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Location: Remote, Global ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ABOUT THE ROLE Supabase manages millions of Postgres instances and is growing. We have strong teams across observability, release engineering, and incident management — and we're concentrating our reliability efforts into a dedicated SRE practice that ties the discipline together across the platform. You'll be embedded within Service Operations, and your primary job is to make every engineering team more reliable — not by owning their infrastructure, but by establishing the practices, frameworks, and feedback loops that let them own reliability themselves. You'll work across the org: sometimes setting the standard, sometimes pair-programming a fix, sometimes helping a team define their error budget, sometimes telling them it's exhausted. This role is ideal for someone who has a strong vision for how SRE should work and thrives in async, fast-paced environments where influence matters more than authority. WHAT YOU'LL OWN - Partner with service teams to define meaningful SLIs and SLOs grounded in customer experience, and build the error budget policies that turn them into engineering decisions - Own and evolve the Operational Readiness Review (ORR) process — conducting reviews for new services and major changes across observability, alerting, runbooks, capacity, and graceful degradation - Strengthen the incident-to-improvement pipeline: connecting postmortem findings to operational readiness gaps, identifying repeat failure patterns, and driving systemic fixes - Act as the reliability expert teams pull in for architecture reviews, failure mode analysis, dependency mapping, and resilience design - Identify and quantify operational toil across the org, and build or advocate for automation that eliminates it - Help teams design sustainable on-call practices: alert quality, escalation paths, runbook coverage, and noise reduction - Track and report on org-wide operational maturity, surfacing systemic gaps and driving remediation YOU MIGHT BE A GOOD FIT IF YOU - Have 7+ years of experience in SRE, production engineering, or reliability-focused roles, including experience shaping SRE practices and driving adoption across engineering teams - Have a software engineering mindset — you write code and build tools, not just configure them - Have hands-on experience defining and operationalizing SLOs/SLIs at scale, including error budget policies that actually influenced engineering decisions - Have deep experience with incident response, postmortem facilitation, and turning incident learnings into systemic improvements - Have worked with large-scale multi-tenant systems (bonus: managed database platforms or Postgres) - Are proficient with cloud infrastructure (AWS preferred) and infrastructure-as-code (Pulumi preferred, Terraform/CDK also acceptable) - Communicate clearly and persuasively — this role requires influencing without authority across a distributed org - Have experience in async or globally distributed teams - Are energized by making other teams more effective rather than being the one who fixes everything NICE TO HAVE - Experience with Kubernetes-based platform operations - Familiarity with OpenTelemetry, VictoriaMetrics, Grafana, or similar observability tooling - Experience building developer-facing reliability tooling (SLO dashboards, ORR frameworks, toil tracking, DORA metrics) WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Location: Espoo Workplace: Hybrid ROLE HIGHLIGHTS: - Mechanical Engineering Systems & CAD Specialist - Location: Espoo, Finland - Department: Spacecraft Hardware - Reports to: Mechanical Team Lead - Employment type: Permanent - Workplace model: Hybrid / Office - Employment is subject to applicable security screening (incl. SUPO, where required) WHY THIS ROLE MATTERS: As ICEYE expands its satellite constellation and develops more advanced spacecraft, reliable engineering tools and efficient workflows are essential to meeting demanding aerospace quality standards. This role ensures mechanical design teams have the software, systems, and processes they need to develop reliable, cost-effective products and deliver missions successfully. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. YOUR DAY-TO-DAY RESPONSIBILITIES - Ensure smooth, seamless and on time product delivery, from concept to qualification - Contribute to the continuous improvements of our current products - Systems & Software Administration: Install, update, license, and maintain mechanical design software, FEA/CFD simulation tools, and PLM databases - Engineering Team Support: Provide day-to-day technical assistance and troubleshooting for design engineers working with CAD and simulation software - Model & Data Management: Maintain standardized CAD library components, template files, and product structure integrity within the PLM system - Process Optimization: Assist in establishing best practices for CAD modeling standards, design release workflows, and revision control - Vendor & IT Liaison: Coordinate with software vendors for licensing/updates and collaborate with internal IT teams on system infrastructure requirements WHAT WE’RE LOOKING FOR Must haves: - Master’s or Bachelor’s degree in Mechanical Engineering, Mechanical Engineering Technology, or a related field - Experience in aerospace, automotive, or related industries - 5-10 years of practical experience in mechanical design or engineering IT/tool support - CAD/PLM Expertise: Proficiency in handling complex product assemblies with modern 3D CAD platforms and PLM environments - Ability to work cross-functionally with systems, electrical, manufacturing and IT- teams - Simulation Knowledge: Hands-on experience or proven familiarity with engineering simulation tools - Problem-Solving Ability: Strong analytical troubleshooting skills with a customer-service mindset toward supporting engineering end-users Nice to haves: - Experience on Autocad Inventor, PTC Creo or Siemens NX - Experience on PTC Arena and Altair simulation tools - Experience on CADTALK or similar integration tools - Ability to program simple macros & scripts - Ability to develop simple toolkits through API interface APPLICATION PROCESS - Talent Attraction Introduction - Hiring Manager Alignment - Task Assignment - Technical Interview - Director Interview WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Задачи: — администрировать и развивать Windows/Linux-инфраструктуру; — поддерживать Multi-domain Active Directory, GPO, DNS и DHCP; — работать с VMware vSphere: ESXi, vCenter, кластеры и vSAN; — администрировать Proxmox VE, виртуальные и Bare Metal-серверы; — поддерживать RDS farm и FSLogix для 100+ пользователей; — настраивать мониторинг в Zabbix; — автоматизировать задачи с помощью PowerShell; — диагностировать проблемы и повышать стабильность и отказоустойчивость инфраструктуры. Требования: — уверенный практический опыт с Active Directory в multi-domain среде; — хорошие знания VMware и опыт работы с Proxmox VE; — опыт администрирования RDS и FSLogix; — навыки работы с физическими серверами и PowerShell; — самостоятельность, ответственность и умение разбираться в технических проблемах. Условия: — формат работы: удалённо; — график: 5/2, 09:00–18:00; — опыт: от 3 лет на аналогичной позиции; — локации: Кыргызстан, Азербайджан, Грузия, Армения, Узбекистан, Молдова, Украина.

Location: Austria; France; Germany; Italy; Netherlands; Poland; Spain; United Kingdom Why Kimchi? Great models are raw ingredients. Kimchi is what happens when you ferment them with good engineering. We started inside CAST AI helping companies run LLMs on their own Kubernetes clusters; today we run our own coding harness on any model you pick, and the router deciding which model answers each request is ours too. The Auto Router Our promise is one enforcement layer for your AI: budgets, spend attribution, and model routing, applied before a request ever hits a model. The Auto Router makes the call: for every request, which model serves it. Eight open-source models whose input prices span more than 20×, cached input up to 50× cheaper than fresh, frontier providers on customers' own keys, and a coding agent that fires hundreds of requests before its task is done. Frontier-level task success at a fraction of the token cost: that sentence is the product, and it stays true only if the model inside the router keeps getting better. That model is yours. Made by Cast AI — a Miami-headquartered, globally distributed team across 34 countries that hit unicorn status in January 2026 with a $50B+ backed investment pushing its valuation past $1 billion. About the role Every request gets a decision: which model serves it. This is an applied-ML seat, not an infrastructure one. Platform engineers own the proxy, the streaming path, and the fleet. You own the model inside them: the training data, the objective, the evaluation, and the iteration loop that ships a better router every cycle. The problem: routing is a prediction problem wearing a product's clothes. For every request you predict the quality each candidate model would deliver, what it would cost, and how fast it would decode, and you have to be right enough, in aggregate, that the savings are real and the quality never dips below frontier. The data is messy: rollout outcomes from benchmark harnesses, per-request records from the live fleet, override signals, and token streams whose speed depends on the serving concurrency at the moment. Speed itself is a correctness variable: on deadline-bound agentic work, a model that decodes three times slower doesn't do the same work slower, it does less work. That's