О компании: " •••••••••• " — агентство, специализирующееся на сложных интерактивных digital‑проектах, UI/UX мирового уровня и веб‑разработке.
Роль: QA Engineer (Middle)
Обязанности:
— Ручное тестирование frontend и backend
— Разработка и актуализация тестерской документации
— Регрессионное и исследовательское тестирование
— Документирование багов в баг‑трекинговой системе
— Взаимодействие с командой тестирования, разработки, лидом и аналитиком
Требования:
— Умение аргументированно отстаивать качество продукта и предлагать улучшения
— Гибкость и умение адаптироваться к изменениям требований и процессов
— Уверенное знание специфики и опыт работы с JSON
— Глубокие навыки тестирования API (REST)
— Понимание сетевых протоколов HTTP и инструментов работы с ними
— Опыт работы с логами (Grafana, Kibana, Sentry)
Условия:
— Офис в Белграде или удалённая работа
— Гибкое начало рабочего дня
— Бесплатные корпоративные завтраки и обеды
— Рабочее место оборудовано современной техникой
— Отсутствие бюрократии
— Компенсация 50% оплаты занятий по английскому языку
Задачи:
— Разрабатывать и поддерживать модули Terraform/OpenTofu для vSphere VM provisioning, настройки размещения и resource-pool, интеграции cloud-init/cloudbase-init согласно дизайнам VMware Architect.
— Создавать и запускать Ansible playbooks для пост-провиженинга конфигурации на VMware VM.
— Обеспечивать модули VMware DRS (правила affinity/anti-affinity, resource pools) и vSAN (storage policy).
— Помогать в создании и тестировании модулей SRM (protection groups, recovery plans) и HCX (site pairing, network extension), включая тестирование отказоустойчивости.
— Сотрудничать с Network Architect по реализации NSX-T сегментов и правил DFW для VMware нагрузок.
— Диагностировать и решать производственные проблемы в VMware automation модулях на этапах внедрения и адаптации.
— Участвовать в тестировании модулей и документации согласно стандартам платформы Infrastructure as Code Engine.
Требования:
— Опыт 3+ лет в разработке и эксплуатации VMware automation.
— Экспертные знания vSphere, DRS и vSAN через Terraform/OpenTofu и Ansible.
— Опыт тестирования VMware, включая paired-site и failover тесты для HCX/SRM.
— Знания NSX-T сетевой сегментации и распределённого файрвола (DFW) для взаимодействия с Network Architect.
— Навыки настройки Windows guest (cloudbase-init) и Linux cloud-init.
— Профессионализм в Terraform (IaC) и Ansible (CaC) разработке.
— Умение работать с AI-поддержкой через GitHub Copilot.
— Свободное владение английским языком на уровне B2 и выше.
Желательно:
— Опыт интеграции VMware provisioning с golden-image pipelines.
— Знания Microsoft Azure.
Условия:
— Полная занятость.
— Удалённая работа.
Role Summary:
We are seeking a skilled Electrical Engineer as an independent contract worker to support the design and coordination of cutting-edge data center projects across the U.S. Responsibilities include modeling, designing power distribution, security and life systems, standby generators and UPS systems, performing calculations, preparing technical documentation, and ensuring design accuracy using advanced BIM and electrical engineering tools. Collaboration with other disciplines throughout the full project lifecycle from schematic design through execution is required. Strong technical knowledge, attention to detail, and excellent communication skills are essential.
Key Responsibilities:
— Use BIM tools to virtually construct electrical systems and coordinate with other disciplines using tools such as Autodesk Revit (mandatory).
— Develop a thorough understanding and delivery of project requirements related to scope, cost, and schedule.
— Determine and expedite engineering deliverables for projects.
— Develop and maintain project scope of work documentation and revisions during design evolution.
— Design electrical systems including power distribution, UPS, standby generators, and security and life systems.
— Prepare engineering calculations, schematic and detailed designs.
— Prepare technical documentation including design criteria, calculations, process flow sheets, and specification/data sheets for electrical equipment.
— Review shop drawings.
— Produce models and drawings in various BIM software and CAD modeling tools.
