Задачи:
— Проектировать и развивать модели компьютерного зрения и видеоаналитики (детекция, трекинг, распознавание лиц, анализ поведения);
— Интегрировать ML-модели в production (backend, edge);
— Обучать и дообучать модели (fine-tuning, transfer learning);
— Работать над реальными AI-проектами с бизнес-применением;
— Сопровождать полный цикл разработки: от исследования до деплоя;
— Оптимизировать модели и повышать качество CV-решений.
Требования:
— Уверенные знания Computer Vision и современных DL-подходов;
— Глубокое понимание машинного обучения и нейронных сетей (CNN, detection/segmentation);
— Уверенное владение Python;
— Опыт работы с OpenCV, NumPy, PyTorch и/или TensorFlow;
— Опыт работы с Git;
— Опыт оптимизации моделей (speed/accuracy trade-offs, inference);
— Опыт решения задач детекции, трекинга и анализа поведения людей.
Условия:
— Формат работы: офис, Астана.
Задачи:
- Поддержка и развитие существующих AI-модулей системы онлайн-прокторинга
- Определение отсутствия лица и нескольких лиц в кадре
- Реализация Face ID и проверки личности пользователя
- Разработка Liveness-проверки (моргание, улыбка, движения головы, контроль дистанции до камеры)
- Определение поворотов головы и направления взгляда
- Анализ положения тела и правильности посадки пользователя
- Выявление ухода пользователя из кадра и поворота от рабочей зоны
- Обнаружение посторонних людей и объектов в кадре
- Детекция смартфонов, наушников, часов и других гаджетов
- Распознавание мониторов, ноутбуков, клавиатур, мышей и других объектов рабочего места
- Определение посторонних движений и плохого освещения
- Снижение количества ложных срабатываний моделей
- Обучение, дообучение и замена AI-моделей
- Оптимизация моделей с использованием CUDA
- Интеграция AI-модулей через API
- Развертывание локальных LLM на собственных серверах
- Работа с моделями Qwen, Llama, Mistral, Gemma и другими open-source LLM
- Интеграция GPT, Claude, Gemini и других LLM через API
- Подбор и оптимизация AI-моделей под задачи продукта
- Внедрение новых AI-библиотек и технологий
Требования:
- Уверенное владение Python
- Практический опыт работы с Computer Vision
- Практический опыт работы с LLM
- Опыт локального развертывания open-source LLM
- Опыт интеграции облачных LLM через API
- Умение работать с существующим кодом и готовыми моделями
- Опыт запуска и оптимизации моделей на GPU
- Готовность поддерживать существующие AI-модули и разрабатывать новые
- Самостоятельность и умение доводить решения до production
- Проживание в Астане
Будет плюсом:
- Опыт работы с Hugging Face и Ollama/vLLM
- Опыт использования TensorRT, ONNX и OpenVINO
- Опыт разработки систем реального времени
- Опыт создания AI-продуктов для Computer Vision
Условия:
- Полная занятость
- Возможна стажировка
- Официальное трудоустройство
- Формат работы: удаленно
- График 5/2 или свободный
- Рабочий день — 8 часов или по договоренности
- Заработная плата от 400 000 до 600 000 ₸ до вычета налогов
- Долгосрочная работа над действующим AI-продуктом
- Формат работы и уровень оплаты обсуждаются индивидуально
Location: Hybrid - London
About Vercel:
Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience.
Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide.
About the role:
Developers are building faster than ever. Humans and agents are deploying more than 6 million times a day on Vercel, spinning up over 2 million Sandboxes and serving a trillion requests per month.
Every single one is powered by
our own compute infrastructure
.
The Persistence team sits within Vercel's Compute division. This team owns the deep infrastructure within Hive (our compute platform) focussing on storage and state for all our workloads (Builds, Sandboxes and Functions). This work is redefining compute with features like Fluid Compute, Persistent Sandboxes, and Custom Images.
As a Software Engineer on the Persistence team, you'll work on the infrastructure that runs 100s of instances across every region where our customers deploy code, rethinking low-level primitives and contributing to platform features that improve the experience for thousands of developers every day.
This role is based in
London, UK
. If you're within commuting distance of our London office, the role includes in-office anchor days. If you're located further afield within the UK, the role is fully remote. For location-specific details, please connect with our recruiting team.
What you will do:
Manage and improve our fleet of clusters, running 100s of instances deployed in every region where our customers deploy and run their code.
Write Golang on a daily basis and use Terraform to provision infrastructure; you'll get to know Nomad as our scheduler for managing workloads.
Rethink the primitives of our infrastructure — working with virtual filesystems, Linux primitives, and low-level virtualisation.
