Вакансии

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

180 000 – 360 000 $

Location: San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems.Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated — whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA.We’re looking for a systems engineer who enjoys working deep in the stack. You’ll build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of Modal’s container platform. You’ll also work closely with maintainers of gVisor and contribute to the runtime itself when the right fix belongs upstream. THE WORK: - Make container startup, checkpoint, and restore dramatically faster for large inference and training workloads. - Build multi-GPU and accelerator-aware snapshotting, including efficient handling of GPU memory and RDMA-enabled workloads. - Design zero-copy and low-copy data paths between container memory, filesystems, storage, and Modal’s runtime. - Optimize large snapshot pipelines using techniques such as parallel uploads, direct I/O, incremental snapshots, and more efficient memory handling. - Improve container image and filesystem performance across EROFS, FUSE, page caches, overlay filesystems, and remote storage. - Extend our sandboxed runtime to support new GPUs, drivers, profiling tools, and device capabilities across NVIDIA and AMD hardware. - Debug complex failures involving system calls, virtual memory, process lifecycle, kernel behavior, GPU drivers, and container isolation. - Safely roll out runtime and kernel changes across a heterogeneous fleet using compatibility controls, scheduling constraints, feature flags, and observability. - Work across the runtime, scheduler, storage, and GPU infrastructure—and take ambiguous production problems from investigation through deployment. WHAT WE’RE LOOKING FOR: - Strong Linux systems knowledge, particularly processes, virtual memory, filesystems, system calls, scheduling, namespaces, cgroups, and signals. - Experience building or debugging container runtimes, sandboxes, Linux kernel, or similarly low-level infrastructure. - Strong programming ability in Rust, Go, or another systems language, with an interest in becoming productive in both Rust and Go. - Experience profiling and improving systems where memory movement, I/O, synchronization, or kernel interactions dominate performance. - Comfort debugging across abstraction boundaries, from application behavior down through runtimes, drivers, and the kernel. - An ability to turn loosely defined production problems into well-designed, reliable systems. - A desire to own important infrastructure and work closely with both internal teams and customers. RELEVANT EXPERIENCE: Any of the following would be helpful, but none is required: - gVisor, runsc, runc, OCI runtimes, seccomp, or checkpoint/restore systems. - Linux kernel development, virtualization, sandboxing, kernel modules, or device proxying. - CUDA, ROCm, GPU drivers, accelerator virtualization, or GPU profiling. - RDMA and high-performance networking. - FUSE, EROFS, direct I/O, mmap, page-cache behavior, or storage engines. - Large-memory or multi-GPU inference and training systems. - Contributions to open-source systems software. Prior gVisor or machine-learning experience is not required. We care more about strong systems fundamentals, curiosity, and the ability to learn unfamiliar parts of the stack. WHY THIS ROLE: The container runtime is directly on the critical path for inference performance. Improvements here can substantially reduce cold starts, increase token throughput, unlock new accelerator types, and make previously impractical workloads possible.This is an opportunity to work on unusually deep systems problems with immediate production impact. You’ll have room to shape the architecture, contribute to open-source runtime technology, and take ownership of foundational infrastructure used by every inference and training workload on Modal.