why naive cost-per-token objectives quietly optimize for the wrong thing. And the bar for evidence is high: a router change ships only after production-parity evaluation with error bars, then gets held to its numbers in live traffic. Stack: Python; PyTorch; SQL at scale (ClickHouse); OpenAI- and Anthropic-compatible LLM APIs; benchmark and rollout harnesses (RouterBench-class); GitLab CI. Requirements You've spent 5+ years in applied ML or ML research, and you've trained, evaluated, and shipped models that make real-time decisions (ranking, recommendation, bandits, pricing, or LLM routing) and you can tell that story with receipts. Strong Python and SQL at scale: you can pull, clean, and interrogate millions of request-level records without waiting on anyone. You know the difference between a model that got better and an eval that got easier. You have real opinions about what LLM benchmarks measure, agentic harnesses included. You know enough serving reality (TTFT, decode speed, batching, prefix caching, concurrency) to model the objective honestly. You instrument before you optimize, error bars and all. A wide mandate excites you more than it unsettles you. Nice to haves You've worked on LLM routing specifically: RouterBench-class evals, cost/quality/latency Pareto fronts. Calibration, abstention, or conformal methods in production decision systems. You've run online A/B loops with drift monitoring on a model that touches real money. Responsibilities Own the routing model end to end: features, objective, training, calibration, and release cadence. Iterate it like a product, not a research artifact. Build the evaluation that gates every change: production-parity benchmarks, router-vs-router comparisons, holdouts by task family, error bars on pass rates. Nothing ships on vibes. Turn fleet data into training signal: per-request outcomes from production, benchmark rollouts, and override feedback, with failure categorization (infra vs task) so poisoned labels never reach the policy. Model the objective the user actually experiences: task success × token cost × wall-clock speed under the real concurrency regime, with cached-input economics in the picture. Run the online loop: shadow, A/B, full rollout, drift monitoring, retrain. When production disagrees with your offline eval, you find out why before the next ship. Push the frontier where it pays: calibrated decisions, abstention under uncertainty, speed-aware routing. We experiment on what a router should be, not just which model it picks today. Partner with platform engineers on instrumentation: the features and labels recorded per request (decode speed first-class among them) and the experiments the data path must support. What’s in it for you? Competitive salary (depending on the level of experience). Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: Austria; France; Germany; Italy; Netherlands; Poland; Spain; United Kingdom Why Kimchi? Great models are raw ingredients. Kimchi is what happens when you ferment them with good engineering. We started inside CAST AI helping companies run LLMs on their own Kubernetes clusters; today we run our own coding harness on any model you pick, and we run the models underneath it ourselves. Kimchi Inference One API line and a customer's existing client just works: DeepSeek, GLM, Kimi, MiniMax, Nemotron served serverless from our own GPU fleet (OpenAI- and Anthropic-compatible, pay per token, spend visible per user, team, and key). When control matters, the same models run on the customer's own cluster instead. Behind that one line sits the machinery you'll own: SGLang and vLLM engines, B300 nodes, a shared cluster filesystem that holds every checkpoint exactly once, KV caches riding coding traffic with heavy prefix reuse, and the benchmark harness that gates every change we ship. Made by Cast AI — a Miami-headquartered, globally distributed team across 34 countries that hit unicorn status in January 2026 with a $50B+ backed investment pushing its valuation past $1 billion. About the role Throughput. Latency. Cold starts. Cost per token. Move those four numbers in the right direction and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every loader you tune, every scheduler decision you land, every kernel you stare at shows up in a customer's p99 and on our P&L. Your mandate is the inference stack's optimization, whatever it takes, and the technical direction of how we optimize it is yours to argue with data. The problem: the checkpoints run 0.3-1.5 TB, and the "right" serving configuration depends on traffic shape, sequence-length distribution, batch dynamics, GPU SKU, memory bandwidth, and quantization tolerance, all variables that shift week to week. Most teams pick a configuration once, over-provision GPUs, and absorb the cost. We don't: we took Kimi-K3 (1.5 TB) from over an hour