Own the reliability and performance of our compute platform, including on-call coverage for a team where every improvement has outsized impact at scale.
Collaborate across teams to drive the convergence of all compute at Vercel.
About you:
5+ years of software engineering experience, with Golang strongly preferred.
Deep experience with virtual machines, file systems and Linux — you like knowing how things work under the hood (tcpdump, strace, and iptables are familiar tools).
Experience building and operating distributed systems at scale; you design for performance and reliability.
Experience with schedulers and orchestrators for managing containers and non-containerised workloads (e.g. Nomad, Kubernetes).
Excellent problem-solving and communication skills, with a genuine enthusiasm for digging into problems that don't have obvious solutions.
Bonus if you:
Have worked on low-level virtualisation or sandbox execution environments.
Have product engineering experience and care about the developer-facing impact of infrastructure decisions.
Have experience with on-call operations for large-scale distributed systems.
Benefits:
Competitive compensation package, including equity.
Inclusive Healthcare Package.
Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.
Flexible Time Off.
We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.
#LI-KR1
Disclosures:
Privacy:
Please review our
Job Applicant Privacy Policy
for more information on how we handle your data.
Equal Opportunity:
Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.
About the role
We’re building a high-performance computer vision system that detects and recognizes objects on fast-moving trains and trucks. The application runs on Linux and is built with Rust/C++ and OpenCV.
You’ll join a small team of engineers and ML specialists, working directly with the technical lead on software that powers logistics, automation, tracking, and access control for ports, railways, and industrial facilities.
This is not an ML research role. Our ML team trains the models—you’ll focus on everything around them: recognition quality, algorithms, tooling, performance, and developer experience.
What you’ll do
Improve recognition quality through data analysis and application logic
Build internal tools, scripts, and developer utilities
Refactor and optimize existing systems for performance and stability
Contribute to other engineering projects when needed (web, mobile, embedded, infrastructure)
Depending on the project, you may also work with Go, Python, React/TypeScript, SQL/Postgres, and Linux tooling.
We’re looking for someone with
Strong Rust, C++, or equivalent systems programming skills
Solid Linux, Git, and command-line experience
Basic understanding of ML or data analysis
Good written and spoken English
We value engineers who are curious, take ownership, debug systematically, communicate well, and enjoy solving challenging real-world problems.
Nice to have
OpenCV, CUDA, deep learning, or custom ML model training
Linux internals, performance optimization, or low-level debugging
Docker, networking, distributed systems, or embedded development
Strong personal or open-source projects
Why Bravora?
We’re a small, fully remote engineering team where you’ll have real ownership, direct impact, and plenty of room to grow. We actively modernize our stack, encourage AI-assisted development, and provide access to state-of-the-art LLM tools.
Interested?
Send us your CV, GitHub or portfolio (if available), your earliest start date, expected hourly rate, and a few sentences about why this role interests you.
Location: Remote: United States; San Francisco HQ; Remote: Canada
Workplace: Remote
At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure.
Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users.
Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development.
We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you.
APPLYING TO RENDER
We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team.
We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed.
Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time.
ABOUT THE ROLE
Render's mission is to eliminate the undifferentiated work that goes into building software products by offering an easy-to-use, powerful cloud platform for developer teams of all sizes.
We are scaling rapidly. Our customers have created millions of services on our platform, and the numbers continue to accelerate. Our customers trust us to deliver a secure, reliable and performant cloud — this is our top priority as a company.
By joining us at an early stage, you will design and build the cloud platform you've always wanted for yourself, and make decisions that will shape our product and company, directly impacting developers around the globe.
Render builds and orchestrates a growing number of kubernetes clusters on different hyperscalers and recently, our own hardware. We leverage open source and industry-standard technologies, modifying and extending the core components to meet the unique reliability, performance, and scaling demands of our platform.
We are looking for engineers with deep specialization in cloud and compute infrastructure. We are particularly interested in experience with Kubernetes and container orchestration, micro VMs, controllers, operators, and the automation and self-healing of large scale distributed systems.
Areas of focus for the team this year will unlocking bottlenecks to scale our clusters while also automating the multi-step creation, configuration, testing, and tuning of Render clusters. We will expand Render to new regions, our own bare metal, and start orchestrating micro VMs outside of Kubernetes entirely.
WHAT YOU'LL DO
- Own Render's core compute infrastructure across multiple cloud providers, regions, and data centers. You'll shape how we evolve our compute platform as we rapidly scale.
- Design and build capabilities that give users greater performance and flexibility in how their services are built, deployed, perform, and stay available even when underlying resources go down.
- Investigate challenging cloud and compute issues across the stack, from the kernel and data plane to our kubernetes cluster, control plane, and other orchestration mechanisms.
