Вакансии

Location: Amsterdam, Netherlands; Berlin, Germany; Israel; Remote - Europe About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role As a Senior Machine Learning Engineer on the Applied AI team at Nebius Token Factory, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization and model compression, speculative decoding, KV-cache optimization, inference engines, serving architecture, and benchmarking to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving quality and reliability. You will work with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions. You will evaluate model- and engine-level optimizations together with distributed inference designs, including request routing, scheduling, prefill/decode coordination, and multi-node GPU execution. Your improvements will be validated through reproducible benchmarks and safe production rollouts under real-world workloads. Your responsibilities Own optimization projects for specific model families, customer endpoints, or serving backends. Compare inference engines and recommend serving configurations suited to individual workloads. Diagnose model-quality and performance regressions during production rollouts. Improve LLM and VLM endpoint latency, throughput, memory efficiency, GPU utilization, quality, and cost per token. Deploy, configure, benchmark, and extend engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, and NVIDIA Dynamo. Develop production model-compression workflows covering quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery. Implement or integrate speculative decoding, draft-model approaches, KV-cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving. For prefill–decode disaggregation (PDD), evaluate KV-cache transfer, worker placement, and capacity balancing to determine which workloads benefit from the architecture. Design and improve LLM request routers and scheduling policies that balance worker utilization, queueing, request characteristics, and KV-cache locality while meeting latency and reliability targets. Scale dense and mixture-of-experts inference across multiple GPU nodes. Select and tune tensor, pipeline, data, and expert parallelism—including wide expert parallelism (WideEP)—with attention to hardware topology, expert load balance, and communication overhead. Build reproducible benchmark harnesses measuring TTFT, TPOT, tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token. Validate architecture choices under representative traffic and consistent GPU budgets. Collaborate with GPU kernel and platform engineers to trace bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers. Produce design documents, performance reports, rollout plans, and customer-facing technical explanations. Must-haves Strong engineering skills in Python and PyTorch. Hands-on experience deploying or optimizing LLM, VLM, or high-throughput transformer inference. Practical knowledge of at least one modern inference stack, such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or an equivalent internal system. A strong understanding of transformer inference bottlenecks involving KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving. Ability to quantify trade-offs among latency, throughput, quality, utilization, and cost. Experience designing or optimizing distributed inference system architecture, with hands-on work in one or more areas such as request routing, distributed scheduling, PDD, multi-node inference, or expert parallelism. Strong communication and collaboration skills across research, kernel, infrastructure, product, and customer teams. Nice-to-haves Experience with quantization-aware training, post-training quantization, FP8, INT8, INT4, NVFP4, MXFP4, AWQ, GPTQ, or SmoothQuant. Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or related inference acceleration methods. Experience supporting agentic workloads involving tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. Familiarity with CUDA or Triton; the role does not require kernel engineering to be the candidate’s primary specialization. Contributions to open-source projects such as vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, or KServe. Implementation experience with cache-aware request routing, PDD, or WideEP, including diagnosing communication bottlenecks and load imbalance. Familiarity with GPU communication libraries and interconnects, such as NCCL, NVLink, InfiniBand, or RoCE. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Remote Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE *Open to hiring remote — we also have offices in New York, San Francisco, Seattle, London, Paris, and Tel Aviv. Runway is hiring an Infrastructure Security Engineer to secure the platform our models are trained and served on. The role covers Kubernetes platform security, cloud identity and access, software supply chain, tenant isolation in the serving layer and the research infrastructure behind our models. Securing a company that trains and serves frontier video models is a different problem from securing a typical SaaS product. The environment includes research compute, large training datasets, a fast-moving build pipeline, and engineers who work inside AI-assisted tooling every day. Each of those changes what an attack looks like and what the platform has to enforce to stop it. This is a hands-on engineering role on the Security team. You'll write policy, tooling and infrastructure code, work in the platform team's repositories, and ship controls that hold up in production. WHAT YOU'LL DO - Design and ship security controls in our Kubernetes ecosystem: admission policy, RBAC, workload identity, network policy and runtime hardening across every cluster we run - Harden the software supply chain from dependency intake through build and deploy, including package firewalling, artifact signing and provenance, and admission controls that block what doesn't pass - Own cloud IAM and identity architecture: least-privilege roles, short-lived credentials and workload federation - Secure research infrastructure and training pipelines, including access to model weights and datasets, without slowing down the people using them - Threat model new platform components before they ship and turn the findings into concrete requirements the owning team can act on - Build guardrails for AI agents and developer tooling operating inside our infrastructure - Write infrastructure as code and policy as code, and treat security configuration with the same review and rollout discipline as any other change - Give the incident response team what they need when infrastructure is involved: fast answers about how a system works and what to shut off WHAT YOU'LL NEED - Hands-on experience securing Kubernetes in production: you've written admission policies, debugged RBAC and workload identity problems and understand how a cluster gets compromised - Working knowledge of cloud IAM and networking on at least one major cloud platform, including how identity federation and short-lived credentials actually work - Experience with infrastructure as code and GitOps-style deployment, and the habit of shipping security changes through the same pipeline as everything else - Comfort writing Python, Typescript, Rust or another language to build tooling, not just scripts - An understanding of software supply chain attacks and the controls that stop them: signing, provenance, SBOMs, admission enforcement - Clear writing. Design docs, threat models and explanations to engineers who don't work in security are all part of the job - Judgment about which controls to enforce, which to recommend and how to roll out a breaking change without breaking the company EVEN BETTER IF YOU HAVE - Experience securing GPU or HPC-style compute, training pipelines or research environments - Experience with policy engines and admission controllers (Kyverno, OPA Gatekeeper, Falco or similar) - Multi-tenant isolation design in a cloud environment: ABAC, scoped credentials, per-tenant boundaries - Experience producing security architecture evidence for SOC 2, ISO 27001 or other audits and customer assessments - Open source contributions or published work in cloud or Kubernetes security Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: US PlanetScale is growing rapidly and reinventing the database space. The PlanetScale platform offers both Postgres and Vitess clusters. Vitess, an open-source database clustering system for horizontal scaling of MySQL, enables businesses to efficiently handle large-scale data workloads — without sacrificing developer experience. Our customers entrust us with what is often their most precious digital asset, their data, so the stakes couldn’t be higher. We’re looking for a Customer Support Engineer to help developers and businesses get the most out of PlanetScale, resolve issues quickly, and build the support function that helps us scale. What’s the job to be done? You will advise and handle support requests from customers and developers on the PlanetScale platform. You will respond to, debug, and resolve customer support issues through support tickets, customer Slack channels, public discussions, and other support channels. You will help customers understand how to use PlanetScale effectively, including how to reason about queries, schema changes, application behavior, database connectivity, and production workflows. You will create and improve internal and external documentation, support playbooks, troubleshooting guides, and customer-facing materials. You will identify product gaps and recurring sources of customer friction, then work with Engineering to prioritize improvements. You will contribute to the systems, processes, and practices that help PlanetScale deliver excellent developer-focused support at scale. These attributes best describe you. You are customer-focused, empathetic, and clear in how you communicate, while knowing when to push back in ways that help customers become successful on their own. You have excellent debugging and troubleshooting skills, with the curiosity and persistence to follow issues across applications, databases, infrastructure, and product behavior. You are comfortable stepping outside your comfort zone. Whether that means reading unfamiliar application code, digging into database behavior, testing a new framework, or learning a connector you haven’t used before, you’re willing to go where the problem leads. You are a self-starting, enthusiastic individual who takes responsibility for outcomes and wants to make a meaningful impact on the business. You can operate independently, but you know when to ask for help and how to bring the right people into an issue. You are highly organized and able to operate in ambiguous or changing situations. You are data-driven, team-oriented, and comfortable communicating across many audiences. You enjoy working cross-functionally and translating customer pain