cold-to-serving to under twelve minutes with a shared filesystem, O_DIRECT weight loaders, and node-local JIT caches, and we're nowhere near done. Prefill/decode disaggregation and tiered KV caches are next. Stack: Python; SGLang; vLLM; TensorRT-LLM; PyTorch; fastsafetensors; CUDA-adjacent tooling; Kubernetes; virtiofs shared filesystems; ClickHouse; OpenTelemetry; Prometheus; Grafana; GitLab CI. Requirements You've built real ML systems for 5+ years, and your portfolio shows depth in inference or training infrastructure, not just model training notebooks. Your Python is production-grade: services, not scripts. You've run vLLM, SGLang, or TensorRT-LLM for real, and you have a working mental model of why an engine performs the way it does on a given GPU. You've measured quantization regressions, not just compression ratios. Multi-GPU and multi-node setups hold no fear: tensor and expert parallelism, collective communication, and their practical failure modes. You know where the bytes live (page caches, O_DIRECT, network filesystems under terabyte-scale reads) and how fast they move. You instrument before you optimize, and you can tell a real win from a benchmark artifact. A wide mandate excites you more than it unsettles you. Nice to haves You've worked on LLM routing specifically: RouterBench-class evals, cost/quality/latency Pareto fronts. Calibration, abstention, or conformal methods in production decision systems. You've run online A/B loops with drift monitoring on a model that touches real money. Responsibilities Push throughput. Continuous batching, chunked prefill, speculative decoding with draft models, CUDA-graph capture, and scheduler tuning across the engine fleet. Find the ceiling on each GPU SKU, then raise it. Cut latency. Attack TTFT and inter-token latency separately; profile to find the actual bottleneck (compute, memory bandwidth, scheduling, storage, or network) and fix it, not the one you assumed. Get more out of the KV cache. Hierarchical and paged attention, prefix caching on heavy-reuse coding traffic, eviction policies, quantized KV. A lot of the unrealized throughput lives here, and you'll own it. Kill cold starts. Weight loaders (O_DIRECT, fastsafetensors-class), JIT and compile caches, shared-filesystem read paths. A 1.5 TB checkpoint has no business taking an hour to reach serving. Quantize without regressing quality. INT8/INT4, FP8/FP4 across weights, activations, and KV, measured on real workloads, not just perplexity benchmarks. Scale across nodes. Distributed inference topologies, network-aware placement, prefill/decode disaggregation, checkpointing strategies that don't bottleneck on storage or interconnect. Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments. What’s in it for you? Competitive salary (depending on the level of experience). Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are looking for a strong Deep Learning Engineer to join our Autonomy team and develop the learning-based algorithms that power dynamic locomotion and whole-body control on our humanoid robots. You will develop robust, reusable motion capabilities that enable the robot to move dynamically, maintain balance, interact with its environment, and combine locomotion with manipulation. This includes building the underlying learning-based motion primitives that can be composed into increasingly complex whole-body behaviors. You will work closely with robotics, controls, simulation, and machine learning engineers to turn learned behaviors into reliable capabilities running as part of the robot's real-time control stack.   WHAT YOU'LL DO - Design and train learning-based locomotion and whole-body control policies for dynamic robotic behaviors. - Develop motion primitives using different learning based generative models. - Apply reinforcement learning, imitation learning, and other learning-based approaches to motion generation and control. - Build scalable simulation, data generation, and training pipelines using platforms such as Isaac Lab and MuJoCo. - Develop methods for robustness, adaptation, and sim-to-real transfer, including domain randomization and learning from real-world robot data. - Deploy, evaluate, debug, and fine-tune learned policies on physical humanoid robots. - Optimize policy inference and training systems for the performance and latency requirements of real-time control. - Integrate learned policies into the broader robot control and autonomy stack.   