- Improve the performance and reliability of our infrastructure through systematic profiling, experimentation, and tuning.
- Partner with engineers across the company to build a platform that is stable, predictable, and secure.
- Participate in our on-call rotation. Help continuously improve how we detect, respond to, and learn from incidents.
WHAT WE'RE LOOKING FOR
- At least 7 years of experience building and operating large-scale platform or compute infrastructure.
- Deep expertise in operating, scaling, and enhancing Kubernetes clusters or similar resource/container orchestration system.
- Experience developing in Go, Rust, or similar languages to develop custom infrastructure components, scheduling, controllers, that apply business logic to resource management.
- Comfort going broad and deep in a complex systems, making tradeoffs to improve performance and efficiency without sacrificing reliability.
- Strong experience designing, debugging, and operating distributed systems.
- Experience planning and executing rapid, high-risk upgrades, changes with minimal downtime to user services.
NICE-TO-HAVES
- Background in virtualization technologies like Firecracker, gVisor, Kata, or similar.
- Experience optimizing the performance of node, pod, and container spin-up times.
- Familiarity with eBPF, Linux kernel internals, resource management.
- Comfort securing and isolating workloads in multi-tenant execution environments.
RELEVANT LINKS FROM THE RENDER INFRASTRUCTURE TEAM
- The Namespaces Scaling Trap https://www.youtube.com/watch?v=NCKhoYsNsmE (video podcast interview) and related article How We Found 7 TiB of Memory Just Sitting Around https://render.com/blog/how-we-found-7-tib-of-memory-just-sitting-around
- SEV0 SF 2025 | Boundary Cases: Technical and social challenges in cross-system debugging https://www.youtube.com/watch?v=d4hAyzmBNXk
- Distributing Global State to Serve over 1 Billion Daily Requests https://render.com/blog/distributing-global-state-to-serve-over-1-billion-daily-requests
- Breaking down OpenAI's outage: How to avoid a hidden DNS dependency in Kubernetes https://render.com/blog/a-hidden-dns-dependency-in-kubernetes
- Kubernetes Informers are so easy... to misuse! https://render.com/blog/kubernetes-informers
If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need.
BENEFITS
- 4 weeks of paid vacation.
- 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return.
- Long-term disability, life insurance, and 401K plans.
- 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well.
- Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc.
- Monthly cell phone and internet subsidy.
- Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders.
- Continuous learning benefits & related support.
This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization.
Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
We encourage all who are interested to apply. We can't wait to hear from you!
Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view
Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view
Задачи:
— Разработка и улучшение biometric и identity verification решений
— Создание production-level Computer Vision и ML-систем
— Разработка алгоритмов Face Verification, Liveness Detection, Anti-Spoofing и Deepfake Detection
— Оптимизация моделей для высоконагруженных систем
— Работа с большими датасетами и подготовка данных
— Внедрение современных исследований SOTA в production
— Разработка и поддержка полного ML/CV pipeline
— Участие в подготовке решений к международным сертификациям и тестированиям
— Работа над AI-продуктами для банков, финтех-компаний, криптоплатформ, телеком-операторов и государственных организаций
Требования:
— Опыт работы ML Engineer / Computer Vision Engineer от 3 лет
— Опыт работы с Face Biometrics, KYC, Identity Verification или Anti-Fraud решениями
— Глубокие знания Computer Vision и Deep Learning
— Уверенное владение Python
— Опыт работы с PyTorch и/или TensorFlow
— Опыт построения production-grade ML/CV систем
— Опыт работы с large-scale datasets
— Опыт оптимизации inference, latency и производительности моделей
— Понимание архитектуры enterprise biometric systems
— Английский язык на уровне B2
— Обязательное преимущество: Опыт подготовки решений к сертификации iBeta Level 2 или Опыт прохождения / участия в сертификации iBeta Level 2
Будет большим плюсом:
— Опыт работы в biometric, KYC или identity verification компаниях
— Участие в NIST FRVT Evaluations
— Опыт разработки Anti-Spoofing и Liveness Detection систем
— Опыт работы с Deepfake Detection
— Понимание международных biometric compliance и certification standards
— Опыт внедрения SOTA research papers в production
— Опыт teamleading
Условия:
— Работа в международной AI-компании
— Участие в разработке production-grade AI-продуктов для международных рынков
— Официальное трудоустройство по трудовому договору
— График 5/2, 8-часовой рабочий день
— Работа в офисе в Алматы
— Финальный оффер зависит от уровня экспертизы
— Возможность работать над сложными задачами в области Face Biometrics, Digital Identity, KYC, AML, Fraud Prevention и Identity Verification
Location: Remote, Global
Workplace: Remote
ABOUT SUPABASE
Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth.