into actionable product, documentation, and process improvements. What you will need. Experience supporting production applications, databases, developer tools, infrastructure, or other technical products. Working knowledge of SQL, preferably with experience in MySQL and/or PostgreSQL. Strong debugging skills and the ability to reason through application and database behavior. Programming experience. You will not be programming full-time, but you should be comfortable reading and navigating unfamiliar code to understand customer issues. Experience with common application frameworks, ORMs, database connectors, or application deployment patterns. Willingness to explore new languages, frameworks, tools, and customer environments as needed. Strong written and verbal communication skills. Strong empathy for customers, developers, and teammates, with the ability to advocate for customer needs clearly and constructively. What else will help you be successful. Experience working in a remote organization. Experience with cloud platforms such as AWS, GCP, or Azure. Knowledge of monitoring, observability, and debugging tools. Experience helping build support processes, documentation systems, or teams from an early stage. Why PlanetScale. We’re redefining how high-growth companies manage data at scale — and we work with some of the most exciting brands in gaming, consumer tech, and B2B SaaS. As a Customer Support Engineer, you’ll be on the front lines helping developers and businesses solve real production problems, while also shaping the product, documentation, and support systems that make PlanetScale better for every customer. PlanetScale is a profitable company with a philosophy centered around building small teams of p99 individuals and is recognized as one of the fastest growing companies in America. At PlanetScale we believe in supporting people to do their best work and thrive no matter the location. Our mission is to build a diverse, equitable, and inclusive company. We strive to build an inclusive environment where all people feel that they are equally respected and valued, whether they are a candidate or an employee. We welcome applicants of any educational background, gender identity and expression, sexual orientation, religion, ethnicity, age, citizenship, socioeconomic status, disability, pregnancy status, and veteran status. If you have a disability, please let us know if there’s any way we can make the interview process better for you; we’re happy to accommodate! Total Compensation and Pay Transparency An employee’s total compensation consists of base salary + variable comp where appropriate + benefits + equity. A member of our Talent Acquisition team will be happy to answer any further questions when we engage with you to begin the interview process. Base salary range: $150,000 - $200,000 USD

Location: Atlanta, GA (Hybrid) The Position CallRail is looking for a Senior Product Manager to own one of our most important integration domains — either our ad platform integrations (Google Ads, Microsoft Advertising, Meta) or our CRM integrations (Salesforce, HubSpot, and the vertical systems our customers run their businesses on). These integrations are where CallRail's data becomes real value for customers: closing the loop between a phone call and the ad that drove it, or pushing conversation intelligence into the system a sales team actually works in. You'll lead the strategy for your domain and own that surface end to end, and partner with the other integrations PM on the shared patterns — data sync, authentication, webhooks, and third-party APIs — so the portfolio stays coherent. Your integrations are also the foundation other teams build on — including Voice Assist , where what our AI agents can do for a customer depends directly on what your integrations can read and write. We're looking for someone who is genuinely AI-fluent — both in how they work and in what they build. The integration landscape is changing fast: platforms are exposing agent-accessible interfaces, customers expect setup and mapping to be intelligent rather than manual, and the PMs who move fastest are the ones using AI as a daily tool rather than a talking point. You don't need to be an ML engineer. You do need to reach for AI first and have opinions about where it helps and where it doesn't. This role suits a self-motivated PM who thrives at both setting product direction and rolling up their sleeves to deliver results with engineering. What You'll Do Own your integration domain Define and own some of our largest core integrations, aligning them with business goals, customer needs, and strategic partnerships. Take the integrations customers already depend on past MVP — fill functional gaps, expand data coverage, and make them genuinely good rather than merely connected. Own how customers experience your domain: how they discover, connect, configure, and troubleshoot the integrations you're responsible for. Lead discovery with customers, partners, and internal teams to validate problems before scoping solutions. Lead the strategy Lead the product strategy for your integration domain — synthesizing input from Partnerships, business strategy, and customer signal into a clear point of view, and driving alignment on it across the org. Partner with the other integrations PM on the shared design patterns every integration inherits — data sync, authentication, webhooks, and third-party APIs — and make sure the next integration is cheaper to build than the last. Stay current with partner platform roadmaps and the shifting privacy and measurement landscape, and bring a point of view on what it means for our customers. Bring AI into the product Identify where AI meaningfully improves the integration experience — intelligent field mapping, automated setup and diagnostics, enriched data pushed into partner systems, self-healing syncs — and build the case for what's worth investing in. Shape how CallRail's integration data is consumed by AI agents and assistants, as customers increasingly expect their systems to be queryable and actionable by AI rather than only by humans. Know the difference between an AI feature that holds up in production and one that demos well, and be willing to say so. Prioritize and measure Monitor success metrics, product health, and user feedback, and use them to continuously refine your domain. Make the call on sequencing net-new work against fixes and migrations, and be able to explain that call to anyone who asks. Keep the unglamorous half of integration work — bugs, migrations, reliability — visible and scheduled rather than invisible and endless. Cross-functional Partner with other product teams whose features depend on your integrations — most often Voice Assist , where the quality of a CRM or scheduling integration directly determines what our AI agents can actually do for a customer. Treat your domain as a platform other teams build on, and sequence your roadmap accordingly. Work closely with Product Design on the integration experience — setup and authentication flows, field mapping, error and reconnection states — where most of the design difficulty is in making genuinely complex configuration feel simple. Write clear, actionable epics, user stories, and acceptance criteria with real technical context and edge cases identified up front. Partner with Marketing, Sales, and Customer Experience on launches, enablement, and adoption of new integrations. Close the loop with Support — turn ticket patterns into prioritized work, and give them answers and workarounds in the meantime. Represent the integrations domain in planning cycles, executive updates, and cross-functional initiatives. What You'll Need 5+ years of product management experience , with 2+ years focused on integrations, partner ecosystems, or platform-oriented work. Demonstrated AI fluency in your day-to-day practice. You use AI tools to accelerate research synthesis, competitive analysis, spec drafting, data exploration, and prototyping — and you can speak specifically about what you've changed in how you work, not just which tools you've tried. A track record of shipping B2B SaaS integrations end to end—CRMs, ad platforms, marketing automation, analytics, or communication tools. Martech experience is preferred. Strong technical fluency. You read API documentation comfortably, reason about data models and auth flows, and scope edge cases with engineers without needing a translator. Deep API design experience isn't required, but you need to know this territory well enough to make good calls about rate limits, sync behavior, and failure modes. Proven ability to manage complex product surfaces across partner APIs, webhooks, OAuth, and data syncing. Experience building product surfaces that other product teams depend on — negotiating roadmaps with peer PMs, making commitments you can keep, and saying no in a way that keeps the relationship intact. Ability to prioritize clearly across business goals, customer needs, and technical feasibility, and to explain your reasoning to both engineers and executives. Comfort working directly with Support, Sales, and Marketing — turning their signal into prioritized work and keeping them informed without being asked twice. Experience in Agile teams working closely with engineers and designers. We flex to optimize how the team works best together. Excellent written and verbal communication skills. Integration decisions live or die by how well they're documented. Familiarity with tools we use: Jira, Confluence, Miro, Looker, Fullstory, Figma. Nice to Have Hands-on experience with ad platform measurement — offline conversion imports, value-based bidding, consent and privacy changes, and how signal loss affects attribution. Hands-on experience with CRM data models and lifecycle — lead and contact objects, custom fields, activity logging, and the realities of syncing into a customer's existing workflow. Experience shipping an AI-powered feature to production and owning its quality, cost, and evaluation over time. Experience with MCP, agent frameworks, or designing APIs intended for AI consumption. Experience in marketing tech, communications tools, or call tracking ecosystems. Background working with public APIs and/or developer experience tools. Working With AI at CallRail AI is core to how our product team operates, and we expect it to be core to how you operate. We use Claude across discovery, spec writing, data analysis, prototyping, and internal tooling, and we're actively building AI capabilities into the product itself. In this role you will: Use AI daily as a working tool — clustering support tickets to find the real bug patterns, drafting and pressure-testing specs, exploring integration data, and building throwaway scripts and prototypes to answer questions faster than a meeting could. Build your own leverage rather than waiting for it — writing Claude