Qualifications & Experience:
— Bachelor’s or master’s degree in engineering.
— Proven expertise as an electrical engineer.
— Written and spoken English at B1 level or higher.
— Experience in electrical design for industrial, residential, and commercial sectors, including medium and low voltage distribution, lighting, grounding, and lightning protection.
— Experience with various electrical modeling software.
— Hands-on experience with Autodesk Revit (mandatory).
— Experience working on projects in multidisciplinary environments.
— Deep knowledge of electrical manufacturing processes.
— Understanding of electrical engineering codes and safety standards.
— Proficiency in Microsoft Office (Word, Excel, Outlook).
— Ability to multitask and prioritize to meet project deadlines.
— Self-starter, ambitious, thriving in fast-paced environments.
— Ability to communicate technical knowledge clearly.
— Excellent communication skills.
What We Offer:
— Experience in a high-tech industry working for an international company.
— Unique, cutting-edge data center projects.
— Dynamic work partnering with a professional engineering team.
— Competitive hourly rate.
— Ability to collaborate remotely.
— Supportive dynamic environment.
— English classes available.
Additional Information:
— Engagement is on a long-term independent contractor basis with a US-based company.
— Not limited to a single project; involves continuous collaboration across multiple mission-critical projects.
— Ehvert Mission Critical is a business unit within Salas O’Brien, specializing in data center design and construction management.
— Projects include hyperscale and AI data centers for global tech giants such as Microsoft, Oracle, Uber, and Amazon.
— Use of advanced technologies such as BIM, Virtual Design and Construction (VDC), digital twins, and augmented reality.
Location:
— Based in Tirana, Albania with remote work format.
How to Apply:
— Submit resume in English detailing relevant experience via the provided application URL.
Location: Hybrid - EMEA
About the Job:
We are looking for a talented Senior Solutions Engineer at LaunchDarkly, you will be a trusted technical advisor to our largest and most important Enterprise prospects and customers. This role is a critical part of the Enterprise sales strategy at LaunchDarkly, serving as a trusted technical advisor to sales working to both land new customers and expand existing customers. The ideal candidate will have deep expertise in supporting multiple verticals. An ideal candidate is curious, excels in active listening, quickly and effectively builds custom demos and solutions, and demonstrates profound technical expertise with a customer-centric focus.
Responsibilities:
Drive technical discovery, architecture design, and PoC implementation throughout the pre-sales lifecycle.
Partner with Account Executives and Customer Success Managers to craft compelling technical value propositions.
Deliver high-impact demonstrations, workshops, and proposals tailored to C-level and technical stakeholders.
Cultivate trust and credibility with customers, identifying technical champions and positioning as a strategic advisor.
Liaise between customers and internal Product and Engineering teams to relay feedback and influence product roadmap.
Lead cross-regional technical initiatives and enhance SE tools, processes, and frameworks for global scalability.
Mentor junior team members, foster technical excellence, and share industry best practices across the SE team.
Maintain expert-level knowledge of LaunchDarkly’s platform, integrations, industry trends, and emerging technologies.
Respond to RFPs, and manage technical environments to support enterprise sales motions.
Translate complex client requirements into scalable, sustainable, and technically sound solutions.
Represent LaunchDarkly at industry events and customer engagements through travel as needed.
Qualifications:
8+ years of experience in a solutions engineering, sales engineering, or systems architecture customer-facing role.
Experience in areas such as the SDLC, cloud architecture, or DevOps.
Extensive knowledge of cloud platforms, expertise in at least one (e.g., AWS, Azure & Google Cloud).
Demonstrated excellence in leading & documenting a proof of concept and building technical & deal champions.
Excellent communication and presentation skills. Demonstrated history of presenting thought leadership to the broader industry.
Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field (or equivalent experience).
Experience with security and compliance frameworks PII, PCI, HIPAA, is a bonus
Travel & On-Site Engagement:
Up to 35% travel, primarily across EMEA, for customer workshops, deal closings, and industry events
About LaunchDarkly:
Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations.
The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by:
Improving the velocity and stability of software releases, without the fear of end customer outages
Delivering targeted experiences by easily personalizing features to customer cohorts
Maximizing the business impact of every feature through the ability to experiment and optimize
Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types
Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability
At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status.