WHAT WE'RE LOOKING FOR - BS, MS, or PhD in Robotics, Machine Learning, Computer Science, or a related technical field. - 3+ years of experience developing machine learning systems in industry or research. - Strong understanding of deep learning and modern policy architectures, including training, inference, experimentation, and debugging. - Hands-on experience with RL and at least one additional area such as imitation learning, generative models, sequence models, or large-scale representation learning. - Strong Python and PyTorch experience. - Experience with physics-based simulation environments such as Isaac Lab, Isaac Sim, MuJoCo, or similar platforms. - Ability to reason about learning algorithms in the context of dynamics, control, and physical systems. Nice to have: - Experience applying reinforcement learning or imitation learning to legged robots, humanoids, or other complex physical systems. - Experience with whole-body control, locomotion, motion imitation, or loco-manipulation. - Experience deploying learned policies on real robotic systems and debugging the sim-to-real gap. - Familiarity with motion capture, trajectory optimization, model-based control, or learning from demonstrations. - Experience training policies at scale across large numbers of simulated environments. - Publications at NeurIPS, ICML, ICLR, CoRL, RSS, CVPR, or equivalent contributions to impactful open-source robotics or machine learning projects.   WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: Abu Dhabi, United Arab Emirates; Dammam, Saudi Arabia; Jeddah, Saudi Arabia; Khobar, Saudi Arabia; Riyadh, Saudi Arabia; Amman, Jordan; Kuwait City, Kuwait; Doha, Qatar Workplace: on-site At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Senior Full-Stack and AI Engineer to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Responsibilities: Design, configure, and manage cloud-based lab environments, including Azure Databricks workspaces, AI coding tools, and development repositories. Develop hands-on technical exercises, starter repositories, and training materials for a 3-day programme. Prepare and validate access requirements, permissions, and technical setups before training delivery. Lead practical workshops covering AI-driven software development, agentic coding, CI/CD, and deployment automation. Deliver hands-on training in data engineering, including Spark, Delta Lake, ETL/ELT pipelines, lakehouse architecture, and data governance. Demonstrate AI platform security, including LLM guardrails, model access control, prompt injection prevention, and production monitoring. Conduct Azure Databricks labs covering workspace configuration, notebooks, Delta tables, pipelines, and model inference. Guide participants through integrating AI capabilities into full-stack applications using Python and TypeScript/JavaScript. Perform live coding, troubleshoot technical issues, and support participants with different experience levels. Facilitate team-based capstone projects involving AI-integrated application development. Collaborate with the AI instructor to coordinate technical sessions and practical exercises. Provide complete lab materials and a post-training delivery report. 5+ years of professional software engineering experience, including full-stack development with Python and TypeScript/JavaScript. Strong hands-on experience integrating LLM APIs and developing production AI applications. Proven production experience with Azure Databricks, including workspace configuration, Delta Lake, jobs, and data pipelines. Experience with AI engineering architecture, model serving, inference APIs, retrieval systems, and model evaluation. Practical knowledge of AI platform security, LLM guardrails, prompt injection prevention, and sensitive data protection. Proficiency with agentic AI coding tools such as Cursor, Claude Code, or GitHub Copilot. Strong experience with CI/CD pipelines, Azure cloud services, and deployment automation. Hands-on data engineering experience with Apache Spark, lakehouse architectures, data governance, access control, and lineage. Experience integrating AI models into full-stack applications. Previous experience delivering technical workshops, bootcamps, or corporate training programmes. Excellent presentation, communication, live-coding, and technical troubleshooting skills. Ability to independently prepare and deliver complex hands-on technical labs. Must be based in the UAE and available for 3 consecutive on-site training days in Abu Dhabi, plus approximately 3 days of remote preparation. Must have no current or previous engagement with the end client. Nice to have: Experience with NVIDIA AI Enterprise or GPU-accelerated AI workloads. Experience delivering technical training or solutions within public-sector or regulated environments. Knowledge of UAE data protection and compliance requirements.

Требования: — 5+ лет опыта в Computer Vision и Deep Learning — Глубокая экспертиза в Python и современных CV-фреймворках — Практический опыт с OCR, распознаванием текста на изображениях, Document AI — Опыт с CNNs, Vision Transformers и мультимодальными моделями О компании: Глобальная команда, работающая над AI-решениями в области компьютерного зрения. Сотрудничество по B2B-контракту.