skills, agents, and internal workflows that make you and your team faster. Think about CallRail's platform as something AI agents will consume, not just humans. MCP servers, agent-friendly API design, and tool-calling patterns are increasingly part of what a modern integrations platform is expected to offer, and you'll help shape our point of view there. Stay genuinely current. The tooling changes every few months, and we want someone curious enough to keep up and pragmatic enough to know when a new tool actually helps. We're looking for evidence that you've already changed how you work because of these tools — not just enthusiasm about them. If you do not meet all the requirements listed, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that aligns with your skills and experience. Additional Perks Healthcare (one option covered at 100% for employees), Dental & Vision Coverage Competitive HSA with company matching Paid parental leave Flexible vacation policy 401K options with company dollar-for-dollar match Employee stock options available from day one $2,000 annual educational allowance Catered lunch every Tuesday * an in-office perk MARTA transportation or office parking expenses covered Employee charitable donation company match, up to $500 annually Regular company outings and events Hybrid work options with $500 office stipend to set up your home office Designated bike storage Learn more: https://www.callrail.com/about/ You Are Welcome Here CallRail understands that valuing diverse creative practices and forms of knowledge are crucial to and enrich the company's core mission. We encourage applications from everyone, including members of all equity-seeking communities, such as (but certainly not limited to) women, racialized and Indigenous persons, persons with disabilities, and persons of all sexual orientations and gender identities and expressions. In your application, please feel free to note which pronouns you use (For example - she/her/hers, he/him/his, they/them/theirs, etc). Continuous adoption of AI technologies is essential to this role. You will be expected to leverage AI platforms to streamline operations, solve complex problems, and stay ahead of industry benchmarks. *** This position is based out of our Atlanta office. Through December 2026, employees are expected to work in the office on Tuesdays and Thursdays. Beginning in January 2027, CallRail will transition to a 3 day hybrid work model. Employees will work in the office on Mondays, Tuesdays, and Thursdays.

Location: London, United Kingdom About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role As a Senior Machine Learning Engineer on the Applied AI team at Nebius Token Factory, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization and model compression, speculative decoding, KV-cache optimization, inference engines, serving architecture, and benchmarking to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving quality and reliability. You will work with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions. You will evaluate model- and engine-level optimizations together with distributed inference designs, including request routing, scheduling, prefill/decode coordination, and multi-node GPU execution. Your improvements will be validated through reproducible benchmarks and safe production rollouts under real-world workloads. Your responsibilities Own optimization projects for specific model families, customer endpoints, or serving backends. Compare inference engines and recommend serving configurations suited to individual workloads. Diagnose model-quality and performance regressions during production rollouts. Improve LLM and VLM endpoint latency, throughput, memory efficiency, GPU utilization, quality, and cost per token. Deploy, configure, benchmark, and extend engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, and NVIDIA Dynamo. Develop production model-compression workflows covering quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery. Implement or integrate speculative decoding, draft-model approaches, KV-cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving. For prefill–decode disaggregation (PDD), evaluate KV-cache transfer, worker placement, and capacity balancing to determine which workloads benefit from the architecture. Design and improve LLM request routers and scheduling policies that balance worker utilization, queueing, request characteristics, and KV-cache locality while meeting latency and reliability targets. Scale dense and mixture-of-experts inference across multiple GPU nodes. Select and tune tensor, pipeline, data, and expert parallelism—including wide expert parallelism (WideEP)—with attention to hardware topology, expert load balance, and communication overhead. Build reproducible benchmark harnesses measuring TTFT, TPOT, tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token. Validate architecture choices under representative traffic and consistent GPU budgets. Collaborate with GPU kernel and platform engineers to trace bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers. Produce design documents, performance reports, rollout plans, and customer-facing technical explanations. Must-haves Strong engineering skills in Python and PyTorch. Hands-on experience deploying or optimizing LLM, VLM, or high-throughput transformer inference. Practical knowledge of at least one modern inference stack, such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or an equivalent internal system. A strong understanding of transformer inference bottlenecks involving KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving. Ability to quantify trade-offs among latency, throughput, quality, utilization, and cost. Experience designing or optimizing distributed inference system architecture, with hands-on work in one or more areas such as request routing, distributed scheduling, PDD, multi-node inference, or expert parallelism. Strong communication and collaboration skills across research, kernel, infrastructure, product, and customer teams. Nice-to-haves Experience with quantization-aware training, post-training quantization, FP8, INT8, INT4, NVFP4, MXFP4, AWQ, GPTQ, or SmoothQuant. Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or related inference acceleration methods. Experience supporting agentic workloads involving tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. Familiarity with CUDA or Triton; the role does not require kernel engineering to be the candidate’s primary specialization. Contributions to open-source projects such as vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, or KServe. Implementation experience with cache-aware request routing, PDD, or WideEP, including diagnosing communication bottlenecks and load imbalance. Familiarity with GPU communication libraries and interconnects, such as NCCL, NVLink, InfiniBand, or RoCE. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. We are looking for an experienced Database Infrastructure Engineer to join our Infrastructure team. Our goal is to ensure the reliability, scalability, security and performance of high-load relational database systems. The primary focus of this role is the administration and optimization of PostgreSQL and MariaDB clusters, automation via IaC, and the development of reliable HA/DR solutions. Job Responsibilities Database Cluster Management: Deploy, administer, upgrade, and scale PostgreSQL and MariaDB clusters in high-load production environments; High Availability & Disaster Recovery: Design and maintain HA solutions, replication topologies, failover/switchover, backup/restore , and DR plan; Infrastructure as Code: Fully automate provisioning and configuration management using Terraform and Ansible; Performance Tuning: Analyze query execution plans, optimize indexes and database parameters, investigate locking and replication lag, and tune Linux kernel parameters for specific workload profiles; Observability: Configure monitoring, dashboards, logging, alerting, and SLOs for database services; Troubleshooting: Investigate incidents, analyze logs and metrics, identify performance bottlenecks, and participate in on-call activities; Automation: Develop tools and scripts for routine operations, health checks, failover validation, maintenance, and database lifecycle management. You’ll thrive here if you have Experience: 3+ years as a DBA, DBRE, DevOps Engineer, or System Administrator with a strong focus on production relational databases; Deep understanding of PostgreSQL/MariaDB architecture and internal database processes; Building PostgreSQL/MariaDB high-availability architectures, replication, backup and performance tools; Experience HA soultions for PostgreSQL (Patroni, PgBouncer), MariaDB (MaxScale, Galera); Experience troubleshooting replication lag, deadlocks, locking issues, and transactional workloads; Hands-on experience testing failover scenarios and performing recovery from backups; Strong SQL and query optimization skills, analyze and profiling queries. IaC & Automation: Strong proficiency in Terraform, including writing reusable modules and managing state files; Experience writing complex Ansible roles and playbooks. Linux: Deep knowledge of Linux internals, filesystems, CPU, memory, disk I/O, networking, and kernel tuning for database workloads. Observability: Experience with Prometheus/VictoriaMetrics, Grafana, and the ELK stack. Scripting: Proficiency in Python or Bash for automation and operational tooling. Big Plus: Kafka & Debezium: Experience configuring CDC pipelines from PostgreSQL or MariaDB using Debezium and Kafka Connect; Kubernetes & Helm: Experience running stateful database workloads in Kubernetes, including database operators; Cloud Platforms: Experience with managed database services and cloud infrastructure; Analytical & NoSQL Databases: Knowledge of ClickHouse, MongoDB, Redis or other distributed data platforms; Security: Experience with database access control, TLS, secrets management, auditing, and encryption; Programming: Experience supporting applications written in Java, Go, Python, or similar languages. Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. EU passport. Opportunity to obtain an EU passport after 4 years of residence Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family Corporate mobile plan (unlimited in Cyprus with roaming included) Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals Professional growth support: language courses, conferences, training programs, and coaching. Peer recognition program: receive and share kudos for great work. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free breakfasts and lunches in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons — because great work happens in great communities. Recruitment process HR interview (45 minutes); Technical interview (1.5 hour); Final interview (1 hour); Recommendations check; Job Offer.