Compute https://supabase.com/compute is our newly launched microVM architecture for running agentic workloads, operating alongside our existing Edge Functions https://supabase.com/docs/guides/functions service for server-side TypeScript functions distributed globally at the edge.
We want developers to be able to build truly global applications by distributing both compute and data globally. Infrastructure concerns like regions, cold starts, CPU and memory provisioning should fade into the background so developers can focus on iterating on business logic, and fast, flexible runtimes a growing range of agent-driven code.
We are looking for experienced and passionate engineers to help us go further in this vision.
WHAT YOU’LL OWN
- Help build & architect the Supabase Compute platform, built on Firecracker microVMs.
- Implementing monitoring, alerting, and OpenTelemetry tracing across the runtime, then using that visibility to drive optimizations that improve latency and reliability of the service.
- Working closely with the Firecracker, Deno, and other open-source teams, contributing to upstream and relaying our users' requirements.
- Participating in an on-call rotation to keep Compute healthy in production.
- Help manage and improve features like scheduled functions, background tasks, WebSockets streaming, ephemeral file storage, and custom routing.
- Integrating Compute more tightly with the rest of the Supabase stack — Auth, Postgres, Storage, and Realtime.
- Expanding the Compute runtime to support more use cases (AI inference, MCP servers, hosting simple websites, URL shorteners).
- Improving the DX of developing and debugging Compute locally through the Supabase CLI, including DevTools integration, logging, and production parity.
WHAT YOU’LL BRING
- At least 5 years of backend or systems engineering experience, with strong fluency in Rust and TypeScript.
- Experience with Firecracker, V8 Isolates, Deno, and related runtime isolation technologies .
- Experience operating infrastructure at scale — Kubernetes, AWS (EC2/Lambda/MicroVM), Cloudflare Workers, Redis, or comparable systems.
- A strong vision for how compute and data can be pushed to the edge.
- Bonus: experience building developer-facing CLIs or front-end tooling that sits on top of an infrastructure product.
WHAT WE OFFER
- Fully Remote
We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.
- ESOP
Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.
- Tech Allowance
Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.
- Health Benefits
Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.
- Annual Off-Sites
Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.
- Flexible Work
We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.
- Professional Development
Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.
ABOUT THE TEAM
Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.
- ~400 team members
- 60+ countries
- 20+ languages spoken
- Over $1B raised (including our $500M Series F)
- 540,000+ community members
We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.
Location: United Kingdom; Brazil; Ireland; Peru; Costa Rica; Latvia; Argentina; Romania; Cyprus; Portugal; Slovenia; Lithuania; South Africa; Czech Republic; Panama; Estonia; Canada; Hungary; Mexico; Poland; Spain; Bulgaria
Workplace: Remote
BUILDING THE FUTURE OF OPEN FINANCE
Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system.
Before you apply, we encourage you to explore our culture page https://www.kraken.com/culture to understand what drives us and how we work.
THE TEAM
Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.
Kraken is building a dedicated AI Compute and Infrastructure team to power the next generation of model training, inference, evaluation, and experimentation across the exchange. This team sits within engineering leadership and owns the infrastructure layer that lets Kraken run AI workloads with control, speed, reliability, and cost discipline.
The team is responsible for GPU and accelerator infrastructure, cluster operations, scheduling, model serving, observability, capacity planning, and cost-efficient compute at scale. This is the backbone that allows Kraken to train, serve, evaluate, and iterate on AI systems in-house where it matters for privacy, latency, reliability, cost, or product differentiation.
You will join a small, senior, high-impact team working directly with AI/ML researchers, platform engineers, security teams, and product teams. The mandate is simple: make Kraken's AI ambitions real by building compute infrastructure that is fast, dependable, efficient, and production-grade.
THE OPPORTUNITY
- Own and operate GPU and accelerator clusters used for training, inference, evaluation, and experimentation, including drivers, runtimes, kernels, device plugins, node configuration, scheduling primitives, and workload isolation.
- Design infrastructure that enables Kraken teams to run models locally on GPUs where it is strategically and economically preferable, reducing unnecessary dependency on external providers and containing compute costs.
- Build and improve scheduling, orchestration, placement, quota management, and utilization systems across heterogeneous accelerator environments.
- Optimize inference pipelines for latency, throughput, reliability, memory efficiency, and cost using frameworks such as vLLM, Triton Inference Server, TensorRT, or equivalent serving stacks.
- Partner with ML engineers and researchers to remove bottlenecks in training, evaluation, batch inference, online inference, deployment, and production debugging workflows.
- Build observability for GPU utilization, memory pressure, queue depth, saturation, token throughput, request latency, failed workloads, capacity pressure, and spend.
