Remote, Poland GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role At GitLab, our mission is simple: to enable everyone to contribute to and co-create the software that powers our world. As a Senior Backend Engineer on Tenant Controls , you'll design, implement, and evolve backend capabilities for a global platform that millions use. You'll solve problems of high scope and complexity, influence technical and product direction, and improve system quality, reliability, and performance beyond assigned feature work. Working across product, frontend, infrastructure, data, and security, you'll make pragmatic architectural trade-offs and partner with product managers and designers to deliver value to users in a remote-first, asynchronous environment. What you’ll do Design and ship moderate to complex backend features with minimal guidance, choosing between modular-monolith code, shared components, and independently operated services. Influence team objectives, technical direction, and long-range goals, partnering with product managers and designers to shape requirements around user needs. Define backend standards for style, maintainability, testing, application programming interfaces (APIs), and operational readiness, advocating for quality, security, availability, and performance. Mentor associate and intermediate engineers, remove technical blockers, and improve delivery practices through code and design reviews. Diagnose and prevent performance and reliability issues at scale, participate in incident response, and act as a technical owner where appropriate. Experiment with and integrate agentic AI into production engineering workflows, evaluate its effectiveness, and coach others on responsible use and sound judgment. What you’ll bring Strong command of backend architecture, APIs, data systems, and performance tuning in a complex product or service environment. Proficiency in modern backend languages and a deep understanding of systems programming, with the ability to learn and adapt rather than mastery of a single language. Experience designing or evolving modular backend boundaries, bounded contexts, and migration-safe architectures. Ability to lead through influence, technical judgment, and clear asynchronous written communication, connecting product needs with technical decisions and directing your own work. Experience building or operating agentic AI systems in production, including loops, tool use, and error-handling strategies that support reliability at scale, beyond prompt engineering alone. Helpful, but not required: experience with high-throughput distributed systems, concurrency or profiling; containerized production operations (such as Kubernetes); database performance (PostgreSQL, ClickHouse, schema evolution or partitioning); large-scale modular monoliths or event-driven systems; public technical communication, open source maintenance or developer-focused software as a service (SaaS). About the team You'll join Tenant Controls within Production Engineering, where we own application-level rate limiting on GitLab.com. We build the framework that defines, counts, and observes every application rate limit and migrate existing implementations onto it. Our mission is to give GitLab.com a single way to define, configure, and observe these limits, so operators can understand them during an incident and change them without a deploy. The base salary range for this role’s listed level is currently for residents of the EU, applicable in the specified country or countries only. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location and having regard to any applicable collective agreements. The base salary range does not include bonuses, equity, or benefits. Poland base salary range: 272,000zł - 408.000zł How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Москва Данные — главный рычаг качества фронтирной модели. Станьте тем, кто его держит ------------------------------------------------------------------------------ GigaChat обучает одна из крупнейших ML-команд страны. Мы знаем то же, что знают OpenAI и Anthropic: качество следующей версии модели определяют претрейн-данные. Поэтому мы ищем не «инженера по датасетам», а исследователя, который будет владеть данными как рычагом роста модели — от стратегии сбора до измеримого прироста на бенчмарках. Контур влияния короткий и прямой: ваша гипотеза → эксперимент → обучающий прогон → прирост метрик модели, которой пользуются миллионы людей. Обязанности * Вести программу экспериментов с данными. * Планировать, запускать и анализировать ablation-эксперименты: сравнивать версии смеси данных, фильтров и порядка обучения при фиксированном вычислительном бюджете. Вы автор эксперимента, а не исполнитель. * Оптимизировать смесь и порядок использования данных. * Отвечать на главный вопрос претрейна: какие данные, в какой пропорции и в каком порядке должна видеть модель. Применять интуицию scaling laws к распределению токенов. * Измерять качество данных. * Превращать расплывчатые «хорошие данные» в конкретные измеримые сигналы: классификаторы для отбора документов, насыщенных рассуждениями, кодом и знаниями. * Курировать корпус на масштабе триллионов токенов. * Проводить точную и fuzzy-дедупликацию, фильтрацию, очистку от утечек бенчмарков, html2text. * Собирать данные для agentic-pretrain. * Проводить поиск, сбор и генерацию траекторий использования инструментов, многошаговых рассуждений и взаимодействия со средой — чтобы агентные способности закладывались в модель уже на этапе претрейна, а не только в пост-обучении. * Создавать рецепты подготовки синтетических данных. * Генерировать синтетику под дефицитные способности модели (длинный контекст, рассуждения, код) — с количественной проверкой через эксперименты. * Замыкать петлю: «данные → обучение → оценка». * Развивать контур бенчмарков и сетапов экспериментов для измерений, чтобы каждое изменение данных имело измеримый ответ. Требования * Нам нужны сильные исследователи, а не исполнители. Главное — умение самостоятельно задавать правильные вопросы, проектировать эксперименты и доводить гипотезы до измеримого