Задачи: — Осуществлять первоначальную установку и настройку сервера с базой данных. — Вести администрирование и операционное сопровождение СУБД MS SQL Server. — Заниматься администрированием кластеров, Always On, репликации и механизмов высокой доступности и аварийного восстановления (HA/DR). — Осуществлять настройку мониторинга производительности БД: сбор метрик, создание дашбордов, настройка системы уведомлений. — Настраивать и поддерживать механизмы репликации данных. — Реализовывать партиционирование (секционирование) таблиц и индексов. — Обеспечивать корректную работу транзакций, управлять блокировками, контролировать уровни изоляции. — Оптимизировать SQL-запросы и индексы. — Анализировать планы выполнения запросов, выявлять узкие места. — Выявлять и устранять блокировки в момент возникновения. — Настраивать и сопровождать процессы резервного копирования и восстановления. — Осуществлять регламентное сопровождение и обслуживание БД, в том числе автоматизацию регулярных процедур и процессов. — Разграничивать уровни доступа до баз данных согласно принятой ролевой модели и политик безопасности, принятых в компании, и автоматизировать данные работы. — Регулярно проводить аудит баз данных на соответствие политикам информационной безопасности. — Взаимодействовать с разработчиками по оптимизации запросов (проводить анализ производительности, статистик, индексов, журналов, разбор блокировок и других инцидентов в работе БД). Составлять рекомендации по оптимизации кода для разработчиков. — Разрабатывать стандарты эксплуатации и технической документации. Требования: — Опыт администрирования и поддержки БД MSSQL 2012-2025 от 5-ти лет, от 20+ инсталляций и 100+ БД. — Знание внутренней архитектуры SQL Server и принципов работы СУБД. — Практический опыт работы с Always On. — Понимание принципов работы Failover Clustering, Replication и Log Shipping. — Навыки анализа производительности, поиска узких мест и тонкой настройки СУБД. — Уверенное владение SQL, T-SQL, PowerShell. — Плюсом будет опыт работы с PostgreSQL или другие вендоры OLTP баз данных. — Глубокое понимание языка SQL и принципов оптимизации запросов, включая: оптимизацию индексов, чтение и анализ планов выполнения запросов, профилирование текущей нагрузки БД, выявление и устранение блокировок, анализа производительности, поиска узких мест и тонкой настройки СУБД. — Будет преимуществом: опыт работы с корпоративными (Enterprise) базами данных уровня ERP AXAPTA или другими высоконагруженными системами на базе MSSQ. Условия: — Аккредитованная IT-компания, которая создает и развивает один из ТОП-10 крупнейших интернет-магазинов страны. — Персональное предложение по заработной плате и официальное трудоустройство. — Помощь карьерного консультанта для выбора индивидуального направления развития. — Широкий социальный пакет со стоматологией, компенсация питания в офисе, скидки и бонусы от партнеров. — Современное оборудование для работы. — Стильный и уютный офис в центре Екатеринбурга. — Изучение английского языка в GA English Club, компенсация обучений и развитие в собственном онлайн-университете. — Никаких ограничений по дресс-коду и внешнему виду.

О компании Aidentity — стартап в сфере AI × Human Intelligence. Продукт, который помогает человеку лучше понять свои сильные стороны и найти свое призвание. Стадия: MVP → развитие продукта → масштабирование Нам нужно: — Опыт работы в стартапе / яркое желание его получить — Готовность влиять на продукт с первого дня — Мышление продуктом, а не выполнение задач — Готовность работать только за долю от компании — ML / Data Science / AI — Python и привычный ML-стек — работа с данными, построением признаков, обучением и оценкой моделей — ML-эксперименты и проверка качества результатов — самостоятельное исследование неизвестной области — интерес к задачам на стыке AI, психологии, человеческие качества и рекомендационные систем — recommendation systems, embeddings, NLP/LLM, clustering, similarity / ranking models. Что предстоит делать ✔️создавать систему синтетических профилей данных ✔️развивать и улучшать алгоритм подбора профессий ✔️проектировать систему, которая будет обучаться на данных пользователей и специалистов ✔️экспериментировать с ML/AI-подходами и проверять гипотезы ✔️оценивать качество рекомендаций и разрабатывать метрики для сравнения разных подходов ✔️исследовать способы персонализации результатов для разных пользователей ✔️в перспективе — работать с NLP/LLM и другими AI-инструментами для анализа и обогащения данных ✔️участвовать в проектировании ML-части продукта и принимать технические решения вместе с командой Что предлагаем: — Удаленка — Гибкий график, part-time — Долгосрочное участие — Опционы — Маленькая команда, где слышат каждого — Продукт с большой миссией Подойдет тем, кто любит эксперименты и не боится неопределенности, готов влиять на будущий результат

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. WHAT YOU'LL WORK ON: - Automate remediation of unhealthy machines (power cycling, reimaging, GPU recovery) to maximize uptime and minimize operator toil - Automate integration of new CPU, GPU, and storage servers into the fleet while managing hardware and network heterogeneity - Monitor network health and reliability across many datacenters, and standardize bare-metal network configuration - Automate hardware acceptance testing and benchmarking (CPU, disk, GPU, interconnect, network) - Build our custom network bootloader, machine image pipeline, and kernel and firmware management across the fleet YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve operated fleets of physical hardware (bare-metal provisioning, BMC/IPMI, PXE or network boot, firmware) or built the control planes that manage them (the more challenges you’ve worked through, the better) - You have strong cloud skills - You have strong knowledge of low-level operating system foundations (Linux kernel, drivers, networking, file systems, containers, etc.) - You’re effective at debugging across layers, from BGP flapping, Linux RPS, and vBIOS bugs to a Python control-plane service - You’re willing 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

Location: Stockholm; 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. WHAT YOU’LL WORK ON: - Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicate data across multiple blob storage providers - Automate garbage collection across hundreds of petabytes of data - Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better) - You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - You’re willing to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVE: - 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

Location: Remote - United States Workplace: Remote Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data. As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI. THE TEAM AND YOUR IMPACT We're looking for a Solutions Engineer to own the technical side of our enterprise deals, partnering with Account Executives as the technical authority rather than a supporting player. You'll lead the scoping, pricing, and deployment of semantic search, image and video search, and on-premise and edge deployment solutions for our most complex enterprise customers. This is a hands-on, customer-facing role for someone with real depth in solutions engineering who's ready to run high-stakes deals independently. WHAT YOU WILL OWN: - Own Technical-to-Commercial Strategy: Translate complex architectural requirements (multi-AZ, sharding, replication) into accurate pricing models and contract terms, independently protecting deal value in high-stakes negotiations. - Drive Deal Execution End to End: Own the technical sales workflow across Support, Product, and Engineering to unblock POCs, resolving cross-functional bottlenecks without escalation. - Identify and Mitigate Deployment Risk: Proactively spot noisy neighbor issues, latency bottlenecks, and resource contention before they threaten renewals or expansions, and advise customers on architectural fixes. - Lead Architectural Reviews and Migration Assessments: Run discovery sessions solo, validate use cases, and design migration paths from legacy search engines like Elastic, Solr, and OpenSearch to Qdrant. - Design Resilient, Production-Grade Architecture: Spec high-availability search clusters that meet demanding customer SLAs and throughput requirements, including for the most technically complex accounts. - Own Client Trust at the Executive Level: Serve as the primary technical authority during evaluation, guiding customers to value quickly and acting as a long-term advisor beyond the initial sale. WHO YOU ARE - 2-5 years of technical, customer-facing experience in Sales Engineering, Solutions Architecture, or Technical Consulting, with a track record of owning complex, high-value deals independently, including at least 2 years of direct, hands-on vector search experience (Qdrant, Pinecone, Weaviate, Zilliz/Milvus, or similar). Background in data science, computer engineering, or a previous DevOps/SRE role, with demonstrated depth rather than surface exposure is preferred. - Strong scripting ability in Python or Bash, used to build reusable tools and validate business value at scale, not just one-off scripts. - Fluency in calculating total cost of ownership (TCO) and estimating hardware requirements (RAM, CPU, disk) for distributed systems, including for multi-region or highly regulated deployments. - Deep expertise in Kubernetes and cloud platforms (AWS, GCP, or Azure), with a clear point of view on how infrastructure choices affect cost and performance at scale. - Excellent communication skills, comfortable running the room with engineers, VPs, and business stakeholders alike, and able to influence without authority across internal teams.   