- Drive reliability, incident response, alerting, runbooks, and post-incident improvements for always-on AI compute infrastructure.
- Evaluate and integrate new hardware, cloud instance families, specialized accelerators, runtimes, schedulers, and serving frameworks as the AI infrastructure landscape evolves.
- Build tooling that makes GPU usage visible, accountable, and easier for internal teams to consume without needing to become infrastructure experts.
- Contribute to long-term architecture decisions that balance performance, cost efficiency, scalability, operational simplicity, and production safety.
WHAT YOU BRING
- 5+ years of infrastructure engineering experience, with significant time spent on GPU compute, ML infrastructure, distributed systems, high-performance computing, or large-scale production platforms.
- Hands-on experience operating GPU clusters or accelerator-backed infrastructure in production or production-like environments, including scheduling, orchestration, utilization monitoring, and cost optimization.
- Strong systems engineering fundamentals across Linux, networking, storage, containers, Kubernetes, distributed runtimes, and production debugging.
- Experience with ML serving frameworks such as vLLM, Triton Inference Server, TensorRT, TorchServe, KServe, Ray Serve, or equivalent systems.
- Proficiency in Python for infrastructure automation, tooling, debugging, integration, and operational workflows.
- Practical understanding of performance tradeoffs across batching, concurrency, memory usage, GPU utilization, model size, latency, throughput, availability, and cost.
- Track record of optimizing compute costs while maintaining clear performance, reliability, and availability expectations.
- Experience building observable systems with useful metrics, logs, traces, dashboards, alerts, and incident workflows.
- Comfortable working in high-stakes, always-on environments where uptime, throughput, correctness, and operational discipline are critical.
- Clear communicator who can translate infrastructure tradeoffs for researchers, product teams, platform engineers, security stakeholders, and engineering leadership.
NICE TO HAVES
- Experience at a frontier AI lab, hyperscaler, high-frequency trading firm, research platform, or high-scale ML organization.
- Familiarity with custom silicon or specialized accelerators such as TPUs, AWS Trainium, Gaudi, or similar platforms.
- Background in capacity planning, procurement input, reserved capacity strategy, cloud accelerator economics, or GPU fleet cost management.
- Experience with distributed training frameworks such as DeepSpeed, Megatron-LM, FSDP, Ray, or equivalent systems.
- Experience debugging CUDA, NCCL, kernel, driver, runtime, memory, networking, or low-level performance issues.
- Experience with Rust, C++, Go, CUDA, or other systems languages used for performance-critical infrastructure.
- Crypto, financial services, trading infrastructure, or security-sensitive production infrastructure experience.
Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.
Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.
We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
OUR COMMITMENT
Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto.
We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision.
As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.
Stay connected
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Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice
Location: Office Based - Beijing, China
Role Summary
Canonical's OEM Delivery Team works with tier-one OEM, IHV, and ODM customers to pre-load Ubuntu Classic, Ubuntu Core, and bring Ubuntu directly to millions of users. You will have the opportunity to enable cutting edge technology with world leading partners, and become the first contributor to the innovation.
As a Software Engineer, you will be responsible for technical aspects of ensuring that Ubuntu functions well on systems. This fast-paced environment requires strong debugging, critical thinking and problem-solving skills, and deep knowledge of the Linux system. You will cooperate with the best developers in the open source communities to deliver the best user experience.
Key Responsibilities
Work closely with project managers and Field/QA engineers to identify, triage, and fix critical system-level problems;
Work with individual upstream projects to find and apply patches for bugs affecting OEM/ODM customers; champion locally-developed patches for inclusion in the upstream package;
Provide software and system engineering services for OEM and ODM customers;
International travel is occasionally required. Must be able to travel to the EU, USA, China, and Taiwan;
Required Skills And Experience
Participation in open-source development projects;
Passion on Linux and Open Source projects;
Strong English-language communication skills, especially in online environments such as mailing lists and IRC;
Excellent and proven time-management skills;
Ability to be productive in a globally-distributed team through self-discipline and self-motivation;
Desirable Skills And Experience
Demonstrated open source participation and contributions;
Fluency in written and spoken Mandarin Chinese;
Canonical is an equal opportunity employer
Canonical believes a diverse workforce enhances our ability to deliver world class software and services which meet the world’s computing needs. We are committed to ensuring equal employment opportunities to all qualified individuals. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Prime Intellect is looking for a Strategic Account Executive AI Infrastructure to acquire strategic accounts, close multi-year GPU capacity agreements, and expand platform adoption.
🔥Проект - Building and scaling a multi-asset trade and portfolio management platform with strong backend focus including designing, developing, and maintaining backend services, APIs, and data pipelines.
Location: New York, NY (HQ)
Workplace: Hybrid
ABOUT RAMP
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.