результата. * Опыт именно с LLM не обязателен, если у вас сильная экспериментальная практика в любой области ML — компьютерное зрение, рекомендательные системы, классический ML, наука — специфике больших языковых моделей мы научим. * Сильные основы ML и статистики, культура контролируемого эксперимента: гипотеза → дизайн → измерение → вывод. * Уверенный Python и опыт обучения моделей на PyTorch или аналогах. * Самостоятельность в исследованиях: умение вести направление от вопроса до результата, а не ждать постановки задачи. * Понимание цикла обучения LLM хотя бы на уровне теории: токенизация, scaling laws, влияние состава данных на качество. * Знакомство с распределённой обработкой данных (Spark, Dask, Airflow, Kubernetes) и открытыми data-проектами (FineWeb, OLMo, Dolma) — как минимум представление о том, как это устроено. Не обязательно закрывать все вышеперечисленные пункты. Если вы сильный экспериментатор и хотите дорасти до владения всем циклом данных фронтирной модели — давайте поговорим. Условия * Вычислительные ресурсы под ваши эксперименты. * Один из крупнейших GPU-кластеров в стране. * ablation-эксперименты — это обучающие прогоны, и вы сможете запускать их регулярно, а не «раз в квартал, если повезёт». * Претрейн с нуля, а не дообучение чужих весов. * Мы обучаем собственную модель с первого токена — это значит, что ваши решения по данным определяют фундамент модели, а не косметику поверх чужого претрейна. Сейчас мы учим модели размером 400–700B параметров, и у нас есть амбиции выйти на масштаб 1.5–2T. * Опенсорс и мировая планка. Мы выкладываем модели в открытый доступ, и наша цель — достичь мирового уровня среди опенсорс-моделей. Ваша работа будет видна всему сообществу и будет сравниваться с лучшими открытыми моделями мира. * Полная ориентация на результат. * Минимум бюрократии, максимум ответственности и свободы. Работу меряем не количеством задач, а приростом модели на бенчмарках при том же бюджете. Подтверждённая гипотеза попадает в обучение следующей модели. * Развитая инфраструктура. * Зрелый стек для работы с данными и экспериментами: S3, YTsaurus, Airflow, DataLens, GitLab CI, wandb. * Вы приходите не строить платформу с нуля, а исследовать — пайплайны, оркестрация, трекинг экспериментов и визуализация уже работают.

• Проектирование масштабируемых web-систем. • Работа с real-time data, fintech-инфраструктурой и AI.

Creating new and improving existing AI solutions Involvement in the whole process of data-driven development from analyzing product requirements to launching the feature or system to production (with the help of MLOps specialists) and improving it based on results of monitoring and feedback.

We’re looking for a Group Product Manager to lead Klaxoon — the product area responsible for Wrike’s visual collaboration strategy and the evolution of whiteboarding experiences within the broader CWM platform. Define and drive the Klaxoon strategy:

Location: AU: Sydney (45 Clarence St) Workplace: Hybrid ENGINEERING MANAGER - APPLIED AI THE ROLE AND ITS IMPACT You will lead and grow the Internal AI Accelerator team as it expands from its current core to a fully formed engineering squad. You will own the strategy, delivery, and roadmap for how Xero designs and delivers agentic AI workflows that eliminate manual toil, speed up decision-making, and generate measurable productivity gains. This means working directly with business leaders across G&A, Finance, P&C, and IT functions to co-build reusable AI patterns and governance frameworks that last. You will shape how Xero thinks about AI delivery long after your tenure, building playbooks and reference architectures that other teams can pick up and run with. What your engineers build goes into production and real people rely on it. One month you are partnering with finance, the next you are embedded in IT. You set the pace, you unblock the path, and you hold your team accountable to shipping. THE TEAM AND HOW THEY CONNECT The Internal AI Accelerator team is a small, high-impact crew of engineers embedded across Xero's business units. They partner directly with product, engineering, and business teams to design and ship AI workflows in weeks, not months. The team operates with a direct line to senior stakeholders and a genuine mandate to move fast. Together, you are genuinely curious about what works and what doesn't, learning openly from every project and sharing what you discover. THE TEAM IS CURRENTLY WORKING ON The team is expanding from a proof-of-concept phase into building at scale. You will focus on growing the engineering capability across multiple workstreams. Initially, your priorities will be: - Scaling agentic AI delivery across multiple business domains (finance, HR, support, operations) - Building reusable patterns, platforms, and governance frameworks that other teams can adopt - Designing and implementing the technical architecture for enterprise AI deployments - Establishing best practices for AI safety, evaluation, and operations at scale WHERE AND HOW YOU CAN WORK This role is based in Sydney. You will work in a hybrid model with core collaboration days in the office. Xero supports flexible ways of working, and regular "boost days" bring our ANZ teams together for connection and planning. HERE ARE SOME OF THE THINGS WE ARE LOOKING FOR - You bring solid engineering credibility, ideally from shipping production software at scale, so you can make sound technical decisions and earn your team's respect without needing to code day-to-day. - Your approach to strategy is pragmatic: you can move fast without all the answers, turning vague problems into clear scope, and pivoting when the situation changes. - You will Go Bold in how you lead: giving your team ownership, pushing back on processes that slow you down, and creating space for innovation alongside delivery. - You demonstrate genuine curiosity about your people and a commitment to coaching them up. You leave your team knowing more than when they joined. - You show comfort bridging technical and non-technical worlds, translating between engineers and business stakeholders without losing nuance on either side. 