NICE TO HAVE - Exposure to enterprise procurement processes, infosec questionnaires, or MSA redlines.   WHY JOIN US - A remote-first, international team working on cutting-edge AI infrastructure. - A competitive salary with additional perks. - Flexible working hours and async-friendly culture. - High ownership and real impact. - Open-source, engineering-driven culture. - Choose your own laptop equipment. For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy. Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist. Come build with us! FOR INFORMATION ON HOW WE HANDLE YOUR PERSONAL DATA, PLEASE REFER TO OUR RECRUITMENT PRIVACY POLICY https://qdrant.tech/legal/recruitment-privacy-policy/ #LI-REMOTE

Location: Remote (US) Infrastructure Engineer (DevOps) About the company Hi, we're Ondo Finance. Our mission is to provide institutional-grade, blockchain-enabled investment products and services. We have both a technology arm that develops decentralized finance technology, and an asset management arm that creates and manages tokenized funds. We were the first company to tokenize exposure to US Treasuries, and have since expanded into several other assets. We are also focused on incubating protocols that can support both tokenized real-world assets and traditional crypto. Founded by folks from Goldman Sachs Digital Assets Team, we're backed by some of the best investors in the world including Founders Fund, Coinbase Ventures, Pantera Capital, Tiger Global, and more. We are currently the leaders in the space in terms of AUM and are well capitalized to continue growing the firm. We're fully remote, with team members across many countries. About the role As an Infrastructure Engineer at Ondo, you'll help build and run the platform our financial products run on. Our team owns the cloud infrastructure, Kubernetes clusters, delivery pipelines, monitoring, and tooling that every engineering team at Ondo depends on, so you'll see a wide range of systems rather than one. You won't do this alone. You'll work closely with a diverse team of infrastructure engineers and developers. Expect to debug real production problems, write code and configuration for user-facing applications, and see your changes running in production early. You'll start with well-scoped work and take on more ownership as you learn our systems. Responsibilities * Collaborate with development teams to build reliable financial services for our customers. * Help the team build and improve release processes, continuous integration, and deployment automation. * Extend application monitoring and alerting. * Participate in an on-call rotation together with infrastructure engineers and developers. * Troubleshoot issues with user-facing and internal services, and debug production incidents. Requirements * Genuine curiosity and desire to learn new technologies and break things. * Hands-on Kubernetes experience: you can deploy, inspect, and debug workloads, even if you've never run a cluster yourself. * Understanding of operating systems, especially Linux internals. * Experience with "infrastructure-as-code" or "infrastructure-as-data" approaches to infrastructure management. * Understanding of the GitOps approach to application management. * Experience with the Prometheus stack or another monitoring solution. Nice to haves * Experience building infrastructure in a major cloud provider (AWS, Google Cloud, or Azure). * Programming ability in Go, Python, or another modern, widely adopted language. * Experience running stateful workloads in production, not only stateless services. Our tech stack AWS, GCP, Azure | Terraform | Kubernetes, Flux | Prometheus, Grafana, Datadog What we offer * Competitive compensation including salary, future token rights, and/or equity (according to your preferences) — we're well-funded and believe that great talent deserves great compensation * Full benefits (medical, vision, and dental) and flexible vacation policy (PTO) * Small remote-first team across many countries — you'll be an early team member helping shape our vision, culture, and design practices * A+ colleagues — our team includes alumni from: Goldman Sachs, Blackrock, Two Sigma, Bridgewater, SpaceX, AWS, Meta, Google, Pinterest, McKinsey, Circle, Uniswap, Phantom * Best-in-class investors — we are proud to be backed by leading crypto experts and VCs, including Pantera Capital, Founders Fund and Coinbase Ventures

Location: Turkey FREEDOM FINANCE TECHNOLOGIES is a Cyprus-based fintech company and part of the international financial holding Freedom Finance. We develop and maintain trading and banking IT products, as well as the holding’s IT infrastructure worldwide. Our team currently consists of 170 professionals.  Over the past three years, we have grown fourfold and continue to actively expand our team. Since 2009, we have been developing our core product - a trading system for brokerage operations in the stock market. More than 700,000 users across 41 countries use our applications. We are looking for a VMware Virtualization Engineer to strengthen our Virtualization and Network Infrastructure team. Key Responsibilities: Operate and develop production virtualization infrastructure based on VMware vSphere (ESXi, vCenter). Support high-availability virtualization clusters and participate in incident resolution. Analyze and resolve technical issues related to hypervisor performance, network infrastructure, and storage systems. Work with storage systems using Fibre Channel and iSCSI. Collaborate with the network infrastructure team to ensure the proper operation of the virtualization environment. Participate in the installation, connection, and commissioning of server hardware. Operate server remote management systems (iDRAC and similar tools). Take part in infrastructure modernization, migration, and testing projects. Requirements Experience administering VMware vSphere in a production environment. Understanding of VMware architecture, including the ESXi scheduler, NUMA architecture, memory management, and storage subsystem. Experience working with storage systems: Fibre Channel zoning, multipathing, latency, and performance analysis. Knowledge of networking technologies required for virtualization operations: VLANs, trunks, LACP, MTU/jumbo frames, and basic L2/L3 principles. Understanding of KVM virtualization principles and architectural differences from VMware. Experience working with enterprise-grade server hardware (Dell, Supermicro, or similar). Experience with server remote management systems (iDRAC), including remote access, firmware updates, and basic hardware diagnostics. Strong independent troubleshooting and technical problem-solving skills. Native Russian Benefits Fully remote work. Daytime and evening working hours according to the Moscow time zone. A service contract with a Cyprus-based company. Fixed monthly salary in euros. Paid annual leave of 21 working days. Paid sick leave. Public holidays: New Year holidays until January 4–6, plus May 1–2 or May 8–9. One additional paid day off per month. Coverage of professional training courses related to your area of work. Coverage of participation in professional online conferences. Training on products and processes. A genuinely comfortable and professional working environment. Opportunities to grow and develop alongside the company and its products.