The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.
If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
About The Role
We’re looking for a Technical Program Manager who can work across engineering, product, and business teams. You’ll bring the technical judgment to earn engineers’ trust and the ability to create clarity and momentum across complex programs. This is a hands-on role with executive visibility and direct impact on how Ramp’s engineering organization scales.
You’re energized by complexity and curious about how AI can improve the way engineering teams work. You experiment with AI tools yourself, understand how they are changing software development, and bring that perspective to the programs you lead.
What You’ll Do
- Lead large technical programs across engineering and partner teams, from infrastructure scaling to reliability and incident response.
- Connect platform and product engineering teams, keep context flowing, surface dependencies, and drive effective execution.
- Own programs from scoping and kickoff through delivery, measurement, and retrospective.
- Partner with engineering leaders on roadmaps, identify how projects overlap or depend on one another, and keep programs aligned with organizational goals.
- Help engineers, engineering managers, and partner teams communicate business and engineering priorities across the organization.
- Strengthen Ramp’s incident response program by improving processes, facilitating retrospectives, and helping teams act on what they learn.
- Help define how TPMs work at Ramp by setting standards, creating playbooks, and improving program practices.
What You’ll Need
- 5+ years of technical program management experience, ideally in a high-growth startup.
- Hands-on fluency with AI tools such as Cursor or Claude Code, and a point of view on how they can improve day-to-day work and software development.
- The ability to execute directly while improving how the broader team works.
- A track record of building trust quickly and working effectively across teams.
- A BA/BS in computer science, engineering, information systems, analytics, or another technical or analytical field.
- Strong systems thinking: you can connect architecture, product, compliance, and timelines, and spot risks early.
- Experience leading cross-functional programs toward ambitious goals with urgency and ownership.
Nice To Haves
- Experience with cell-based or multi-region architectures, or international expansion.
- Hands-on experience with infrastructure, CI/CD, or observability tools.
- Experience leading reliability programs.
- Experience building programs in rigorous, fast-moving organizations.
- A background in software engineering.
- Familiarity with how LLM-based systems are built and deployed, enough to have substantive conversations with the engineers building them.
BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL)
- Flexible PTO
- Centralized home-office equipment ordering
- Health and wellness stipend
- Budget for intra-office travel
- Weekly coffee stipend
UNITED STATES
- 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents
- One Medical annual membership
- 401(k), including employer match on contributions made while employed by Ramp
- Fertility HRA (up to $10,000 per year)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
- Pet insurance
- In-office perks: lunch, snacks, drinks, and more
- Relocation expense coverage to NYC or SF (if needed)
CANADA
- Group medical, dental, and vision coverage through Sun Life
- Life, AD&D, and disability coverage
- Fertility drug coverage (up to $4,000 lifetime)
- Group Retirement Plan with employer match (RRSP + DPSP)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay
- Employee Assistance Program and virtual care through Lumino Health
UNITED KINGDOM
- Private medical insurance through Freedom Elite
- Virtual GP and at-home care via eMed x Livi
- Workplace pension through Penfold, with salary sacrifice option
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay
REFERRAL INSTRUCTIONS
If you are being referred for the role, please contact that person to apply on your behalf.
OTHER NOTICES
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.
Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice
The garden3d Head of Technology has one mandate: everything we build works, holds up in production, and gets built the smartest way available to us. Working in close partnership with our founder & president Hugh Francis, this person sets the engineering standard, and builds the culture that holds it.
Location: San Francisco, CA or Seattle, WA
Workplace: Remote
ABOUT DOCKER
Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.
We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.
_______________________________________________________________________
Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance—so developers can focus on building incredible AI agents, not gluing together infrastructure.
The Gateway sits at the center of modern AI applications, offering:
- A model and tool routing layer with built-in security and cost optimization
- A familiar OpenAI-compatible interface and MCP server
- Unified observability and policy enforcement
- Auto-RAG, tool injection, session summarization, and more
We’re just getting started—and we need exceptional engineers to help us build the backbone of the future of agent-based development.
WHAT YOU’LL DO
- Design and implement core systems powering the AI Gateway, including the model router, MCP gateway, and control plane
- Build infrastructure that supports dynamic model selection/routing, auto-failover, cost-based routing, and policy enforcement
- Own critical capabilities such as secure credential storage, session summarization, caching, and rate limiting
- Develop APIs for developers building with OpenAI-compatible interfaces and the Model Context Protocol
- Build the underlying infrastructure to support evaluation, telemetry, replay, and backtesting for agents and LLM workflows
- Lead architectural decisions and mentor engineers as the team scales
- Performance tuning - caching, session summarization, and rate limiting that keep the gateway fast under real production load
- Contribute to roadmap planning, technical strategy, and cross-functional alignment
KEY PROBLEMS YOU’LL HELP SOLVE
- Building a unified abstraction over fundamentally different model and tool providers without leaking their differences into the developer experience
- Making credential and identity handling for tool access both airtight and fast
- Giving developers real-time and historical visibility into what their agents are doing, with policy enforcement that can't be bypassed
- Keeping latency low and reliability high as traffic scales from early adopters to production fleets
WHO YOU ARE
Required Qualifications:
- 6+ years of backend engineering experience with production-grade systems
- Deep knowledge of distributed and highly scalable systems, cloud-native infrastructure, and API design
- Experience building secure, high-throughput services (e.g., gateways, proxies, load balancers, policy engines)
- Fluency in Go, and/or Rust (both preferred)
- Familiarity with AI/ML platforms or model serving infrastructure
- A strong product mindset—you're excited about building developer-facing tools
- Ownership mentality with a bias for shipping, learning, and iterating
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Bonus Qualifications:
- Prior experience with OpenAI, Anthropic, or similar LLM APIs
- Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI)
- Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways
- Understanding of OAuth2.1, secret management, and cloud IAM systems
- Experience with Kubernetes, Docker, and microservices architecture
WHY JOIN US?
- Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software.
- Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications.
- Impact at scale: Your work will touch tens of thousands of developers building AI-first applications.
- Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking.
- Remote-first culture: Work from anywhere with a team that trusts and empowers you.
Docker considers visa sponsorship on a case-by-case basis based on business needs.
Compensation & Equity
United States: $160,900 – $260,700 + equity
______________________________________________________________________
POSTING INFORMATION
- Open vacancy: This posting is for an existing open role.
- AI in hiring: Docker may use AI-assisted tools during our recruiting process.
- Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent.
______________________________________________________________________
PERKS & BENEFITS
- Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
- Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
- Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
- Home office support – Set up your workspace for comfort and success.
- Technology stipend – Equivalent to US$100 net per month to help support your work.
- Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
- Parental leave – 16 weeks of paid parental leave after six months of employment.
- Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
- Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
- Docker swag – Because representing the whale never gets old.
Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community.
#LI-REMOTE
Location: San Francisco, CA or Seattle, WA
Workplace: Remote
ABOUT DOCKER
Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.
We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.
_______________________________________________________________________
Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance - so developers can focus on building incredible AI agents, not gluing together infrastructure.
The Gateway sits at the center of modern AI applications, offering:
- A model and tool routing layer with built-in security and cost optimization
- A familiar OpenAI-compatible interface and MCP server
- Unified observability and policy enforcement
- Auto-RAG, tool injection, session summarization, and more
We’re just getting started and we need exceptional engineers to help us build the backbone of the future of agent-based development.
WHAT YOU’LL DO
- Set technical direction for core systems powering the AI Gateway 0 the model router, MCP gateway, and control plane - and make sure architectural decisions hold up as usage scales by 10x
- Consistently identify gaps in our infrastructure, process, or tooling before they become blockers, and drive the fix from idea to production
- Take a significant, hands-on role in defining, delivering, and implementing the Gateway's technical strategy, in close partnership with engineering leadership
- Own the hardest, highest-ambiguity problems in the system: dynamic model selection, auto-failover, cost-based routing, and policy enforcement that has to work end-to-end
- Act as the go-to expert for secure credential storage, session summarization, caching, and rate limiting - the capabilities everything else depends on
- Build the infrastructure that lets us, and our customers, evaluate, replay, and backtest agent and LLM behavior with confidence
- Mentor senior and mid-level engineers, and raise the technical bar for the team through code, design review, and example
- Partner with product, design, and leadership to shape not just what the control plane UI does, but where the product goes next
KEY PROBLEMS YOU’LL HELP SOLVE
- Define the unified abstraction layer across diverse model and tool providers (OpenAI, Anthropic, Google, AWS Bedrock) that the rest of the org builds on
- Architect secure, scalable identity and credential vaulting for tool and model access, trusted enough to run at enterprise scale
- Build the infrastructure for real-time and historical analytics of AI agent behavior that leadership and customers both rely on
- Guarantee that policy enforcement and logging work end-to-end - from prompt to tool to response - with no gaps an auditor (or attacker) could find
- Set the bar for developer experience through intuitive APIs and first-class observability
WHO YOU ARE
Required Qualifications
- 8+ years of backend engineering experience, with a track record of owning production-grade systems at significant scale
- Deep specialization in distributed systems, cloud-native infrastructure, and API design - recognized by peers and cross-functional partners as a go-to expert, not just experienced
- Experience building secure, high-throughput services (gateways, proxies, load balancers, policy engines), and a history of making judgment calls other engineers rely on
- Fluency in Go and/or Rust
- A track record of identifying systemic gaps - in architecture, process, or tooling-— and driving the fix across team boundaries, not just within your own
- A strong product mindset, with real experience shaping technical direction rather than only executing against it
- Comfortable operating with wide latitude: given a problem and significant autonomy in how to solve it, including when and who to pull in
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
BONUS QUALIFICATIONS
- Prior experience with OpenAI, Anthropic, or similar LLM APIs
- Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI)
- Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways
- Understanding of OAuth 2.1, secret management, and cloud IAM systems
- Experience with Kubernetes, Docker, and microservices architecture
- A track record of setting technical standards that other teams or engineers went on to adopt
WHY JOIN US?
- Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software.
- Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications.
- Impact at scale: Your work will touch tens of thousands of developers building AI-first applications.
- Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking.
- Remote-first culture: Work from anywhere with a team that trusts and empowers you.
Docker considers sponsorship on a case-by-case basis based on business needs.
Compensation & Equity
United States: $170,350 – $275,550 + equity
______________________________________________________________________
POSTING INFORMATION
- Open vacancy: This posting is for an existing open role.
- AI in hiring: Docker may use AI-assisted tools during our recruiting process.
- Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent.
______________________________________________________________________
PERKS & BENEFITS
- Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
- Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
- Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
- Home office support – Set up your workspace for comfort and success.
- Technology stipend – Equivalent to US$100 net per month to help support your work.
- Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
- Parental leave – 16 weeks of paid parental leave after six months of employment.
- Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
- Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
- Docker swag – Because representing the whale never gets old.
Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community.
#LI-REMOTE
Location: Remote - US
About the Job:
As a Senior Full Stack Engineer on LaunchDarkly’s AgentControl team, you'll build critical systems such as the web application that customers interact with on a daily basis and distributed systems that power AI evaluations at scale. These systems enable customers to control, monitor, and optimize their agent’s functionality.
LaunchDarkly’s AgentControl team is on a mission to manage the complete software development lifecycle for shipping agents to production, from configuring to benchmarking to observing and beyond. AgentControl enables teams to adjust agent behavior without needing a redeploy or code change, while also running experiments, monitoring agents in production, and putting guardrails around AI as usage scales. The product spans offline evals, real-time observability, prompt and workflow optimization, and decision-making around quality, accuracy, relevance, and cost. The AgentControl team has a huge opportunity ahead of it; it's a strategic bet for LaunchDarkly, and we need your help writing the next chapter in our story.
Responsibilities:
Build and maintain scalable backend services, distributed systems, and APIs that power the AgentControl product
You’ll primarily work in Go, Python, and TypeScript and will work directly with other technologies and tools such as AWS, CockroachDB, Datadog, DeepEval, and FastAPI.
Collaborate with internal stakeholders, including product managers, designers, and other LaunchDarkly engineering teams, to understand real-world challenges and improve GenAI workflows using our own platform.
Keep up to date with the latest developments in the AI field and in software development best practices
Continuously optimize the performance, reliability, and scalability of our systems
Drive architecture and design discussions, offering thoughtful input and collaborating with peer engineers to identify trade-offs and make well-informed decisions
Take ownership of code in production, participate in on-call rotations, and help improve the reliability and maintainability of our systems over time.
Support teammates through thoughtful design reviews, knowledge sharing, and informal mentorship.
Qualifications:
7+ years of professional software engineering experience, with a track record of shipping production-quality full-stack features.
Understanding of prompt engineering, fine-tuning models, or deploying AI services in production environments.
Experience with designing, implementing, and maintaining RESTful APIs
Experience writing production-ready code with emphasis on quality and maintainability
Experience with distributed systems or data ingestion
Strong computer science fundamentals
Committed to working in a communicative, collaborative environment
Comfortable navigating ambiguous challenges in a rapidly evolving domain, and excited about staying at the forefront of AI advancements
Strong sense of ownership and accountability for delivering impactful solutions
Proven ability to work closely with Product and Design teams to define requirements for new features in a fast-paced iterative environment
Bonus: Hands-on experience building GenAI features, Agents, and/or working with Large Language Models (LLMs), either through direct model integration or leveraging AI APIs like OpenAI, Google Cloud AI, or AWS Bedrock.
Pay:
Target pay ranges based on Geographic Zones* for Level 4:
Zone 1:
San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle
- $
187,000 - $257,000
**
Zone 2:
Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago -
$
168,000 - $231,000
**
Zone 3:
All other US locations -
$
158,000 - $218,000
**
LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location.
*Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas.
**Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary.
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. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at
hr@launchdarkly.com
.
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
.
Hybrid - London
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