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: Singapore 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 team offsite: Each year, we bring your entire team together in a new location - past offsites have included Croatia, Italy and Cancún - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE We're looking for a RevOps Systems Architect to help build a modern, AI-powered revenue operations stack. This isn't a traditional Salesforce admin role. We're building a GTM tech stack where AI is a first-class citizen, automations are genuinely intelligent, and our CRM is a living system that reflects how our business actually works. You'll function as a Salesforce admin and backend developer in one. You'll own platform administration, build complex automations via Flows and Apex, and develop and maintain custom services and integrations, including Salesforce MCP servers and AI tooling that connect our CRM to the broader systems our team runs on. For larger engineering efforts, you'll work shoulder-to-shoulder with our engineering team, scoping and shipping together. In this role, you will: - Administer our Salesforce org: object model, data architecture, user configuration, and platform health. - Build and maintain automations via Salesforce Flows, Apex, and custom services that power our GTM processes end to end. - Develop and maintain Salesforce MCP servers and AI tooling that extend CRM functionality into AI-powered workflows. - Design and maintain SQL-based data pipelines that feed dashboards and revenue reporting across the org. - Translate ambiguous business problems into clean technical scope, from stakeholder conversation to implemented solution. REQUIREMENTS - Salesforce administration experience with deep familiarity across the object model, Flows, data loading tools, and platform configuration. - Strong Apex development skills: you can build, debug, and maintain custom logic, triggers, and integrations without leaning on a separate engineering team. - SQL proficiency: you can decompose ambiguous questions into answerable queries and are comfortable with complex joins, aggregations, and pipeline logic. - Systems mindset: you can hold an end-to-end process in your head, trace a field from its origin through every downstream dependency, and anticipate what breaks when something changes. - Excited by modern tooling: you're drawn to building AI-native systems and are curious about where Salesforce, MCP, and AI agents intersect. Bonus: - Familiarity with dbt or modern data transformation tooling. - Experience with BI tools such as Sigma or Looker. LOCATION This role is based in Singapore 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: 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 At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Claude is getting good at research. Given a well-posed problem, it can read the literature, write and run simulations, analyze results, and iterate on a design across physics, materials, chemistry, and engineering. But most of the hardest problems in science and engineering aren't well-posed. They live inside companies and labs with their own data, tools, constraints, and experts, and progress depends on turning all of that into work a model can actually do and check. Our Applied AI, Science & Engineering team takes Claude to the scientists and engineers working on hard problems in energy, materials, hardware design, and other physical-world fields. We build the tools  Claude needs to do real research and engineering work. Mostly that means software: the agent harnesses, integrations, evaluations, and working processes that turn a partner's problem into something Claude can make progress on and validate. We find real-world problems and test what we build through partner engagements, then feed our learnings back to our research and product teams. It's early, and the engineers who join now will shape how Claude gets applied to science and engineering. This is an engineering role first. You'll spend real time with domain experts, become the person who knows how to get Claude working in their field, and prototype quickly alongside them. Most of your time, though, goes into building and hardening the systems that make that work repeatable, not into writing recommendations or configuring someone else's product. A science or engineering background is a big plus, but what matters most is that you can earn the trust of expert researchers, turn a fuzzy problem into something concrete and checkable, and ship. Responsibilities Build the agent harnesses and research loops that let Claude carry a problem from literature review through hypothesis generation, simulation, analysis, and design iteration Connect scientific computing and simulation tools (finite element, CFD, electromagnetic, or molecular modeling codes, for example) so Claude can drive them reliably and at scale Design and build evaluations that tell us whether Claude's work is actually right, and be honest about where it isn't Sit with scientists and engineers at partner organizations to learn their problem, data, tools, and constraints, and turn open-ended questions into well-specified, verifiable tasks with clear success criteria Prototype with partners, ship pilots into their workflows, and cut anything that doesn't move the problem forward Turn what works in one engagement into shared tools, reusable components, and documented processes the next one can start from Be the technical voice on how Claude performs on science and engineering work, explaining results, limits, and tradeoffs clearly to researchers, engineering leads, and non-technical stakeholders alike Partner with our research and product teams to share where models fall short on science and engineering work, and help shape what comes next You may be a good fit if you Have 8+ years of experience building software, with strong engineering fundamentals and comfort across the stack, from data pipelines to tooling to quick interfaces Have built real systems with large language models, including agents, tool use, or evaluations Have worked on technical problems in a science or engineering field, such as physics, materials, chemistry, or electrical or mechanical engineering Have a track record of zero-to-one work in startup or startup-like environments\ Can work directly with expert users, understand their workflows deeply, and still keep the focus on building the right system rather than the one first requested Have good judgment about what can and can't be verified, and are comfortable saying a result isn't good enough yet Bring high agency, pick up new domains quickly, and hold strong opinions loosely Communicate clearly with researchers, engineers, and external partners, and care about the societal impacts of your work Strong candidates may also have An advanced degree or research experience in a physical science or engineering field Hands-on experience with scientific computing and simulation, numerical methods, or optimization Experience in industrial R&D, a national lab, or a deep-tech company in areas like energy, materials, manufacturing, or hardware Experience building alongside customers or technical partners, for example in forward-deployed, applied AI, or solutions engineering roles, ideally where you also owned the software that came out of it Experience with ML research, RL environments, or evaluation design Candidates need not have 100% of the skills listed above Formal certifications or education credentials Expertise in every scientific domain we work in Direct machine learning or AI research experience Deadline to apply: None. Applications will be reviewed on a rolling basis. 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: $405,000 — $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: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's legal team operates at the frontier of some of the most consequential legal and regulatory questions of our time — from landmark copyright matters to first-of-their-kind AI regulatory frameworks emerging across dozens of jurisdictions simultaneously. As we scale, the volume and complexity of our discovery and information governance obligations are growing rapidly. We are looking for a Discovery Technical Operations Specialist to join our Litigation and Regulatory team and help build out Anthropic's discovery operations from the ground up, support active matters, and help drive information governance maturation. This is a unique opportunity to be a part of a critical function at one of the most closely watched companies in the world. You will work hand-in-hand with our discovery leads, litigation and regulatory counsel, outside counsel, discovery vendors, and cross-functional partners such as Security and IT to manage retention, preservation, collection, and production of electronically stored information (ESI) across active matters. Beyond matter-level support and programmatic development of discovery systems and processes, you will also help execute the development of Anthropic's broader information governance program, including data classification standards and defensible disposal practices that keep pace with a rapidly scaling AI company's evolving data landscape. The right person for this role will be equal parts technical operator and operational project manager. Key responsibilities Build and operate discovery operations across the full EDRM lifecycle (preservation, collection, processing, hosting, review, and production including for novel and AI-specific data types) Support the operational design and execution of the legal hold program including custodian identification workflows, hold issuance and tracking, periodic re-notification, custodian acknowledgments, and defensible release Support and improve the discovery technology stack including RelativityOne, in-place preservation and collection tooling across Slack, Google Workspace, and internal systems, and supporting analytics and review platforms including configuration, access controls, templates, and reusable workspaces Partner with discovery team, in-house counsel, outside counsel, vendors, and internal technical teams; coordinate matter execution, status, and escalations Partner with Security, IT, and product engineering to support Anthropic's data landscape, instrument new data sources for hold and collection, and ensure each ESI source has a governed retention, hold, and disposition path Improve and support the operational layer of Anthropic's information governance program: retention schedule execution, classification rollout, defensible disposition workflows, and data-inventory maintenance in close partnership with the Discovery Lead and information governance stakeholders Integrate AI and automation into the EDRM lifecycle: generative-AI-assisted review, advanced analytics, custom Relativity applications, and agentic workflow automation for intake, hold tracking, status reporting, and internal documentation Support active litigation, government investigations, and regulatory inquiries as the operational counterpart on the matter team coordinating workstreams, managing vendor execution, and surfacing operational risk and cost trade-offs to counsel Design and build internal tools to streamline and manage critical discovery workflows (legal holds, preservation, collection, ECA, and production), and develop dashboards that report on data management trends and cross-matter discovery status Minimum qualifications Hands-on discovery experience across the full EDRM lifecycle, with demonstrated ownership of operations on complex matters in an in-house legal department, government agency, law firm, or vendor A track record of supporting complex discovery operations functions Working knowledge of major discovery platforms (Anthropic uses RelativityOne), including administration, search and analytics, AI/TAR workflows, custom application development, and AI workflows Strong understanding of the Federal Rules on discovery and evidence, ESI preservation obligations, and proportionality, with the operational fluency to translate those obligations into workflows Experience operating discovery across modern enterprise data sources Slack, Google Workspace, mobile, and engineering systems and an understanding of how to bring novel data sources under preservation and collection Strong project management instincts and a track record of running multiple concurrent matters and programs under tight deadlines, with composure and precision Demonstrated ability to communicate technical discovery and operational concepts clearly to attorneys, executives, engineers, and non-technical stakeholders Preferred qualifications 6+ years of hands-on discovery experience across the full EDRM lifecycle Experience standing up discovery operations at a young and/or fast-scaling company, particularly in the context of new kinds of ESI Experience embedding with engineering or product teams to define discovery and information governance requirements, prioritize roadmap, and ship hold-capable and collection-capable features into core enterprise tools Hands-on integration of generative AI and agentic workflows (e.g., Claude, Claude Code, or similar) into operational discovery work project tracking, status reporting, internal documentation, custom tooling, and script maintenance Technical fluency working with engineering teams and modern infrastructure APIs, cloud (AWS, GCP), data pipelines, and version control and comfort writing, reading, or maintaining small scripts where useful Experience operating information governance programs at scale including retention scheduling, data classification, defensible disposition, and data mapping across heterogeneous enterprise data sources Experience with applying AI and automation to discovery operations, including generative AI for review, agentic automation, and operational tooling for hold tracking, reporting, and documentation A collaborative, hands-on orientation, with integrity and genuine curiosity about building operational programs in a fast-moving environment 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: $170,000 — $220,000 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: Singapore Workplace: Hybrid At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 25,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America and Europe, and now expanding across Asia Pacific. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. Over the past few years, Linear has experienced incredible organic growth and has become the default tool of choice for many of the world’s best product teams. We are now layering a product-led sales motion on top of our existing self-serve business to further accelerate our ambitions and bring the magic of Linear to even more and larger companies. You’ll play an instrumental role in defining our enterprise sales motion, contribute to the future of our product, and help high-impact companies build better software. Location & work mode While Linear is a remote-first company across the US and Europe, this role in APAC is office based 2–3 days per week, as this role will be closely connected to in-person collaboration with our growing sales presence in the region. What you'll do - Become a product expert and help customers use Linear effectively; assist prospects through the trial and evaluation phase - Generate a strong pipeline and exceed quarterly targets - Stay up to date with our product offering, industry trends, competitive landscape, and market trends to continuously adapt sales strategies and approaches for maximum impact - Build relationships with key stakeholders within accounts; understand client needs deeply, align Linear’s solutions to business objectives + shape decision criteria. Effectively communicate and align our value proposition to decision-makers - Be the voice of the customer; advocate for customers by surfacing product or adoption blockers to our product team - Help build the foundation and define our enterprise sales process Requirements - 3+ years selling to the enterprise, and 7+ years in a quota-carrying sales role - Experience selling a technical product to both engineering and product leadership; bonus if you have experience selling collaboration or project management software - SaaS and startup experience; comfortable working and adapting in a fast-paced and flexible environment - Ability to understand complex client needs, craft tailored discovery, and drive sales through consultative approaches. - Strong written and verbal communication, presentation, and product demonstration skills - Highly autonomous with a bias for action. Owner’s mindset to quickly come up to speed on product, market, ICP, and unique differentiators. What we offer We're a small, focused team that cares deeply about the quality of our work and the people we do it with. Here's what you can expect: - Competitive salary and equity - Employee-friendly equity terms - Daily meal and coffee stipend on every workday - Health coverage (based on country requirements) - 5 weeks paid vacation, plus local statutory holidays - 4 months paid parental leave - Paid month off after 4 years & every 2 years thereafter - Regular team events and off-sites Learn how we think and work - A story about our mission: Read Me https://linear.app/readme - How we work: Designing remote work at Linear https://linear.app/now/designing-remote-work-at-linear - Our CEO and co-founder, Karri at 20VC: How to Grow Capital Efficiently in a World of BS Growth https://www.youtube.com/watch?v=4vqDYkuzbSM - Make an Org Chart You Want to Ship — Advice from Linear on How Heirloom Tomatoes Should Inspire Team Design https://review.firstround.com/make-an-org-chart-you-want-to-ship-advice-from-linear-on-how-heirloom-tomatoes-should-inspire-team-design/ - Building our teams: Why and how we do work trials at Linear https://linear.app/blog/why-and-how-we-do-work-trials-at-linear - A video series: Conversations on Quality https://linear.app/quality - Read about our recent Series C Fundraise https://linear.app/now/building-our-way and Giving our team liquidity https://linear.app/now/giving-our-team-liquidity-through-linear-s-first-tender-offer Linear is an equal opportunity employer. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.