ООО "Почтовые финансы" – Центр единого сервиса для ДЗО холдинга "Почта России". Ключевые области работы: логистика, электронная коммерция, IT, банки, финтех. Компания создана в 2021 году для ИТ-поддержки и сопровождения деятельности АО "Почта России". Более 3000 человек в 82 регионах присутствия. Задачи: — Осуществлять техническую поддержку и консультирование пользователей по вопросам эксплуатации корпоративной облачной платформы. — Проводить диагностику и устранение неисправностей. — Разрабатывать пошаговые руководства по решению типовых проблем. — Разъяснять функционал систем и сервисов. — Вести базу обращений пользователей (Service Desk): регистрировать заявки, отслеживать статусы выполнения, закрывать заявки после решения проблемы, формировать отчёты по статистике обращений. — Выполнять установку, настройку и подключение программных компонентов корпоративной облачной платформы. — Проводить профилактические работы и обновление ПО. Требования: — Высшее техническое образование. — Опыт администрирования гипервизоров на базе KVM и/или OpenStack не менее 3 лет ОБЯЗАТЕЛЕН. — Понимание принципов работы различных платформ виртуализации. — Знание OpenStack (Nova, Neutron, Cinder, Glance, Keystone). — Опыт работы с Ceph или подобными SDS, а также аппаратными СХД в связке с cinder. — Опыт работы с MariaDB Galera Cluster (синхронная репликация, split-brain, кворум) либо аналогичными кластеризованными решениями. — Опыт работы с HAProxy + Keepalived (L4/L7 балансировка, SSL termination, VIP). — Опыт работы с Apache2 (WSGI для OpenStack API, тюнинг воркеров). — Опыт работы с RabbitMQ (очереди сообщений control plane). — Знание Linux Networking (iproute2, iptables/nftables, namespaces, OVS/OVN, VLAN/VXLAN). — Навыки автоматизации: Ansible, Terraform, Python/Bash, puppet. — Опыт мониторинга: Prometheus, Grafana (или VictoriaMetrics). — Умение работать в команде, активная жизненная позиция, ответственность. Условия: — Официальное трудоустройство согласно Трудовому законодательству. — Стабильный белый доход в государственной компании федерального уровня. — ДМС со стоматологией (подключение пакета после успешного прохождения испытательного срока). — Заработная плата: оклад 256000 руб. + годовая премия по итогу выполнения ключевых показателей эффективности. — График работы: 5/2 с 9.00 до 18.00 (суббота, воскресенье - выходные). — Формат работы обсуждается: офис/гибрид/удалёнка. — Отличные условия труда и коллектив.

Location: Singapore About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role: Network Engineer / Sr. Network Engineer Nebius is an AI-centric purpose-built for intensive GPU using company. As our global footprint accelerates toward multiple gigawatts of capacity, we are establishing our regional network engineering presence in the Asia-Pacific region. We are looking for a hands-on, high-autonomy Network Engineer / Senior Network Engineer to drive the build-out, connectivity, and continuous production operations of our regional data centers, PoPs, and transport fabrics across APAC, with connectivity to EU/the US region and IP transit/PNI services. In this role, you will be the boots-on-the-ground technical authority in the region. You will bridge low-level physical bringing-up with modern CLOS fabrics, collaborating closely with our core engineering teams in the EU (Amsterdam HQ) and the US within a global follow-the-sun operational model. This position is fully remote within the APAC region (preferred hubs: Singapore, India), with periodic domestic/regional site visits and occasional sync trips to our engineering headquarters in Amsterdam. Your Responsibilities Will Include: End-to-End Infrastructure Ownership: Take complete operational and deployment ownership of the network stack across APAC sites—ranging from Day-0 Out-of-Band (OOB) part of network as seed , console setups, and management L2 switches to high-scale leaf-spine frontend fabrics (EVPN/VXLAN) 400g/800g/1,6T ready and regional DCI/Backbone boundaries (BGP/MPLS/SRv6). High-Autonomy Site Bring-up & Operations: Act independently to triage, debug, and deliver connectivity in fast-moving, greenfield colocation environments. Make sound architectural and operational calls on short notice when counter parts oversight is offline. Global Collaboration & Follow-the-Sun Alignment: Partner tightly with core architecture, backbone, and platform teams in the EU and US. Own regional operational handoffs, participate in global on-call rotations, and conduct changes in coordinated regional maintenance windows. Team Scaling & Knowledge Offloading: As the APAC team expands, actively onboard new engineers, write rigorous runbooks, and offload operational pipelines to incoming peers to keep the team scalable. Dynamic Execution: Operate effectively in a high-velocity environment where quarterly business priorities, cluster locations, and deployment schedules adjust dynamically to customer demand. We Expect You to Have: Proven Production Routing & Switching Depth: Solid hands-on experience operating Service Provider or Scale Data Center networks. Deep working knowledge of BGP, IS-IS (or OSPF), EVPN/VXLAN, SR-MPLS/SRv6, ECMP load balancing, and L3VPN architectures. CLOS Fabric & L2–L4 Diagnostics: Strong diagnostic instincts in multi-tier Clos fabrics. Practical mastery of TCP/IP, IPv4/IPv6 dual-stack environments, packet analysis (tcpdump, Wireshark), interface error rates, and QoS queue behavior. Full-Stack Network Mindset: Comfort with the entire operational pipeline: you are equally willing to console into an unconfigured management switch/OOB router at an unpolished greenfield site and tune BGP policy on multi-terabit edge borders (Juniper preferred, or relevant cisco/nokia). Vendor Agility: Practical configuration and troubleshooting experience across modern network operating systems (Juniper Junos, Cisco IOS-XR, Arista EOS, or NVIDIA/Cumulus). Startup Agility & Timezone Flexibility: Proven ability to self-direct, prioritize backlogs under ambiguous requirements, and maintain effective working overlap with European (CEST) and US (EST/PST) teams when critical milestones hit. Communication: Professional working proficiency in English, with the ability to document complex systems clearly and communicate concisely under Sev-1 pressure. It Will Be an Added Bonus If You Have: Practical scripting and network programmability skills (Python or Go, Git, NetBox, telemetry pipelines). Practical exposure to high-performance AI networking: RoCEv2 (PFC, ECN/DCQCN, MCR) fabrics. Experience interfacing directly with regional APAC telecom carriers, dark fiber providers, subsea consortiums, and local Internet Exchanges (e.g., Equinix IX, JPIX, SGIX). Familiarity with Linux networking fundamentals, bridge-domains, and host-routed container networking (BGP-to-the-host). Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Spain; Romania; Hungary; Portugal; Slovakia; Brazil; Poland; Colombia; Mexico Workplace: Remote ✨ ONE PLATFORM, A WHOLE WORLD OF OPPORTUNITY The best jobs have always clustered in a handful of the world's wealthiest cities. But talent is everywhere. Oyster set out to close that gap - building a global employment platform that lets companies hire, pay, and care for brilliant people anywhere. We're proof that a high-performing culture doesn't need an office. Distributed across 60+ countries since 2020, we've built something the industry keeps noticing: - Ranked #10 of 250 on TIME and Statista's 2026 list of America's Top WorkTech Companies https://www.oysterhr.com/library/oyster-hr-named-10-of-americas-top-worktech-companies-of-2026-by-time - Named one of America's Greatest Startup Workplaces 2026 https://www.oysterhr.com/library/oyster-2026-newsweek-award by Newsweek - A G2 Spring 2026 Leader https://www.oysterhr.com/library/oyster-named-best-roi-for-any-global-employment-platform-for-g2-spring-2026 across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance - The only B Corp-certified global employment platform ~ independently verified since 2023 Two of those rankings measured our business impact from the outside. One measured how our own people feel about working here. They landed in the same place ~ because at Oyster, culture and performance aren't separate conversations. They're the same one. And we're just getting started. If you want to do the best work of your career alongside people who care as much as you do, we'd love for you to apply. Location: Fully remote. To create the best experience for you and to meet our business needs, this role requires you to be based either within EMEA or Americas. As a GTM Engineer you'll be the technical operator behind Oyster's revenue engine. You'll build, connect, and automate the software systems that drive pipeline. Turning high-level commercial strategy into workflows that run reliably, without anyone even touching them. Sitting in Revenue Operations, you'll work alongside GTM Teams. Our GTM stack spans a CRM, enrichment and data providers, outbound tooling, our marketing automation platform, the data warehouse, and Oyster's own product APIs. Your job is to make that a coherent system rather than a pile of disconnected tools: clean data flowing to the right place, leads scored and routed in seconds, and reps working from information they can trust. AI is a key part of the toolkit - you'll use it across the end-to-end funnel to automate and boost workflows, for things like prospect research at volume, personalisation, and