Location: Home based - Worldwide Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1200+ colleagues in 75+ countries and very few office-based roles. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution. The company is founder led, profitable and growing. We are hiring 2025 and 2026 Graduate Software Engineers into engineering teams around the world. As a global platform company we offer a wide range of software engineering challenges, in both open source products and commercial business systems. We have teams that work in a variety of languages, typically Python, Golang, Rust, C/C++, JavaScript and of course... Bash. We work from the very lowest levels of the Linux system - BIOS and boot loaders, firmware, kernel and drivers, all the way up to desktop applications and containers. We work on tiny devices like the Raspberry Pi and new RISC-V boards, all the way up to supercomputers, clouds and Kubernetes clusters. We work on compilers and toolchains, and we work on security, cryptography, performance and documentation. Some of our teams focus on packaging thousands of pieces of software, others focus on deep contributions to a single body of code. If you are excited about the potential that open source has for humanity and the enterprise, you have outstanding results in your academic career, and you are excited to contribute to the open source stack, this is the best way to apply to Canonical. We will work with you to identify teams and projects that would be interesting and a good fit for your skills and motivations. The process is highly competitive, it will require effort and excellence to succeed if you apply here. Most of our engineering teams work from home. We try to align a single team in a single time zone - EMEA (Europe, Middle East and Africa), APAC (Asia Pacific and Indian Ocean), and AMER (North, South and Central Americas). Even though you work from home, we try to ensure you always have colleagues alongside to coach and mentor you, and for the companionship of shared problem solving and pair programming. Larger projects have multiple teams and might span the globe. We work with the open source community and specialize in building teams that work well in the 'fishbowl' of open source engineering. This is full time work, five days a week, often solving hard problems with significant responsibility. We don't generally work weekends and nights and we do enjoy good holidays but we also expect productive and intense engagement Monday to Friday. We bring all our engineering teams together in person twice a year for a deep 'sprint' with other teams to stimulate discussion and enable a wide range of career development paths. This is a fantastic way to demonstrate and develop your skill in software, learn about a wide range of technologies, make a meaningful impact to open source, and see some very interesting new cities that you might never otherwise get to visit. If you find the open source stack amazing, and you have been a consistent high-performing student in your school and university, then this will be a challenging and exciting start to your career. Location: This is a Globally remote role. The role entails Shaping the roadmap for your product at global sprints every six months Focusing on design and user experience, even for developer tooling and command line apps Writing high quality, resilient and performant code, potentially serving millions of demanding daily users Working towards mastery of key programming languages and Linux system knowledge Engaging with users and the open source community through code reviews and issue trackers Responding to customer issues as a priority, develop an understanding of enterprise requirements Developing skills and awareness of security in software design and implementation What we are looking for in you Exceptional academic track record from both high school and university Undergraduate degree in Computer Science, Business Informatics, Mathematics or another STEM discipline with programming courses Confidence to get started and deliver high quality code in one of Python, Rust, C/C++, Golang, JavaScript or Java Experience with Ubuntu or another Linux distribution Track record of going above-and-beyond expectations to achieve outstanding results Result-oriented and organized, with the drive to meet commitments Personal projects in technology and software engineering beyond the curriculum Professional written and spoken English Excellent interpersonal skills, curiosity, flexibility, and accountability Personal responsibility and accountability Thoughtfulness, self-awareness and the ability to reflect and develop Ability to travel internationally twice a year for company events up to two weeks long Nice-to-have skills Upstream open source contributions Packaging and Linux distribution contributions - Debian, Fedora, Arch, Nix or another Leadership and organization skills Presentation and writing skills Business and commercial interests What we offer colleagues We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognize outstanding performance. In addition to base pay, we offer a performance-driven annual bonus or commission. We provide all team members with additional benefits which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally. Distributed work environment with twice-yearly team sprints in person Personal learning and development budget of USD 2,000 per year Annual compensation review Recognition rewards Annual holiday leave Maternity and paternity leave Team Member Assistance Program & Wellness Platform Opportunity to travel to new locations to meet colleagues Priority Pass and travel upgrades for long-haul company events About Canonical Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world of software. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since its inception in 2004.​ Working here is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical is an equal opportunity employer We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration. #LI-remote

Вы будете создавать и внедрять решения на базе генеративного ИИ: мультиагентные системы, RAG-конвейеры, интеграции с внутренними сервисами и автоматизацию бизнес-процессов. Строить и сопровождать RAG-решения: векторные хранилища, пайплайны, ретривал.

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• Оптимизация скорости, стоимости и стабильности inference больших LLM. • Есть production-опыт оптимизации LLM inference: SGLang / vLLM / TensorRT-LLM.

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• Повышение эффективности алгоритмов. Вам предстоит оптимизировать алгоритмы, учитывая аппаратные особенности платформ, автоматизировать тестирование алгоритмов и их адаптацию к платформе.

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• Разработка и развитие программной архитектуры. Предстоит обеспечивать стабильный обмен данными между подсистемами робота с частотой от 1 кГц, выстраивать взаимодействие с датчиками и исполнительными механизмами, контролировать задержки в критичных контурах.

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ASOS.com — британский онлайн‑ритейлер модной одежды, обуви, аксессуаров и косметики. Размер команды — 1k-5k, инвестиции — £587.5M. Технологии и инструменты: Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, Semantic Kernel, LangChain, LangGraph, AutoGen/CrewAI, Python или C#/.NET. Фаундеры компании: Nick Robertson, Andrew Regan, Quentin Griffiths, Deborah Thorpe. В компании работают русскоговорящие сотрудники.