Do you need a disability accommodation?
Fill out this
accommodations request form
and someone from our People Operations team will contact you for assistance.
Your safety matters to us.
To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @
launchdarkly.com
email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains. Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit
Careers | LaunchDarkly
directly for confirmed job openings and links to apply.
Please notify us of any fraudulent representation by sending an email to
careers@launchdarkly.com
.
Задачи:
— поддерживать и развивать инфраструктуру продукта на Linux;
— обеспечивать стабильную работу серверов, прокси и CDN;
— обеспечивать доступность продукта для пользователей из разных стран;
— автоматизировать инфраструктурные процессы и развивать CI/CD;
— развивать мониторинг и участвовать в расследовании инцидентов;
— участвовать в разработке внутренних инструментов.
Инфраструктура:
Ubuntu, Nginx, GitHub Actions, MongoDB, ClickHouse, Grafana, выделенные серверы.
Настройка инфраструктуры с нуля, деплой напрямую на сервер.
Требования:
— уверенное знание Linux;
— работа с bare-metal (must have);
— опыт эксплуатации production-инфраструктуры;
— опыт работы с Nginx;
— опыт автоматизации рутинных задач;
— умение самостоятельно находить причины сложных технических проблем.
Будет большим плюсом:
MongoDB, ClickHouse, Prometheus, Grafana;
GitHub Actions или другие CI/CD-системы;
Docker;
Python или Bash.
Условия:
— оформление по ТК РФ;
— офис / гибрид / полная удалёнка;
— ДМС со стоматологией;
— всё необходимое оборудование;
— компенсация профессионального развития;
— компенсация изучения английского языка;
— ЗП: ориентируюсь на 200-220к RUB
Location: San Francisco, CA | New York City, NY
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The Account Abuse team is tasked with ensuring Anthropic's computing capacity is allocated fairly, minimizing resources available to bad actors and preventing them from coming back. As a software engineer on this team, you will build the machine learning systems that help us detect and stop abuse at scale. The ideal candidate can see things from opponents' perspectives, understand their means and motives, and anticipate their responses to countermeasures.
We're looking for full stack machine learning engineers with experience across model training, productionization, and evaluation. You'll also look for ways to use Claude to speed up how these models get built and maintained.
This is classical ML on structured and behavioral data. You do not need a deep learning background or knowledge of LLM internals. What matters is that you have trained and shipped models where the stakes are real, and that you care about building robust production systems as much as the model itself. A false positive here is a legitimate customer locked out, so measurement, precision, and safe rollout are part of the job.
Key responsibilities
Build and operate a feature computation platform that serves both model training and real-time scoring, with point-in-time correct training data and low-latency online retrieval
Train, evaluate, and deploy models that detect account-level abuse and fraud, running them both offline and online
Build tooling that automates more of the model development lifecycle, including using Claude to speed up feature development, training, and evaluation
Make backtesting, shadow deployment, and staged rollout the default path to production, with monitoring for training / serving skew, drift, and adversarial adaptation
Work with our data scientists and our Policy & Enforcement team to improve label coverage and quality
Partner with product and platform teams to gather signals and integrate model decisions with minimal impact on their systems' latency, stability, or overall architecture
Minimum qualifications
Proficiency in Python and SQL
Experience training machine learning models and deploying them to production
Experience building data pipelines with a batch processing engine (e.g., Spark, Beam) and a workflow scheduler (e.g., Airflow)
Working understanding of point-in-time correctness and training / serving skew, and how to prevent both
Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders
Preferred qualifications
Experience building or operating a feature platform such as Chronon, Feast, or Tecton
Experience with stream processing engines such as Flink, Beam / Dataflow, or Kafka Streams
Experience training ML models in a production setting with demanding serving requirements, such as fraud, risk, or ranking
Experience with tree-based models on tabular data
Experience building unsupervised, clustering-based or graph-based detection systems to surface coordinated account abuse
Experience in integrity, spam, fraud, or abuse detection
Experience working with scarce, delayed, or noisy labels
Experience with AutoML or other approaches to automating the ML workflow
Care about the societal impacts of AI and want your work to make powerful systems safer
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: 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
The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.
Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale.
Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.
Key responsibilities
Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps
Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region
Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads
Minimum qualifications
Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
Are curious about LLM serving; prior inference or ML experience is not required
Thrive in cross-functional collaboration with both internal teams and external partners
Have experience working with external partners to align goals and deliver impact
Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description
Preferred qualifications
Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
Solid understanding of multi-region deployments, geographic routing, and global traffic management
Proficiency in Python or Rust
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: 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
The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.
Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.
This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.
Key responsibilities
Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability
Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads
Minimum qualifications
Have a strong interest in LLM serving; prior inference or ML experience is not required
Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
Thrive in cross-functional collaboration with both internal teams and external partners
Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description
Preferred qualifications
LLM inference optimization, batching, and caching strategies
Capacity-constrained scheduling or shared-resource test infrastructure
Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
Proficiency in Python or Rust
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: 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
Our Inference team is responsible for building and scaling 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 reliably 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.
Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems.
Key responsibilities
Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
Develop resilient, flexible systems that adapt in real time to real world events
Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers
Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers
Build and operate production-grade deployment pipelines for releasing new models to users
Provide high-performance inference infrastructure that enables researchers to develop next-generation models
Integrate new AI accelerator platforms and support inference for new model architectures
Minimum qualifications
Significant software engineering experience, particularly with distributed systems
Results-oriented, with a bias towards flexibility and impact
Willingness to pick up slack, even if it goes outside your job description
Desire 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
Preferred qualifications
Experience with high-performance, large-scale distributed systems
Experience implementing and deploying machine learning systems at scale
Experience with load balancing, request routing, or traffic management systems
Familiarity with LLM inference optimization, batching, and caching strategies
Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure)
Proficiency in Python or Rust
Representative projects
Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments
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 reliably
Contributing to new inference features
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
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Компания Vinted, ведущая онлайн-платформа для торговли одеждой секонд-хенд в Европе, ищет опытного Senior Backend Engineer для команды Member Acquisition. В работе используются технологии Golang, Ruby on Rails, MySQL, Memcached, Elasticsearch, а также инструменты GitHub, Grafana и Kibana. Формат работы гибридный, с возможностью работать в офисах в Каунасе или Вильнюсе, Литва. Основные задачи включают разработку и поддержку серверной части, оптимизацию процессов привлечения пользователей и обеспечение стабильности сервисов.
Location: Remote - Singapore
Who we are
At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to
hundreds of thousands of businesses
and empower millions of developers worldwide to craft personalized customer experiences.
Our dedication to
remote-first work
, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.
.
Hiring and how we work
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings.
.
See yourself at Twilio
Join the team as our next Solutions Engineer for our Twilio Communications APJ team.
About the job
The Twilio Solutions Engineer is both highly technical and a skilled executive relationship builder. They are comfortable showing an engaging communications experience to a CEO or sketching out a flow on a whiteboard with technical decision makers.
This role sits at the intersection of communications, AI, and experience design. You will help customers across APJ — design and build next-generation customer engagement experiences powered by Twilio’s Customer Engagement Platform. These experiences increasingly blend voice, messaging, autonomous and human-assisted agents, and intelligent workflows to create interactions that feel natural, trusted, and brand-aligned.
As a Solutions Engineer, you lead the technical and experiential win: shaping how customers think about conversations, designing intelligent flows, prototyping solutions, and translating business intent into scalable architectures. You will guide customers not just on what to build with Twilio, but how those experiences should behave when humans and AI work together.
Responsibilities
In this role, you’ll:
Discovery & Scoping: Lead client discovery sessions to identify business challenges, goals, and core value drivers.
Solution Design: Translate complex customer requirements into high-level future-state architecture and implementation roadmaps.
Product Demonstrations: Deliver customized software demos, presentations, and proof-of-concepts (POCs) for audiences ranging from front-line staff to C-level executives.
Sales Support: Address technical objections, respond to RFPs/RFIs, and partner closely with Account Executives to accelerate deal closures.
Qualifications
Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!
*Required:
Technical Knowledge:
Understanding of cloud computing, cPaaS, AI.