Задачи: — Владение полным циклом пользовательских сценариев с AI-агентом Upgrade на чат, голос и email: создание, оптимизация, обработка крайних случаев и рост показателя containment. — Создание сценариев в no-code инструменте Sierra Agent Studio, сотрудничество с продуктовыми группами для интеграции сервисных потоков. — Ответственность за разрешение проблем клиентов AI-агентом без участия человека. — Анализ и улучшение сценариев после запуска, включая чтение транскриптов и повышение качества взаимодействия. — Ведение портфеля сценариев по продуктам (Personal Loans, Card, BNPL, HELOC, Deposits) и установление стандартов разработки AI-опыта. Требования: — 3–5 лет опыта во Frontend Software Engineering или эквивалентный опыт в Solutions Engineering, Conversational AI или технических продуктовых ролях. — Знание поведения LLM-агентов: инструкции, вызовы инструментов, извлечение знаний и типичные ошибки. — Опыт построения оценок для недетерминированных систем: тестовые наборы, симуляции, LLM в роли судьи, регрессионные проверки. — Техническая грамотность для чтения API спецификаций, работы с backend-инженерами по REST и GraphQL, понимание авторизации и прав доступа. — Знание JavaScript/TypeScript для создания и поддержки кодированных сценариев и интеграции API в платформы Conversational AI. — Ориентация на продукт и клиента, умение читать транскрипты, забота о тоне общения и измерение успеха по решению проблем клиента. — Владение процессами выпуска, мониторинга, анализа логов и реагирования на инциденты. — Умение ясно писать и работать с неинженерами из операций, комплаенса и юридического отдела. Плюсы: — Опыт работы с Sierra Agent Studio или аналогичными no-code платформами (Decagon, Ada, Kore.ai, Google CCAI, Amazon Lex/Connect). — Опыт с Voice AI: распознавание речи, синтез речи, настройка задержек, обработка прерываний. — Знание систем контакт-центров, таких как Genesys, и проектирование передачи агентам. — Опыт в финтехе или регулируемых отраслях (UDAAP, FDCPA, TCPA, PCI, SOC 2). — Опыт в дизайне разговоров или UX-писательстве. Условия: — Конкурентная зарплата $140K-$180K CAD и опционный план. — Оплачиваемое медицинское, стоматологическое и офтальмологическое страхование. — Гибкий оплачиваемый отпуск. — Возможности профессионального роста и развития. — Оплачиваемый декретный отпуск. — Инициативы по здоровью и благополучию.

Задачи: — Быть гибким техническим ресурсом, который CSM могут привлекать для решения сложных или повторяющихся ситуаций с аккаунтами, которые стандартная поддержка не может решить. — Выполнять краткосрочные технические проекты для клиентов без выделенного Technical Account Manager. — Сотрудничать с CSM для оценки технических потребностей клиентов, участвовать в расследовательских или консультационных звонках и определять следующие шаги. — Руководить оптимизацией платформы: проводить обзоры конфигураций, настраивать лучшие практики и предотвращать повторяющиеся проблемы. — Документировать итоги сессий и последующие шаги в CRM для ясности рекомендаций и видимости для команды. — Консультировать клиентов по неиспользуемым функциям и выявлять возможности для дополнительной продажи или профессиональных услуг. — Передавать сложные ситуации менеджеру по критическим ситуациям или технической поддержке с четкой документацией. — Выявлять системные проблемы и передавать их в команды продукта, инженерии и успеха клиентов для улучшения. Требования: — Опыт не менее 3 лет в технической роли, связанной с клиентами (инфраструктура электронной почты, IT-безопасность/администрирование, инженерия или техническая поддержка) в сфере корпоративного SaaS или кибербезопасности. — Глубокое понимание платформы Abnormal и лучших практик конфигурации, достаточное для самостоятельной работы с клиентами без старшего технического ресурса. — Сильные навыки триажа, способность быстро определять необходимость технической поддержки или привлечения старшего специалиста. — Умение входить и выходить из клиентских взаимодействий по определенным задачам, без постоянного владения аккаунтом. — Способность управлять несколькими параллельными, ограниченными по времени задачами с широким кругом клиентов. — Отличные коммуникативные навыки с техническими и бизнес-стейкхолдерами, включая презентации для старших клиентов. Желательно: — Знание протоколов аутентификации и доставки электронной почты, облачных почтовых платформ (Microsoft 365, Google Workspace). — Опыт работы в модели плавающего/пулового технического ресурса (профессиональные услуги, внедрение, инженерия решений). — Степень бакалавра в технической области или эквивалентный практический опыт.