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• Разрабатывать AI-агентов на Python. • Интегрировать модели и внешние API.

до 260 000 ₽

Location: San Francisco; New York Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on top of it, whether that is a kernel panic, a broadcast storm during boot, or getting our container runtime to run on new architectures and platforms. REQUIREMENTS: - 5+ years of experience writing high-quality production code - Experience operating fleets of physical hardware (bare metal provisioning, BMC/IPMI, PXE or network boot, firmware) or building the control planes that manage them (the more challenges you've worked through, the better) - Strong cloud skills - Strong knowledge of low-level operating system foundations (Linux kernel, drivers, networking, file systems, containers, etc.) - Effective at debugging across layers, from BGP flapping, Linux RPS, and vBIOS bugs to a Python control-plane service - Willingness to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVES: - Experience with GPUs and the NVIDIA software stack in production (drivers, health monitoring, XIDs, RDMA/NVLink) - Prior experience with Go KEY THINGS THE TEAM IS WORKING ON: - Automatic remediation of unhealthy machines (power cycling, reimaging, GPU recovery) to maximize uptime and minimize operator toil. - Automatic integration of new CPU, GPU, and storage servers into the fleet while managing hardware and network heterogeneity. - Network health monitoring and reliability across many datacenters, and standardization of bare metal network configuration. - Automatic hardware acceptance testing and benchmarking (CPU, disk, GPU, interconnect, network). - Custom network bootloader, machine image pipeline, and kernel and firmware management across the fleet.

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

Location: San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal's LLM inference platform delivers frontier performance https://modal.com/blog/kimi-k3-by-moonshot-now-available-on-modal for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots https://modal.com/blog/gpu-mem-snapshots and multi-cloud substrate https://modal.com/blog/resource-solver. We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area. This is a hands-on leadership role — expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direction, remove blockers, and build a strong engineering culture as your team tackles hard problems in distributed computing, frontier inference serving, and performance optimization. RESPONSIBILITIES: Team - Recruit, hire, and grow a high-performing team of engineers; run regular 1:1s focused on coaching, feedback, and career growth. - Set clear performance expectations, hold a high bar, and build an environment where engineers do their best work. - Foster a culture of ownership, accountability, customer obsession, and continuous improvement. Technical and Product Direction - Drive technical and product decisions through design reviews, code reviews, and architectural discussions. - Lead our efforts working with customers with novel or frontier workloads so they can be successful running on Modal. - Translate learnings from frontier customers into a roadmap for our internal optimization platform and user-facing product, so that gains from optimization and research efforts are accessible to all of our users. - Establish standards for reliability and product excellence; ensure the team owns projects end-to-end, from spec through production. Cross-Functional Leadership - Partner with business operations and compute strategy on continuing to develop our strategy for compute purchases across a variety of accelerators. - Collaborate with GTM on product launches, positioning, and improving win rates for inference opportunities. - Help guide the roadmap for teams building the infrastructure platform underlying inference, as well as adjacent product teams. REQUIREMENTS: - 10+ years of industry experience, including 3+ years in a leadership role - Track record building high-performance systems at scale - Strong background in cloud infrastructure - Deep knowledge of low-level OS foundations (Linux kernel, file systems, containers, etc.) - Nice to have: Experience working with LLM inference in production and familiarity with underlying concepts like engines, kernels, routing, KV cache management and speculative decoding.

Задачи: — Разработка ядра высоконагруженных систем на Rust: торговые боты, low-latency инфраструктура, потоки данных Solana — Проектирование архитектуры с низкой задержкой, надежностью 24/7, работа со шредами — Руководство командой из 1-3 инженеров: код-ревью, стандарты, менторинг, найм — Работа с данными и бэктестинг (ClickHouse), R&D — quant/ML-стратегии, поиск edge — Оптимизация производительности на всех уровнях: код, сеть, инфраструктура — Использование продвинутых технологий: kernel-bypass datapath (AF_XDP / eBPF), тюнинг сокетов, дедупликация и форвардинг шредов, прямые сенды (QUIC → TPU), bundle-роутинг, MEV-relay, обход медленных RPC Требования: — Опыт продакшен-разработки на Rust не менее 3 лет (async/tokio, производительность, глубокое понимание внутренностей) — Сильные навыки системного дизайна, опыт работы с low-latency и высоконагруженными системами — Понимание трейдинга и рынков (EV, риск, стратегии) — принципиально важно — Лидерские качества и самостоятельность в принятии решений Плюсы: — Опыт с Solana (RPC, программы, Jito/MEV, Geyser, шреды) — Опыт работы с ClickHouse и данными — Знания в ML/quant, DevOps/инфраструктуре — Опыт в блокчейн-среде Условия: — Полная занятость, удалённая работа из любой точки мира — Оплата в USD, возможна выплата в криптовалюте — Русскоязычная команда