Soft Skills:
Exceptional public speaking, storytelling, interpersonal, and consensus-building capabilities.
Curious of technology and willingness to learn new technology
Location
This role will be remotely based in Australia/Singapore/Japan
Travel
We prioritise connection and opportunities to build relationships with our customers and each other. For this role, approximately 35% travel is anticipated to help you connect in-person in a meaningful way.
What We Offer
Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.
Twilio thinks big. Do you?
We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call
Twilio Magic
. Additionally, we empower employees to build
positive change in their communities
by supporting their volunteering and donation efforts.
So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for,
please consider other open positions.
.
Stay alert to recruitment fraud
We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @
twilio.com
email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps.
.
Twilio is proud to be an equal opportunity employer.
We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.
Location: Andorra la Vella, Andorra; Buenos Aires, Argentina; Brasilia, Brazil; Rio de Janeiro, Brazil; Barcelona, Spain; Madrid, Spain; Milano, Italy; Rome, Italy; Abu Dhabi, United Arab Emirates; London, United Kingdom; Lugano, Switzerland; Warsaw, Poland; Amsterdam, Netherlands; Lisbon, Portugal; Dublin, Ireland; Bucharest, Romania; Bangalore, India; Kuala Lumpur, Malaysia
Workplace: remote
Join Tether and Shape the Future of Digital Finance
At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance:
Our innovative product suite features the world’s most trusted stablecoin,
USDT
, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that’s just the beginning:
Tether Power:
Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data:
Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like
KEET
, our flagship app that redefines secure and private data sharing.
Tether Education
: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution
: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio.
We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios.
Responsibilities
Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint.
Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms.
Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions.
Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems.
Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch.
Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms.
A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios.
Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required.
Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency.
Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters.
Deep understanding of the math and structure behind Diffusion Models and Vision Transformers
Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.
Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:
Apply only through our official channels.
We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
Verify the recruiter’s identity.
All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
Be cautious of unusual communication methods.
We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
Double-check email addresses.
All communication from us will come from emails ending in
@
tether.to
or @
tether.io
We will never request payment or financial details.
If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.
When in doubt, feel free to reach out through our official website.
Компания Click&Boat, входящая в Boats Group, ищет Senior Engineering Manager для работы в Барселоне с гибридным форматом. В технологическом стеке используются современные версии Angular, PHP, MySQL и Symfony. Основные задачи включают руководство инженерной командой, развитие продукта аренды лодок и обеспечение высокого качества технических решений.
Location: Remote; San Francisco; New York
Workplace: Remote
Patreon is a media and community platform where over 300,000 creators give their biggest fans access to exclusive work and experiences. We offer creators a variety of ways to engage with their fans and build a lasting business including: paid memberships, free memberships, community chats, live video, and selling to fans directly with one-time purchases.
Ultimately our goal is simple: fund the creative class. And we're leaders in that space, with:
- $10 billion+ generated by creators since Patreon's inception
- 100 million+ free memberships for fans who may not be ready to pay just yet, and
- 25 million+ paid memberships on Patreon today.
We're continuing to invest heavily in building the best creator platform with the best team in the creator economy and are looking for a Security Engineer to support our mission.
This role is Fully Remote (US only), or can be based in New York or San Francisco (where it is open to those who are able to be in-office 3 days per week on a hybrid work model.)
About the Team
Patreon’s security team works to protect Patreon creators and their fans. The team deals with all facets of Patreon’s security, including application security, infrastructure security, and internal/corporate security. We’re a small but effective team. We write code to solve security problems and work closely with our partners across the engineering organization. We also understand the importance of balancing security risks against business needs. We strive for honest and effective communication and focus on pragmatically reducing risk over checking boxes. The security team is part of Patreon’s Risk Engineering org, which also includes our Safety Engineering and Identity and Access teams. Collectively, the risk org tackles a range of problems including content moderation, internal tooling, identity verification, access control, and account security.