Задачи: — Анализ рынка, поиск товарных возможностей, расчёт экономики, поиск поставщиков, создание товара и контента, размещение, реклама, аналитика, операционное управление. — Поиск участков, требующих человека и повторяющихся действий, и превращение их в автоматизированные процессы, сервисы или AI-агентов. — Создание систем, которые выполняют 70–90% работы, передавая человеку только спорные решения. — Совместный выбор приоритетных задач с бизнесом по ожидаемому эффекту и сложности внедрения. — Анализ новых маркетплейсов и категорий, поиск быстрорастущих товаров и ниш. — Сбор и нормализация данных из маркетплейсов и внешних источников, конкурентная аналитика. — Поиск аналогов товара и поставщиков, создание AI-агентов для запросов цен и коммуникации с фабриками. — Расчёт полной стоимости поставки и потенциальной прибыльности товара. — Анализ отзывов и поиск возможностей для улучшения продукта. — Генерация и локализация карточек товара под разные страны и площадки. — Автоматизация рекламы и регулярной операционной работы. — Интеграция маркетплейсов, ERP, CRM и аналитических систем, внутренних инструментов и AI-интерфейсов для сотрудников. — Разработка систем Product Hunter для поиска перспективных товаров, оценки экономики и помощи в принятии решений о запуске. Требования: — Опыт работы 3–6 лет. — Знание Python и SQL/PostgreSQL. — Опыт работы с API и интеграциями со сторонними сервисами. — Навыки асинхронной разработки, работы с очередями и фоновыми задачами. — Опыт построения data pipelines. — Владение Docker, Git/CI/CD и работа с облачной инфраструктурой. — Практический опыт работы с LLM API. — Умение оценивать качество AI-систем, обрабатывать ошибки и контролировать стоимость их работы. — Знание structured output, tool calling, агентов и agentic workflows. — Опыт с RAG и embeddings. — Знание MCP, browser automation и мультимодальных моделей. — Навыки мониторинга и отладки AI-систем (например, Langfuse или аналоги). — Product thinking: понимание проблемы бизнеса перед выбором технологии. — Ownership: самостоятельный поиск и обоснование задач, прохождение полного цикла от проблемы до результата. — Скорость разработки: предпочтение быстрому созданию рабочей версии. — Умение работать с неопределённостью, исследовать новые рынки и находить рабочие решения. — Business curiosity: интерес к работе маркетплейсов, структуре прибыли, закупкам, рекламе и ручному труду. Условия: — Полная занятость. — График 5/2. — Удалённый формат работы.

Компания Kodland, онлайн-платформа для обучения детей программированию, ищет AI-инженера для удалённой работы. Кандидат должен иметь более трёх лет опыта в разработке веб-приложений или сервисов, уметь работать с инструментами n8n или Make, а также обладать практическими навыками использования API больших языковых моделей (LLM). Важны уверенные знания REST API и вебхуков, умение управлять проектами и взаимодействовать с отделом кадров. Кроме того, требуется внимательное отношение к финансовым данным и процессам сверки.

Key Requirements: — 3+ years of commercial experience in a relevant role. — Strong expertise in Asterisk (versions 13 and above). — Hands-on experience building and maintaining VoIP solutions for contact centers or fintech environments. — In-depth understanding of SIP and RTP protocols, including NAT and QoS. — Experience configuring and managing SIP trunks. — Experience configuring IVR workflows, agent queues, and skill-based routing, including fallback and overflow logic. — Experience with call recording, CDR, and CEL. — Strong Linux administration skills (Ubuntu/Debian) in production environments. — Practical experience securing VoIP infrastructure, including protection against brute-force attacks, Fail2Ban, firewall configuration, ACLs, and rate limiting. — Experience integrating Asterisk with external systems, including CRM, billing, antifraud solutions, and APIs. — Experience using AMI / ARI to integrate Asterisk with backend systems. — Understanding of financial systems requirements, including reliability, auditability, and logging. — Ability to quickly understand and troubleshoot complex or legacy systems. Responsibilities: — Maintain and continuously improve the company’s telephony platform. — Ensure the stable operation of support, collections, and sales communication channels. — Configure and maintain IVR menus, call queues, and routing logic in line with business processes. — Integrate the telephony platform with internal services, including CRM, backend systems, and billing. — Ensure high availability and minimize system downtime. — Monitor call quality and key performance metrics, including SLA, ASR, and ACD. — Identify and resolve latency and call-quality issues. — Optimize system performance and support infrastructure scaling. — Upgrade and improve the existing VoIP infrastructure. — Create and maintain technical documentation covering call flows, routing, and integrations. — Collaborate with cross-functional teams, including backend, support, and security.