buying-signal detection. Where a traditional ops hire would build a rules-based scoring model, you'll build an agent that reads a prospect's careers page, funding history, and hiring footprint and hands a rep a research brief worth acting on. The foundation is a strong combination of commercial processes, systems and data - that's where the work lives. CORE RESPONSIBILITIES - Design the architecture of the GTM stack: CRM objects and fields, lifecycle stages, territory and routing logic, sync patterns between systems, and the contracts between them. - Integrate systems end to end: CRM (Salesforce), enrichment providers (Clay, Zoominfo), outbound and sequencing platforms (Nooks, Salesloft), marketing automation (Hubspot), the data warehouse, and Oyster's product APIs (using APIs, webhooks, and scripts rather than waiting for a native connector) - Ship AI-driven GTM workflows - prompt chains, agents, and signal-detection pipelines that automate prospect research, personalised outreach, and real-time buying-signal alerts and more. - Optimise our commercial processes. It’s not only about installing Tech & AI, it is also about taking ownership and evolving the ways we generate revenue. - Build automated data waterfalls that pull, clean, deduplicate, and route prospect and account data into the CRM, so reps work from data they can trust. - Work in a system that's already live. Reverse-engineer existing processes and the reasoning behind them, identify what to keep versus replace, and land changes through a migration plan that keeps pipeline, reporting, and day-to-day selling intact throughout. - Instrument what you build: define the metric each workflow is supposed to move, measure it, and evaluate output quality so automations stay trustworthy as they scale. - Keep the stack maintainable and compliant - sensible data handling, monitoring and alerting on the pipelines or agents you build, documented workflows, and no single points of failure that live only in your head. - Partner with GTM to translate commercial goals into technical solutions, and be honest about which ideas are worth building. MINIMUM REQUIREMENTS - 5+ years in a GTM engineering, Revenue operations, growth engineering, or marketing/sales engineering role, or a software engineering background you've deliberately pointed at revenue problems. - Clear, proven examples of solutions you've implemented that drove measurable pipeline impact. We'll ask you to walk us through them: what you built, why, and what moved as a result. Specifics matter more than scale - Deep, hands-on knowledge of the modern GTM stack. You've architected a CRM rather than just administered one: navigating existing processes to own the re-configuration of objects and fields, lifecycle stages, routing and territory logic, and the sync patterns that keep multiple systems consistent. Salesforce or HubSpot, plus enrichment providers, outbound and sequencing tools, marketing automation, and platforms such as Clay. - You build custom integrations, and can wire up a tool nobody at the company has used before from the docs alone. - Experience owning production workflows: error handling, retries, idempotency, monitoring, and alerting. - Working experience using AI/LLMs in a GTM or automation context - prompt and context engineering, and strong judgement to know where a model beats a rule and where it doesn't - Commercial instinct. You understand funnel mechanics, conversion rates, and unit economics well enough to spot which automation is worth building and which is a distraction - A bias toward shipping. You prototype quickly, put things in front of real users, and iterate rather than designing in the abstract. HOW WE WORK TOGETHER AT OYSTER Our values guide the work we do, the decisions we make, and the culture that makes Oyster what it is. We make it happen—progress is our default setting. We drive change, we build and give trust, and we move as one united team. Our mission is to create a more equal world of work: helping companies everywhere hire, pay, and care for talent anywhere. Everything we do ladders up to our mission. We embrace asynchronous, collaborative work and share how we operate in the Oyster Public HQ https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d so other global teams can learn from us. HOW YOU WORK With diverse locations, cultures, and needs, we created How YOU Work; https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395 a program supporting your whole human experience at Oyster: - Work from anywhere: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere. - Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country. - Mental health support: Access Plumm https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7, our mental well-being service. - Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet to spend on a wide range of options. - Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally. - WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly. ✨ THE BEST JOBS SHOULD BE AVAILABLE TO EVERYONE  We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment. Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email jobs@oysterhr.com with the subject line: Interview Accommodations. Our available positions are on our careers page. Our team will only contact you from an @oysterhr.com email, and we will never ask for money as part of an interview process or job offer. If you receive a suspicious email about Oyster jobs or are directed to a site other than www.oysterhr.com/careers http://www.oysterhr.com/careers, please report it via our Compliance and Ethics Helpline https://faceup.com/c/8tpzyyye.

Location: EMEA; United States; Ireland; United Kingdom; Brazil; Canada; Mexico ✨ ONE PLATFORM, A WHOLE WORLD OF OPPORTUNITY The best jobs have always clustered in a handful of the world's wealthiest cities. But talent is everywhere. Oyster set out to close that gap - building a global employment platform that lets companies hire, pay, and care for brilliant people anywhere. We're proof that a high-performing culture doesn't need an office. Distributed across 60+ countries since 2020, we've built something the industry keeps noticing: - Ranked #10 of 250 on TIME and Statista's 2026 list of America's Top WorkTech Companies https://www.oysterhr.com/library/oyster-hr-named-10-of-americas-top-worktech-companies-of-2026-by-time - Named one of America's Greatest Startup Workplaces 2026 https://www.oysterhr.com/library/oyster-2026-newsweek-award by Newsweek - A G2 Spring 2026 Leader https://www.oysterhr.com/library/oyster-named-best-roi-for-any-global-employment-platform-for-g2-spring-2026 across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance - The only B Corp-certified global employment platform ~ independently verified since 2023 Two of those rankings measured our business impact from the outside. One measured how our own people feel about working here. They landed in the same place ~ because at Oyster, culture and performance aren't separate conversations. They're the same one. And we're just getting started. If you want to do the best work of your career alongside people who care as much as you do, we'd love for you to apply. Location: Fully remote. To create the best experience for you and to meet our business needs, this role requires you to be based within the EMEA or AMER regions. You’ll join Oyster as a Senior AI Solutions Engineer: Go-to-Market, reporting to the AI Director and partnering closely with GTM leadership. Your mandate goes beyond automating individual tasks. You’ll help make Sales, Marketing, Customer Success, Partnerships, and Revenue Operations AI native. This means rethinking how people work with AI, where agents can take on operational work, and where human judgement creates the most value to build a more effective AI enabled GTM organization. You’ll be part of a connected group of Senior AI Solutions Engineers transforming different departments across Oyster. Together, you’ll establish shared standards, reuse successful approaches, and ensure Oyster’s AI transformation is coordinated rather than siloed. This is a senior, hands on role. You’ll independently identify high value opportunities, decide where AI should and should not be used, and lead complex solutions from discovery through adoption and measurable business impact.   CORE RESPONSIBILITIES Make GTM AI native Reimagine how GTM teams work with AI. Move teams from manually operating tools and workflows toward humans orchestrating AI powered ways of working, with human judgement where it matters. Shape the AI roadmap Partner with GTM leaders to identify, prioritize, and frame high impact transformation opportunities. Lead solutions from start to finish Own complex initiatives from an ambiguous problem through design, build, deployment, adoption, and improvement. Build best in class AI agents and solutions Design, build, test, and continuously improve reliable AI agents, agentic workflows, automations, and integrations using LLMs, orchestration platforms, APIs, tools, and enterprise data sources. Apply sound judgement Balance value, feasibility, risk, data quality, maintainability, and human oversight. Recognize when AI is not the right solution. Drive AI adoption and self sufficiency Partner with GTM leaders, managers, and champions to embed AI into everyday work. Help teams move beyond consuming AI outputs toward confidently creating reusable prompts, workflows, and AI powered ways of working. Own solutions beyond launch Measure adoption, quality, reliability, and business impact after release. Continuously improve solutions based on real usage and outcomes rather than treating launch as completion. Connect the organization and raise capability Build trust with GTM leadership, share reusable patterns with AI Solutions Engineers supporting other departments, mentor colleagues, and help teams develop the skills and confidence to operate effectively in an AI enabled environment.   