About the Role
In this role, you’ll be a member of our Security team. You’ll split your time between contributing to security projects and responding to security investigations, vulnerabilities, or questions. The work spans application security, infrastructure security, and internal/corporate security. It includes both proactive and reactive security work. You’ll be part of an on-call rotation and help respond to security incidents and investigations. You’ll write code – both to support security work and to improve the security of the Patreon platform. You’ll work closely with other members of the security team, the wider Risk engineering org, and cross functional partners in engineering, legal, and IT. Your work will help reduce known risks and will protect the security, privacy, and trust of Patreon creators and their fans.
What you’ll need:
- You have two or more years of experience reducing security risks in the application, infrastructure, or corporate security spaces. You can create a threat model and to explain why a given risk matters and what we might do to reduce it.
- You have deeper knowledge (three or more years) in at least one security or security-adjacent domain (infrastructure security, application security, cloud security, corporate/IT security, cryptography, privacy, etc.)
- You can develop software (Python, Rust, Golang, or a similar language). You have experience working in a modern software development environment (git, CI/CD, LLM coding tools, etc.)
- You have experience using AI tools (LLMs, ML models, etc) to identify and address security issues (software vulnerabilities, detection and response, etc.)
- You’re energized by fast iteration: shipping MVPs, testing hypotheses, and evolving products based on what creators and fans respond to.
- You take pride in creating elegant solutions to messy, real-world problems and balancing pragmatic trade-offs between security risks and business needs.
- You believe in Patreon’s mission: giving creators control over their work and building communities that feel good to be in.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field, or the equivalent
Bonus if you have:
- Experience working on large scale Internet platforms that allow users to upload content.
- Past contributions to large scale, production code bases.
- Experience responding to security incidents, investigating incident impact, and building out incident mitigations.
We hire talented and passionate people from different backgrounds because workplace diversity and inclusion is critical to our ability to serve creators worldwide. If you’re excited about a role but your past experience doesn’t match with every bullet point outlined above, we strongly encourage you to apply anyway. If you’re a creator at heart, are energized by our mission, and share our company values, we’d love to hear from you.
About Patreon
Patreon powers creators to do what they love and get paid by the people who love what they do. Our team is passionate about making this mission and our core values come to life every day in our work. Through this work, our Patronauts:
- Put Creators First | They’re the reason we’re here. When creators win, we win.
- Build with Craft | We sign our name to every deliverable, just like the creators we serve.
- Make it Happen | We don’t quit. We learn and deliver.
- Win Together | We grow as individuals. We win as a team.
Patreon is proud to be an equal opportunity employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. If you need a reasonable accommodation during the interview process, please let us know via email at accommodations@patreon.
Patreon offers a competitive benefits package including and not limited to salary, equity plans, healthcare, flexible time off, company holidays and recharge days, commuter benefits, lifestyle stipends, learning and development stipends, patronage, parental leave, and 401k plan with matching.
Patreon operates under a hybrid work model, where employees based in office locations are expected to come into the office three days per week, excluding sick time and paid leave. The goal of this policy is to be intentional about the in-person time we spend together to strengthen the feeling of community at Patreon. Candidates hired into remote-eligible roles are not expected to meet the same requirements.
At Patreon, we believe in fair and transparent pay. In compliance with New York and California pay transparency laws, we are sharing the expected salary range for this role.
The posted salary range is dependent on the location and the level. This range may encompass multiple levels within the role’s job family. The final offer will be based on candidate’s experience, skills, competencies, and geographic location, aligning with the appropriate job level within Patreon’s leveling framework. For remote employees located outside CA and NY, salary may vary based on location and local market conditions.
Patreon reserves the right to modify or update compensation and benefits at any time.
Location: United States
Workplace: Remote
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
Cantina is a place where people create AI characters and the videos those characters star in, and the catalog grows far faster than anyone can browse. Search and recommendations are what turn that catalog into a product: they decide which characters a new user meets in their first minute, which creators get discovered, and what appears in every feed, leaderboard, and discovery surface we ship. We are hiring a Senior Staff Software Engineer to own that area end to end — retrieval, ranking, relevance quality, and the roadmap for all three. This is the first dedicated hire for search and recommendations, so you will inherit a real production system serving live traffic along with a large amount of unclaimed ground, and you will set the technical direction rather than execute someone else’s.
What you'll do:
- Own the architecture and roadmap for search and recommendations end to end — query understanding, retrieval, ranking, and the surfaces they feed: search, discovery, the home feed, and our trending and creator leaderboards.
- Make relevance a measured discipline rather than an opinion: define the quality metrics per surface, build the offline evaluation and golden-set tooling, and run the online experiments that decide whether a ranking change ships.
- Design and evolve the ranking stack — engagement signal pipelines, decay and freshness models, and the pattern we use to combine pre-computed index-time signals with live re-ranking at query time.
- Own OpenSearch in production: index and mapping design, reindex and cutover safety, query performance, cost, and the operational headroom of the clusters behind every discovery surface.
- Build candidate generation and personalization for recommendation surfaces, and partner with data and ML on the feature pipelines and models behind them.
- Work directly with Product and Trust & Safety on what “good” means for each surface — quality gates, cold-start behavior for brand-new creators and characters, and what must never be recommended.
- Set the engineering standard for the area: instrumentation, flag-gated rollouts, and runbooks that let other teams change ranking behavior without breaking it.
- Act as the technical point of contact for discovery across backend teams, and mentor the engineers whose work touches it.
What you'll bring:
- 10+ years building production software, with substantial depth in search, ranking, recommendations, or ML-driven relevance on a consumer-scale product.
- Hands-on expertise with a production search engine — OpenSearch, Elasticsearch, Lucene, Vespa, or similar — covering index and analyzer design, relevance tuning, and operating the cluster, not only querying it.
- A rigorous approach to relevance measurement: you have owned offline evaluation, golden sets, and A/B or interleaving frameworks, and you can explain what moved a metric and why.
- Fluency across the recommender stack — candidate generation, feature pipelines, embedding retrieval, re-ranking — and a working understanding of the serving constraints that make an offline win fail online.
- Strong distributed systems and backend fundamentals, with production experience in Go or a comparable systems language, and comfort in the data layer behind it (SQL warehouses, streaming and batch pipelines).
- Demonstrated ownership of an ambiguous area: you have picked up something with no dedicated owner, decided what mattered, and can show the result.
- Clear written communication and the judgment to work with Product on real tradeoffs between relevance, freshness, safety, and latency.
- Preferred: experience with AI-generated or rapidly growing content catalogs, severe cold-start conditions, or ranking under trust-and-safety constraints.
Compensation:
The anticipated annual base salary range for this role is between $250,000 - $320,000 (USD). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits:
- Competitive salary and generous company equity
- Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
- 42 days of paid time off, including:
- 15 PTO days
- 10 sick days
- 15 company holidays
- 2 floating holidays
- Generous parental leave & fertility support
- 401(k) retirement savings plan
- Lifestyle spending account – $500/month to use however you’d like
- Complimentary lunch and snacks for in-office employees
- One Medical membership, and more!
Location: San Francisco, California; New York, New York
Workplace: Hybrid
WHO WE ARE
Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion.
Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work.
ABOUT THE ROLE
Millions of people rely on Notion to do their most important work, and protecting that trust is foundational to everything we build.
We’re looking for a hands-on Detection Engineer to build and operate the systems and workflows we use to detect and respond to attacks across Notion’s cloud-native environment. You’ll ship high-signal detections, improve the platform that powers them, participate in incident response, and help shape how detection and response engineering scales at Notion.
You’ll work closely with Engineering, Corporate Security, and Infrastructure, with broad latitude to identify gaps, prioritize investments, and build what’s needed next.
We view detection and response as a software engineering discipline: detections are code, platforms are products, and measurement matters
WHAT YOU'LL ACHIEVE
- Build and tune high-signal detections across cloud, identity, endpoint, and SaaS environments, with review and mentorship from senior teammates as you ramp up.
- Contribute to the detection platform, including rule lifecycle management, tuning, measurement, and rollout safety.
- Build tooling and automation that speed up triage, enrichment, investigation, and detection authoring, including LLM-based workflows where useful.
- Turn threat intelligence and adversary TTPs into detections, telemetry requirements, and response improvements.
- Take part in investigations, incident response, and postmortems, and help turn what we learn into lasting fixes.
- Help define and track metrics such as coverage, MTTD, and alert quality.