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Location: Remote, Global 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. ABOUT THIS ROLE We’re hiring experienced performance engineers to make performance measurement at Supabase rigorous, repeatable, and actionable by product teams. This role owns the benchmarking and profiling systems we use to detect regressions, explain performance changes, and publish credible numbers for customers and the market. You’ll build the tooling and the methodology and make it easy for product teams to use it correctly. You’d join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There’s no legacy process to inherit — you’ll help define how we measure and communicate performance metrics at Supabase. WHAT YOU’LL DO - Build and evolve benchmarking, profiling, and load-testing tooling (cloud, database, and end-to-end). - Define benchmark suites and reference workloads that reflect real customer behavior (and evolve them as the products change). - Establish performance baselines and regression gates across products (variance tracking, environment control, and detection of changes). - Build mechanisms that turn benchmark results into action: triage workflows, owner routing, and clear, reproducible reports. - Partner closely with database teams (e.g. Multigres, OrioleDB) to identify bottlenecks and land concrete performance improvements. - Enable the company to publish credible, repeatable performance numbers for customers and the market. - Help teams self-serve performance testing and make performance a first-class engineering concern. PROBLEMS YOU MIGHT WORK ON - Build our continuous benchmarking infrastructure so product teams can spot performance regressions early. Ideally, teams can run benchmarks directly on PRs or locally while developing a feature. - Analyze and eliminate issues with load generators, workloads or benchmark environments to ensure that benchmarks are reliable indicators for actual product performance. - Build regression triage tooling that pinpoints what changed (diffing, profiles/traces, query-level attribution). - Help product teams so they can analyze the root cause of performance regressions in benchmark environments themselves. WHAT WE’RE LOOKING FOR - Deep experience in performance engineering, benchmarking, and profiling of complex distributed systems. Specifically, you have owned benchmarking systems where reproducibility and controlling variance mattered. - Strong systems intuition (databases, storage, networking, cloud infrastructure). - Comfortable working across product, infra, and database teams. - Pragmatic, tooling-oriented mindset with strong communication skills. - Depth on at least one end of that stack: Linux kernel internals (virtual memory, scheduling, networking, IO) or database internals (query planning, storage engines, buffer and WAL management) 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: Remote, Global 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. ABOUT THE ROLE We're hiring experienced performance engineers to find and land performance wins across the Supabase stack — from the query optimiser to block device level, and across the network paths and cloud infrastructure that connect our distributed platform. This is a performance delivery role: real, measured improvements to our database, platform, and APIs as we scale toward enterprise and platform-grade workloads. The methodologies you develop and tooling you build exist to multiply that delivery. You'd join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There's no legacy process to inherit — you'll help define how performance engineering works at Supabase. WHAT YOU'LL DO - Find bottlenecks in live production systems and characterize them precisely enough that the owning team can act on them without you in the room. - Partner closely with database teams (e.g. Multigres, OrioleDB) and infra teams to land concrete performance improvements. - Build, communicate, and evolve performance methodologies and tooling that turn live production data into actionable insight. - Partner with the observability team to capture the right signals and establish a unified view of platform performance (latency, throughput, tail behavior) across products. - Help teams self-serve performance analysis and make performance a first-class engineering concern. PROBLEMS YOU MIGHT WORK ON - Tune the kernel's paging behavior to production workloads - Reduce memory overhead in OrioleDB and Multigres - Identify and eliminate sources of latency spikes from application to kernel level - Identify scalability bottlenecks across the entire stack and work the appropriate teams in Supabase and the wider community to resolve them WHAT WE'RE LOOKING FOR - Deep experience in performance engineering, specifically performance analysis of complex distributed systems. - You can walk the whole stack: follow a tail-latency problem from the query optimizer through the syscall boundary to the IO scheduler — or across pooler hops, network paths, and availability zones — reading profiles and traces at every layer. - Depth on at least one end of that stack: Linux kernel internals (virtual memory, scheduling, networking, IO) or database internals (query planning, storage engines, buffer and WAL management) - Strong working knowledge of networking and cloud infrastructure performance: TCP behavior under load, network virtualization overhead, and the performance characteristics of AWS primitives (EBS throughput and IOPS, instance network limits, placement groups, cross-AZ latency). - Proven ability to turn performance insights into real product and architecture improvements — including getting teams you don't belong to to prioritize and ship the fix. - Strong written communication: your problem characterisations are precise, reproducible, and compelling on their own. - Pragmatic, tooling-oriented mindset; comfort working across product, infra, and database teams. 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: San Francisco Bay Area; 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. _______________________________________________________________________ As a Staff Software Engineer in Networking, you will set the technical direction for the networking stack behind Docker's Sandboxes platform and make architectural decisions that ripple across Docker's product portfolio. Your work will directly enable Docker's expansion into AI and security products. This role calls for someone who: 1. Combines deep technical expertise in infrastructure at scale, virtual networking, service mesh, orchestration, and integration across the broader infrastructure stack; 2. Communicates and collaborates well, thinks critically, and turns ideas into working systems 3. Adapts to ambiguity and brings clarity 4. Provides technical leadership to a small team of engineers, driving customer delight through the solutions they deliver   RESPONSIBILITIES - Design, implement, and operate core networking services that power Docker's Sandboxes platform across local laptops and public cloud environments - Build scalable networking infrastructure for microVM orchestration, workload scheduling, and lifecycle management - Develop high-performance networking data- and control-plane components for multi-tenant agentic workloads - Ensure network reliability, observability, and performance across Docker's Sandbox infrastructure - Collaborate with product, platform, and security teams to deliver customer-focused capabilities - Participate in architectural discussions, code reviews, and design documents - Contribute to automation and CI/CD improvements across the deployment pipeline - Debug and resolve production issues across distributed systems in local and public-cloud environments - Take part in on-call rotation for your team; respond to incidents and drive continuous improvement of system reliability and availability   QUALIFICATIONS - 8+ years of experience building and leading large-scale cloud or distributed systems, with a focus on networking foundations - Track record of driving technical consensus and delivering high-quality infrastructure software at scale, on tight timelines - Experience with microservices architecture, container networking, service mesh, policy enforcement, and container orchestration - Experience with kernel and user-space networking technologies, including Linux networking, OVS/OVN, DPDK, and eBPF - Experience designing and operating highly available, secure, and observable networking infrastructure - Strong understanding of cloud infrastructure (AWS, Azure, GCP, OCI) and related scalability patterns - Familiarity with CI/CD pipelines, monitoring, and infrastructure-as-code tooling - Excellent problem-solving and debugging skills in distributed environments - Strong communication skills and ability to collaborate across remote, cross-functional teams - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience   WHAT TO EXPECT FIRST 30 DAYS - Onboard, integrate with our Sandbox infrastructure teams, and build context on Docker's Sandbox vision - Deep-dive into Sandbox architecture for local and public-cloud infrastructure, with a focus on driving simple, common foundational primitives usable across both environments - Identify the highest-leverage opportunities in the current architecture, along with strategic and tactical execution risks FIRST 90 DAYS - Develop a technical roadmap to address the challenges identified; drive consensus across stakeholders - Provide technical leadership to a small team of engineers to deliver on the roadmap - Establish or improve technical standards for development, deployment, operation, and observability of networking services ONE-YEAR OUTLOOK - Drive simplification of foundational networking infrastructure across local and public-cloud environments - Establish repeatable engineering practices for quality, performance, and operational excellence - Nurture the team's confidence and capability by providing clarity, sustaining focus, and delivering pragmatically through successive iteration - Set a standard for what a small team of engineers can deliver and manage when given a charter, autonomy, and the tools they need Docker considers visa 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: San Francisco Bay Area; 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. _______________________________________________________________________ As a Principal Software Engineer in Networking, you will set the technical direction for the networking stack behind Docker's Sandboxes platform and make architectural decisions that ripple across Docker's product portfolio. Your work will directly enable Docker's expansion into AI and security products. This role calls for someone who: 1. Combines deep technical expertise in infrastructure at scale, virtual networking, service mesh, orchestration, and integration across the broader infrastructure stack; 2. Communicates and collaborates well, thinks critically, and turns ideas into working systems 3. Adapts to ambiguity and brings clarity 4. Provides technical leadership to a small team of engineers, driving customer delight through the solutions they deliver RESPONSIBILITIES - Design, implement, and operate core networking services that power Docker's Sandboxes platform across local laptops and public cloud environments - Build scalable networking infrastructure for microVM orchestration, workload scheduling, and lifecycle management - Develop high-performance networking data- and control-plane components for multi-tenant agentic workloads - Ensure network reliability, observability, and performance across Docker's Sandbox infrastructure - Collaborate with product, platform, and security teams to deliver customer-focused capabilities - Participate in architectural discussions, code reviews, and design documents - Contribute to automation and CI/CD improvements across the deployment pipeline - Debug and resolve production issues across distributed systems in local and public-cloud environments - Take part in on-call rotation for your team; respond to incidents and drive continuous improvement of system reliability and availability QUALIFICATIONS - 10+ years of experience building and leading large-scale cloud or distributed systems, with a focus on networking foundations - Track record of driving technical consensus and delivering high-quality infrastructure software at scale, on tight timelines - Experience with microservices architecture, container networking, service mesh, policy enforcement, and container orchestration - Experience with kernel and user-space networking technologies, including Linux networking, OVS/OVN, DPDK, and eBPF - Experience designing and operating highly available, secure, and observable networking infrastructure - Strong understanding of cloud infrastructure (AWS, Azure, GCP, OCI) and related scalability patterns - Familiarity with CI/CD pipelines, monitoring, and infrastructure-as-code tooling - Excellent problem-solving and debugging skills in distributed environments - Strong communication skills and ability to collaborate across remote, cross-functional teams - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience WHAT TO EXPECT FIRST 30 DAYS - Onboard, integrate with our Sandbox infrastructure teams, and build context on Docker's Sandbox vision - Deep-dive into Sandbox architecture for local and public-cloud infrastructure, with a focus on driving simple, common foundational primitives usable across both environments - Identify the highest-leverage opportunities in the current architecture, along with strategic and tactical execution risks FIRST 90 DAYS - Develop a technical roadmap to address the challenges identified; drive consensus across stakeholders - Provide technical leadership to a small team of engineers to deliver on the roadmap - Establish or improve technical standards for development, deployment, operation, and observability of networking services ONE-YEAR OUTLOOK - Drive simplification of foundational networking infrastructure across local and public-cloud environments - Establish repeatable engineering practices for quality, performance, and operational excellence - Nurture the team's confidence and capability by providing clarity, sustaining focus, and delivering pragmatically through successive iteration - Set a standard for what a small team of engineers can deliver and manage when given a charter, autonomy, and the tools they need Docker considers visa sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $198K – $319K + 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: 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 hundreds of thousands 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 operates our own networking stack end-to-end. 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 network infrastructure, particularly with experience in edge/ingress networking and Kubernetes networking internals. Areas of focus include scaling and evolving our traffic routing and load balancing systems; advancing Kubernetes and Linux networking components to support large-scale, zero-downtime operation; and exploring networking for Render’s next-generation compute platforms. WHAT YOU'LL DO - Own Render's core network infrastructure across multiple data centers and cloud providers. Shape how networking evolves as Render rapidly scales. - Design and build customer-facing networking capabilities that give users greater flexibility in how their services connect, communicate, and how traffic is routed. - Investigate complex networking issues across the stack, from the kernel and data plane to distributed systems and edge networking. - Drive performance and reliability improvements through systematic profiling 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 6 years of experience building and operating large-scale networking or infrastructure systems. - Experience with Kubernetes networking internals (e.g. kube-proxy, CNI plugins, service routing) or similar container networking technology. - Experience with Linux networking internals (e.g. routing, netfilter/iptables/nftables, conntrack) in production environments. - Experience building and operating traffic routing systems (e.g. load balancers, ingress, proxies) at scale. - Strong experience designing, debugging, and operating distributed systems. - Experience planning and executing high-risk changes with minimal downtime. NICE-TO-HAVES - Experience with eBPF or advanced Linux kernel networking. - Experience developing systems in Go or similar languages that interact with low-level OS and networking primitives. RELEVANT LINKS FROM THE RENDER ENGINEERING 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