MINIMUM REQUIREMENTS - 3+ years of hands on AI and automation experience, supported by broader experience delivering complex solutions in GTM Engineering, Solutions Engineering, Revenue Operations, systems integration, or a related field. - A track record of redesigning workflows or operating models, rather than only automating isolated tasks. - Experience independently leading complex, cross functional initiatives from an ambiguous problem to measurable business impact. - Strong automation capability using tools such as n8n, Zapier, Make, or comparable orchestration technologies. - Strong hands on experience designing, building, deploying, and improving production AI agents and agentic workflows using LLMs, APIs, tools, and enterprise data. - Strong understanding of B2B GTM operations across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. - Experience integrating business systems through APIs, webhooks, and authentication mechanisms. - Strong judgement about where AI can create value, where processes need deeper redesign, and where automation should not be used. - Ability to influence functional leaders, challenge assumptions constructively, and align technical and nontechnical stakeholders. - A track record of mentoring others, sharing expertise, and raising standards across a team.   BONUS EXPERIENCE - Experience with Salesforce, HubSpot, Gong, Clay, or similar GTM platforms. - JavaScript, Python, or SQL experience. - Familiarity with RAG, MCP, AI evaluation, observability, governance, or security controls. HOW WE WORK TOGETHER AT OYSTER Our values guide the work we do, the decisions we make, and the culture that makes Oyster what it is. We make it happen—progress is our default setting. We drive change, we build and give trust, and we move as one united team. Our mission is to create a more equal world of work: helping companies everywhere hire, pay, and care for talent anywhere. Everything we do ladders up to our mission. We embrace asynchronous, collaborative work and share how we operate in the Oyster Public HQ https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d so other global teams can learn from us. HOW YOU WORK With diverse locations, cultures, and needs, we created How YOU Work; https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395 a program supporting your whole human experience at Oyster: - Work from anywhere: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere. - Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country. - Mental health support: Access Plumm https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7, our mental well-being service. - Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet to spend on a wide range of options. - Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally. - WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly. ✨ THE BEST JOBS SHOULD BE AVAILABLE TO EVERYONE  We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment. Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email jobs@oysterhr.com with the subject line: Interview Accommodations. Our available positions are on our careers page. Our team will only contact you from an @oysterhr.com email, and we will never ask for money as part of an interview process or job offer. If you receive a suspicious email about Oyster jobs or are directed to a site other than www.oysterhr.com/careers http://www.oysterhr.com/careers, please report it via our Compliance and Ethics Helpline https://faceup.com/c/8tpzyyye.

Location: Bangalore, India GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. As a Staff Site Reliability Engineer (SRE) at GitLab, you’ll help keep all user-facing services and production systems reliable, scalable, and efficient. Our SREs combine a pragmatic operations mindset with strong software engineering practices to drive automation, reduce toil, and improve resilience across our platform. In the Environment Automation specialization, your focus is on operating and automating hundreds of GitLab environments—from initial provisioning to day-to-day maintenance tasks. Unlike other SRE roles, this position centers on automating the lifecycle of many tenant environments, ensuring they remain secure, consistent, and reliable at scale. Some examples of the projects you could work on: Designing infrastructure automation that provisions and operates GitLab environments using Terraform, Ansible, and Kubernetes Creating and maintaining deployment packages for GitLab, such as Helm Charts and omnibus-gitlab Building and operating Dedicated GitLab instances integrated with cloud-native services (e.g., GCP, AWS) Developing tools to orchestrate infrastructure-as-code workflows across multiple tenants Deploying and managing microservices on Kubernetes clusters at scale Enhancing GitLab’s observability stack (e.g., Prometheus, ELK) to support proactive monitoring and incident response Integrating with and operating infrastructure in cloud provider ecosystems (e.g., IAM, networking, storage) Championing and implementing cloud security best practices across automated infrastructure What You’ll Do Build & Scale Multi-Tenant Infrastructure: Design and implement automation that provisions and manages hundreds of isolated GitLab environments using Terraform, Ansible, and Kubernetes. Manage complex state strategies and workspace configurations to support scale and maintainability. Debug & Resolve Production Issues: Troubleshoot issues across Kubernetes clusters, cloud services, and GitLab apps—identifying root causes of failed deployments, crash loops, and scheduling conflicts to ensure service continuity. Automate Operations at Scale: Replace manual workflows with infrastructure-as-code solutions, including automated version upgrades, configuration rollouts, and provisioning pipelines that operate reliably across all tenants. Monitor & Predict Capacity: Build observability systems that detect bottlenecks, predict usage trends, and optimize resource consumption using tools like Prometheus, ELK, and Grafana. Respond & Lead During Incidents: Lead incident response and postmortem efforts, applying technical depth to resolve issues and establish operational standards that reduce future risk. Architect & Collaborate: Influence architectural decisions around automation, scalability, and operational excellence. Partner with engineering teams to improve automation, platform resilience, and production-readiness. What You’ll Bring Production-Scale Experience: Proven ability to operate and troubleshoot production workloads across multiple tenants or environments. Deep understanding of how distributed systems fail at scale and how to build in resilience. Terraform & IaC Mastery: Strong hands-on experience with Terraform, including workspace strategies, state management, and automation patterns that scale. Comfortable solving state isolation issues and building reliable, reusable infrastructure code. Experience with Ansible and templating tools like Jsonnet is a plus. Kubernetes in Production: Skilled at diagnosing deployment failures, interpreting pod logs, and debugging scheduling issues and rollback scenarios in live environments. Understands how pods, ReplicaSets, and controllers interact in production. Programming & Code Analysis: Ability to read and debug code in Go and/or Ruby. Familiar with identifying performance issues, scalability concerns, and contributing to infrastructure tooling through thoughtful code analysis. Large Scale Operations Background: Experience supporting infrastructure for many customers or environments simultaneously. Comfortable managing isolation, scaling, monitoring, and incident response across diverse workloads. Architecture & Incident Response: Able to reason through complex systems and operational challenges. Brings on-call experience and can lead technical discussions and incident resolution efforts under pressure. Customer-Focused Collaboration: Proven ability to work across teams and with internal or external customers to solve technical problems while maintaining service commitments and clear communication. GitLab Platform Proficiency: Comfortable using GitLab as a daily tool for infrastructure automation, collaboration, and operational workflows. About the team GitLab’s Dedicated team, where the SRE Environment Automation role sits, is on a mission to deliver a fully managed, single-tenant GitLab experience through the GitLab Dedicated platform. Our goal is to eliminate manual operations across the entire lifecycle of customer environments, including provisioning, upgrades, security, and monitoring, so customers can focus on unlocking the full potential of The One DevOps Platform without managing the underlying infrastructure. We build scalable, automated systems that ensure each GitLab Dedicated instance is secure, consistent, and production-ready—whether we're managing 10 environments or hundreds. How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .