- Страна
- Великобритания
- Зарплата
- 325 000 £ – 390 000 £
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Staff Software Engineer, Inference
Это исключительная возможность работать в авангарде ИИ-индустрии с очень высокой компенсацией. Позиция предлагает уникальное сочетание сложнейших инженерных задач, работы с передовыми моделями (Claude) и социально значимой миссии.
Сложность вакансии
Роль уровня Staff в одной из ведущих ИИ-лабораторий мира требует исключительных навыков в распределенных системах и оптимизации производительности. Кандидату предстоит решать сложнейшие задачи на стыке системного программирования и машинного обучения в условиях взрывного роста нагрузки.
Анализ зарплаты
Предложенная зарплата (£325k - £390k) значительно превышает средние рыночные показатели для Staff Engineer в Лондоне, что характерно для топовых ИИ-компаний первого эшелона. Это верхний дециль рынка даже для высоконагруженного финтеха и BigTech.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Software Engineer, Inference position at Anthropic. With extensive experience in building high-performance distributed systems and a deep fascination with the challenges of large-scale AI deployment, I am eager to contribute to the mission of making Claude accessible and reliable for millions of users worldwide. My background in optimizing request routing and managing complex orchestration across diverse hardware accelerators aligns perfectly with the technical demands of your Inference team.
Throughout my career, I have focused on maximizing compute efficiency and building production-grade pipelines that bridge the gap between breakthrough research and global scalability. I am particularly drawn to Anthropic's approach to AI as an empirical science and your commitment to safety and interpretability. I am confident that my expertise in Python, Rust, and cloud infrastructure, combined with my results-oriented mindset, will allow me to make immediate contributions to your multi-region deployments and hardware-agnostic infrastructure.
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Откликнитесь в anthropic уже сейчас
Присоединяйтесь к Anthropic, чтобы масштабировать Claude и определять будущее безопасного ИИ в одной из самых влиятельных команд индустрии!
Описание вакансии
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
Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.
As a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary.
Strong candidates may also have experience with
- High-performance, large-scale distributed systems
- Implementing and deploying machine learning systems at scale
- Load balancing, request routing, or traffic management systems
- LLM inference optimization, batching, and caching strategies
- Kubernetes and cloud infrastructure (AWS, GCP)
- Python or Rust
You may be a good fit if you
- Have significant software engineering experience, particularly with distributed systems
- Are results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Want to learn more about machine learning systems and infrastructure
- Thrive in environments where technical excellence directly drives both business results and research breakthroughs
- Care about the societal impacts of your work
Representative projects across the org
- Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
- Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
- Building production-grade deployment pipelines for releasing new models to millions of users
- Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
- Contributing to new inference features (e.g., structured sampling, prompt caching)
- Supporting inference for new model architectures
- Analyzing observability data to tune performance based on real-world production workloads
- Managing multi-region deployments and geographic routing for global customers
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:
£325,000—£390,000 GBP
Logistics
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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
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Навыки
- AWS
- Python
- Rust
- GCP
- Kubernetes
- Distributed Systems
- Machine Learning Infrastructure
- Load Balancing
- Performance Optimization
- Inference Optimization
Возможные вопросы на собеседовании
Для роли Staff важно понимать, как кандидат проектирует системы, способные обрабатывать миллионы запросов к LLM с минимальной задержкой.
Как бы вы спроектировали систему интеллектуальной маршрутизации запросов для парка из тысяч ускорителей (GPU/TPU), учитывая различные размеры моделей и приоритеты пользователей?
Anthropic использует разные облака и типы железа. Вопрос проверяет опыт работы с гетерогенными средами.
С какими основными трудностями вы сталкивались при обеспечении переносимости инференс-стека между различными семействами ускорителей и облачными провайдерами (AWS/GCP)?
Эффективность вычислений критична для маржинальности ИИ-бизнеса.
Какие стратегии батчинга (batching) и кэширования промптов вы считаете наиболее эффективными для снижения стоимости инференса без значительного ущерба для latency?
Проверка навыков отладки в масштабе всей инфраструктуры.
Опишите ваш подход к анализу данных обсервабилити для выявления узких мест в производительности распределенной системы инференса, работающей под реальной нагрузкой.
Anthropic ценит культуру 'pick up slack' и междисциплинарное взаимодействие.
Расскажите о случае, когда вам пришлось выйти за рамки своих прямых обязанностей, чтобы устранить критический блокировщик для исследовательской группы или продукта.
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- Страна
- Великобритания
- Зарплата
- 325 000 £ – 390 000 £