Location: Singapore Workplace: Hybrid At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 25,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America and Europe, and now expanding across Asia Pacific. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. Over the past few years, Linear has experienced incredible organic growth and has become the default tool of choice for many of the world’s best product teams. We are now layering a product-led sales motion on top of our existing self-serve business to further accelerate our ambitions and bring the magic of Linear to even more and larger companies. As an Account Executive at Linear, you’ll contribute to the future of our product and help high-impact companies build better software. Location & work mode While Linear is a remote-first company across the US and Europe, this role in APAC is office based 2–3 days per week, as this role will be closely connected to in-person collaboration with our growing sales presence in the region. What you'll do - Become a product expert and help customers use Linear effectively; assist prospects through the trial and evaluation phase - Generate a strong pipeline and exceed quarterly and annual targets - Build relationships with key stakeholders within accounts - Stay up to date with our product offering, industry trends, competitive landscape, and market trends to continuously adapt sales strategies and approaches for maximum impact - Be the voice of the customer; advocate for customers by surfacing product or adoption blockers to our product team What we're looking for - 5+ years in a quota-carrying sales role - Experience selling to a technical audience; bonus if you have previous experience working with a collaboration or developer tool - SaaS and startup experience; comfortable working and adapting in a fast-paced and flexible environment - Strong written and verbal communication, presentation, and product demonstration skills - Highly autonomous with a bias for action. Owner’s mindset to quickly come up to speed on product, market, ICP, and unique differentiators What we offer We're a small, focused team that cares deeply about the quality of our work and the people we do it with. Here's what you can expect: - Competitive salary and equity - Employee-friendly equity terms - Daily meal and coffee stipend on every workday - Health coverage (based on country requirements) - 5 weeks paid vacation, plus local statutory holidays - 4 months paid parental leave - Paid month off after 4 years & every 2 years thereafter - Regular team events and off-sites Learn how we think and work - A story about our mission: Read Me https://linear.app/readme - How we work: Designing remote work at Linear https://linear.app/now/designing-remote-work-at-linear - Our CEO and co-founder, Karri at 20VC: How to Grow Capital Efficiently in a World of BS Growth https://www.youtube.com/watch?v=4vqDYkuzbSM - Make an Org Chart You Want to Ship — Advice from Linear on How Heirloom Tomatoes Should Inspire Team Design https://review.firstround.com/make-an-org-chart-you-want-to-ship-advice-from-linear-on-how-heirloom-tomatoes-should-inspire-team-design/ - Building our teams: Why and how we do work trials at Linear https://linear.app/blog/why-and-how-we-do-work-trials-at-linear - A video series: Conversations on Quality https://linear.app/quality - Read about our recent Series C Fundraise https://linear.app/now/building-our-way and Giving our team liquidity https://linear.app/now/giving-our-team-liquidity-through-linear-s-first-tender-offer Linear is an equal opportunity employer. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.

Location: San Francisco, CA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO - Run the monthly and quarterly commission cycle, from pulling data and calculating commissions to validating payouts, getting approvals and handing off to payroll. - Investigate rep questions, document what you find, recommend fixes, and clear issues quickly so reps trust their payouts. - Work with Salesforce and data owners to keep source data clean, map new fields and deal types, and find upstream problems before they turn into payout errors. - Reconcile and audit payouts against payroll, bookings and plan terms every cycle. - Model the cost and payout impact of proposed plan changes and set up new plans in the system. - Automate manual steps, tighten SLAs and build reporting on attainment, payout cost and comp effectiveness. WHAT YOU’LL BRING - 5+ years in sales compensation, commissions operations or a closely related finance/RevOps role. - A track record of managing commission cycles across multiple regions, currencies, and payroll schedules, from data collection through payout validation, approvals, and payroll handoff. - Strong analytical skills, including payout modeling, data reconciliation, and investigating discrepancies against compensation plan terms. - Experience using Salesforce to pull and review sales data for commission calculations. - Ability to configure sales compensation tools to calculate, validate, and report commission payouts. - Clear, calm communication with sellers and leaders, including during difficult payout conversations. EVEN BETTER… - Familiarity with commission accounting, including accruals, journal entries, and month-end close. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: San Francisco, CA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO You'll own the operational backbone that connects what we sell to what we bill: turning executed contracts and agent usage into accurate bookings and reports, and turning the data behind both into critical insights the business acts on. This role sits at the center of the company’s business model and works across Sales, Finance, Legal, Pricing, GTM Systems, and Agent Development. Own Order Management across the Customer Lifecycle - Own the path from signature to booking: build, verify, and book quotes across the customer lifecycle, capturing all critical commercial terms - Collaborate across GTM Operations, Finance, and Sales Compensation to ensure bookings flow accurately into all downstream systems and reporting - Leverage and spearhead order management guides and best practices, influencing policies and processes as new terms and products emerge Accelerate usage tracking and reporting - Partner with Agent Development to set up, verify, and maintain outcome-based usage tracking across agents - Run the monthly consumption reporting and billing cycle for our growing customer base, delivering key reports to the company and to the Customer - Serve as the owner for usage questions from customers, Sales, and Agent Development Support our Deal Operations and Velocity - Draft, review, and execute order forms, working with our Pricing team to align on commercial negotiation, deal forecast, and downstream operability - Partner with Sales, Legal, Pricing, and Finance across the deal lifecycle to execute deals cleanly and drive scalability over time Build the Operational Machine with us - Continuously identify repetitive processes across the order management lifecycle and collaborate across the Go-to-Market Operations team to automate and scale them - Work with Revenue Operations and GTM systems to define billing processes and policies for new products and pricing models - Ramp from running standard processes to owning complex and ambiguous scenarios WHAT YOU’LL BRING - 2–4 years in deal desk, order management, billing operations, or revenue operations at a B2B SaaS company - Experience owning an operational booking and/or billing queue end-to-end with high accuracy against monthly deadlines - Experience with CRMs (e.g., Salesforce) and a CPQ or billing system; comfortable reading a contract and translating terms into system fields - Strong attention to detail and clear written communication skills to collaborate with Sales, Finance, Legal, and customers - Ability to identify areas for improvement and build solutions using AI tooling - Based in San Francisco and able to work in-office with the team EVEN BETTER… - Experience with usage-based billing (commitments, overages, credits, true-ups) - Familiarity with Quoting and Contract Lifecycle Management tools - SQL or spreadsheet modeling skills - Exposure to sales compensation, revenue recognition, or partner and reseller billing - Experience at a high-growth company where you helped stand up a process from scratch OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

• Ведёт задачу по workflow команды: от тестирования до закрытия или возврата с комментарием. • Возвращает задачу, если по ней недостаточно информации для тестирования.

Location: San Francisco, CA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. Sierra’s Applied Research team advances the quality, speed, and cost efficiency of the models powering our agents across a wide range of tasks. Our work spans post-training open-weight models for specialized capabilities and pioneering new approaches to voice AI, turning research breakthroughs into reliable production systems. WHAT YOU’LL DO - Tackle unsolved applied AI and ML problems. Pushing the boundaries of post-training, voice AI, and long-horizon task execution, building agents that can reason, adapt, and reliably carry out complex tasks for customers. - Determine when to build specialized models and when to use externally provided frontier intelligence, balancing quality, speed, and cost to deliver customer value. - Turn ambiguous product and customer problems into well-framed machine learning problems. - Develop, fine-tune, evaluate, and deploy models that improve Sierra’s customer-facing AI agents. - Advance our post-training work, from supervised fine-tuning toward reinforcement learning and long-horizon optimization. - Build rigorous evaluations that connect model performance to real-world agent quality. - Work with large-scale, proprietary datasets spanning text and audio interactions. - Collaborate across Sierra while taking ideas from experimentation through production deployment and customer impact. WHAT YOU’LL BRING - Strong experience building and deploying production machine learning and AI systems. We welcome backgrounds across applied ML, including search, ranking, recommendations, advertising, language, and speech. - Excellent judgment in framing product problems as ML tasks and selecting the simplest & most effective approach. - Experience working deeply with data, experimentation, evaluation, and model iteration. - A practical, evidence-driven approach to ML, with strong judgement around when a problem calls for modeling and when a simpler solution will deliver the best outcome. - The ability to operate with high agency and work across the stack when needed to deliver an outcome. - Alignment with Sierra’s values, including Craftsmanship, Customer Obsession, and Competitive Intensity. - A degree in computer science, machine learning, or a related field, or equivalent professional experience. EVEN BETTER… - Experience with supervised fine-tuning or reinforcement learning. - Experience in search, ranking, recommendations, or advertising systems. - Experience training and deploying language, speech, or multimodal models. - Experience designing model evaluations tied to real-world product outcomes. - Experience working with large-scale consumer datasets or high-volume ML products. - Contributions to applied ML research or benchmarks. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: San Francisco, CA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. ABOUT THE ROLE Sierra’s AI agents depend on foundation models to reason and act in real time. The Inference team builds the systems that make those models fast, reliable, and efficient at scale. As a Software Engineer on Inference, you’ll help define Sierra’s inference architecture across both self-hosted models and third-party inference providers. You’ll work on the systems responsible for serving and routing inference, managing capacity and quota, and optimizing for latency, reliability, and cost. This is a systems-first role at the intersection of distributed infrastructure and AI. You don’t need to be an ML researcher—we’re looking for engineers who love complex systems problems and are excited to apply that expertise to one of the fastest-moving areas of AI infrastructure. WHAT YOU'LL DO - Partner with frontier labs and providers. At our scale, we rely on frontier labs, and inference providers to supply capacity, training and inference infrastructure. - Shape Sierra’s inference architecture. Design how inference traffic flows across models, infrastructure, and providers, including new serving and proxy layers as Sierra scales. - Build for low latency and high reliability. Develop systems for routing, failover, capacity management, and quota that keep inference performant and available across large-scale production workloads. - Build and operate self-hosted inference. Run models on GPU infrastructure, from building containers and operating inference engines to managing the underlying compute capacity. - Optimize inference performance. Work with the Applied Research team on techniques such as speculative decoding and serving-engine optimizations that improve latency, throughput, and cost. - Build across a hybrid inference stack. Work with both Sierra-managed infrastructure and leading inference platforms, making architectural decisions about where and how workloads should run. - Push the serving stack forward. Work closely with inference providers to tune engines and infrastructure for Sierra’s workloads. - Support the broader model lifecycle. Contribute to infrastructure that enables post-training while partnering closely with our Models and Agent Runtime teams. WHAT YOU'LL BRING - Deep systems thinking and strong distributed systems fundamentals. - Experience designing, building, and operating large-scale production systems. - Strong judgment around tradeoffs involving latency, reliability, capacity, and cost. - Experience taking ownership of complex infrastructure from architecture through production operation. - Excitement about applying systems expertise to AI infrastructure and learning quickly as the underlying technology evolves. EVEN BETTER - Experience with ML infrastructure, MLOps, or production inference systems. - Experience serving LLMs or other large models at scale. - Experience operating self-hosted inference and GPU infrastructure. - Familiarity with inference frameworks such as vLLM or SGLang. - Experience with post-training infrastructure or inference-performance optimization. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for inference performance engineers who want to make the world's most demanding AI workloads run faster and more efficiently. You'll work across the stack, from the inference engine and runtime through scheduling, serving, and routing. Along the way you'll apply techniques like prefill/decode disaggregation, speculative decoding, and KV-cache management. You'll reason from first principles about where time and memory go, find what's holding performance back, and close the gap. Your work directly impacts how fast our customers' models run and how efficiently we serve them. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM inference.   EXAMPLE INITIATIVES You'll get to work on these types of projects as an Inference Performance engineer: - Agentic Kernels in Production https://www.baseten.co/blog/agentic-kernels-in-production/ - How we built the new fastest API for GLM-5.2 https://www.baseten.co/blog/how-we-built-the-new-fastest-api-for-glm-52/ - Live draft model training for speculative decoding https://www.baseten.co/blog/live-draft-model-training-for-speculative-decoding/#eliminating-traditional-bottlenecks - Making Kimi K3 Tokenization 18x faster https://www.baseten.co/blog/making-kimi-k3-tokenization-18x-faster-for-million-token-agentic-workloads/ - The Baseten Inference Stack https://www.baseten.co/resources/guide/the-baseten-inference-stack/ - Driving model performance optimization https://www.baseten.co/blog/driving-model-performance-optimization-2024-highlights/ RESPONSIBILITIES - Implement and productionize cutting-edge inference techniques, working deep in runtime internals. That includes quantization, speculative decoding, KV-cache reuse, chunked prefill, LoRA, guided generation for structured outputs, and custom scheduling and routing algorithms. - Profile and optimize inference end to end, from kernel launch overhead and memory layout up to request scheduling, prefill/decode disaggregation, and cache-aware routing. Run cross-layer investigations, such as tracing a tail-latency regression from request timing through routing and batching down to a kernel. - Turn performance into cost savings. Improve tokens per GPU-hour, raise utilization, and give customers and internal teams clear latency/throughput/cost tradeoffs. - Bring up and tune new model architectures on new hardware quickly, often in the same week they're released. - Build benchmarking frameworks that measure real-world performance across model architectures, batch sizes, sequence lengths, and hardware configurations. - Contribute upstream to open-source inference engines (vLLM, SGLang, TensorRT-LLM), and partner closely with model, infrastructure, and customer-facing teams to ship wins.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. - Experience with one or more general-purpose programming languages, such as Python or C++. - Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching). - Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM. - Demonstrated interest and experience in LLMs. - Deep understanding of GPU architecture.   NICE TO HAVE - Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs) - Contributed to vLLM, SGLang, TensorRT-LLM, or another inference engine. - Worked on large-scale distributed serving: autoscaling, load balancing, multi-region or multi-cloud capacity. - Written or optimized GPU kernels (CUDA, Triton, CUTLASS, or similar) - Worked on quantization (FP8/FP4, AWQ, GPTQ) or speculative decoding in production. - Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).