- Join a shared on-call rotation for incident response.
SKILLS YOU'LL NEED TO BRING
- We're hiring across a range of experience levels. If you have some of these skills but not all, we'd still like to hear from you.
- 3+ years of experience in detection engineering, security operations, incident response, threat hunting, or a closely related security or software engineering role.
- Have written or tuned detections that run in production, and care about signal quality and cutting noise.
- Working knowledge of at least one detection or query language (Sigma, KQL, SPL, YARA-L, EQL, or Panther), or strong SQL or Python skills and the drive to learn one quickly.
- An understanding of how attackers operate (for example, MITRE ATT&CK), and the ability to use it to decide what to detect.
- Hands-on experience with AWS, GCP, or Azure, ideally including identity and access logs.
- Have used SIEM, EDR, or SOAR tools in any size of environment.
- Write clearly in runbooks, design docs, and incident notes, and can own well-scoped projects end to end.
NICE TO HAVE
- Have led purple team, blue team, or adversary emulation exercises that improved detections or telemetry.
- Experience running SIEM, EDR, or SOAR platforms at large scale.
- Experience building or maintaining detection-as-code workflows (version control, CI, and tests for detections).
- Experience applying LLMs or agent-style tooling to security workflows.
- Experience securing AI-enabled systems or endpoint tooling.
- Kubernetes or container detection experience.
- Background in threat intelligence, malware analysis, or digital forensics.
- Contributions to the security community through research, tooling, CTFs, or talks.
- Experience at a high-growth startup or AI company.
Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $185,000 - $280,000 per year.
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A NOTE ON AI
You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on.
EQUAL OPPORTUNITY & ACCOMMODATIONS
We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know.
Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.
Location: United States
Our client is hiring a SAR Payload Systems Engineer to support current and next-generation Earth-observation satellites. You will own the definition, design, integration, verification and sustainment of SAR payload subsystems across several satellite programs and act as the technical interface with customers, primes and internal teams. Fully remote from the US is now accepted.
What you will do
• Gather and trace payload requirements from mission level down to subsystem level
• Design the SAR payload architecture: antenna arrays and RF front-end Tx/Rx, digital beamforming, processing chain and digital electronics, power, thermal, mass
• Lead conceptual, preliminary and detailed design with trade studies and performance budgets; produce ICDs; specify hardware and review schematics and layouts
• Performance simulations for tolerance budgeting and image quality; support SAR and moving-target-indication algorithm development; payload DC power budget; FMECA, fault tree, FDIR, reliability
• Build the payload verification master plan (unit, subsystem, payload, environmental and EMC tests); lead test automation and reporting
• Support mission operations: payload health monitoring, on-orbit anomaly root cause, telemetry analysis, operator training
What you need
• Degree in Electrical Engineering, Computer Science or Physics with 5+ years supporting remote sensing system development, integration and test on LEO/MEO missions
• Strong technical writing (requirements, ICDs, test procedures, risk reports) and presentation skills
• Hands-on systems integration and test experience; Confluence and JIRA
• Works well with little supervision; strong written and spoken English (French an asset)
• US citizen or permanent resident
УдалённоUnited States
УдалённоTirana
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
seniorNew York City, NY; San Francisco, CA; Seattle, WA
УдалённоRemote - Singapore
УдалённоAndorra la Vella, Andorra; Buenos Aires, Argentina; Brasilia, Brazil; Rio de Janeiro, Brazil; Barcelona, Spain; Madrid, Spain; Milano, Italy; Rome, Italy; Abu Dhabi, United Arab Emirates; London, United Kingdom; Lugano, Switzerland; Warsaw, Poland; Amsterdam, Netherlands; Lisbon, Portugal; Dublin, Ireland; Bucharest, Romania; Bangalore, India; Kuala Lumpur, Malaysia
УдалённоRemote; San Francisco; New York; This role is Fully Remote (US only), or can be based in New York or San Francisco (where it is open to those who are able to be in-office 3 days per week on a hybrid work model.); For remote employees located outside CA and NY, salary may vary based on location and local market conditions
УдалённоseniorUnited States
ГибридSan Francisco, California; New York, New York