Location: Vienna HQ Workplace: Hybrid ABOUT ROHLIK GROUP Rohlik Group is Europe's leading online grocery delivery service. Using technology, we deliver a weekly shop of 25,000 SKUs in under three hours, in 15-minute delivery slots — giving our customers back their time, freedom and flexibility. We believe the world needs a better food system: more sustainable, more inclusive, and bringing healthier, more personalised food to everyone. In every city we operate, we handpick the best and freshest local produce — from butchers to bakeries — and work directly with farmers through our Farm-to-Door program, alongside the trusted brands and affordable own-label products our customers love.   ABOUT THE TEAM The Automation team designs and implements the innovative processes, equipment and automation solutions that shape Rohlik's fulfillment network. Working closely with local and central teams, we drive scalability, efficiency and innovation across every part of our operations.   THE ROLE As a Process Engineer, you'll own end-to-end improvement projects across our fulfillment network — from spotting a process that's slow, costly or manual, to delivering a live, working solution on the warehouse floor. Your projects will span both hardware (robotics, automated material handling, conveyor and packing systems) and software (control logic and orchestration optimisation), using whichever combination best solves the problem.   What we offer - Salary starting from 5000 Euro gross per month (14 salaries per year) - 3 additional Gurkerl days off - €4 per day towards the canteen - Option to work from home up to 2 days a week - Gurkerl Xtra account with 10% discount in the form of Gurkerl Credits (cashback) - Great discounts via CorporateBenefits (fitness, travel, tickets, shopping, and much more) - Gurkerl Vibe: an international team, flat hierarchies, and an informal culture where mistakes are seen as learning opportunities - Speed & Impact: join an extremely dynamic team where ideas get executed fast, ownership is genuinely lived, and customer value outweighs rigid hierarchies   WHAT YOU'LL DO - Identify improvement potential across the fulfillment network — on the floor, in the data, and with operations teams — wherever automation or process redesign can meaningfully improve cost, throughput, quality or safety - Own the business case for each opportunity: quantify throughput gains and labour impact, calculate payback period, prepare capex/opex estimates, and defend the investment to senior stakeholders - Own the full solution end to end, whatever form it takes — physical automation, software/control changes, or a combination of both - Standardise delivered work into reusable templates, playbooks and best practices that accelerate future projects - Lead implementation from design through testing, installation, integration and piloting, coordinating internal teams, vendors and contractors to deliver a working solution on site - Partner with Procurement and Operations across the full lifecycle — from requirements, RFIs/RFQs, vendor evaluation and commercial negotiation, through to a clean handover with documentation, SOPs, support processes and training for operational teams - Feed insights from delivered projects into the group automation roadmap and warehouse planning concepts - Support site and regional leadership by translating process and performance data into prioritised improvement opportunities WHAT WE'RE LOOKING FOR Required: - Degree in engineering, a technical/analytical field (e.g., mechanical, mechatronics, industrial engineering, logistics), or an equivalent completed vocational training (Ausbildung) / relevant hands-on experience - 3+ years of experience in warehouse automation (e.g., robotics, AMRs, AutoStore, sorters, conveyors, packing systems) and process improvement, including end-to-end project ownership from concept to handover - Strong analytical skills, capable of both spreadsheet business modeling and floor-level process evaluation - Proven project management ability to align Operations, Engineering, Finance, and external vendors - Strong negotiation and engagement skills with third-party vendors and contractors - Broad interest in both the hardware and software sides of automation - Professional working proficiency in English (written and spoken) - Willingness to spend regular time on-site at fulfillment centers Nice to have: - Familiarity with control logic, orchestration software or WMS integration - Working knowledge of Lean or Six Sigma methodologies #LI-FK1 #gurkerl

Location: Berlin, Germany; München, Germany Workplace: Hybrid ABOUT ROHLIK GROUP Rohlik Group is Europe's leading online grocery delivery service. Using technology, we deliver a weekly shop of 25,000 SKUs in under three hours, in 15-minute delivery slots — giving our customers back their time, freedom and flexibility. We believe the world needs a better food system: more sustainable, more inclusive, and bringing healthier, more personalised food to everyone. In every city we operate, we handpick the best and freshest local produce — from butchers to bakeries — and work directly with farmers through our Farm-to-Door program, alongside the trusted brands and affordable own-label products our customers love. ABOUT THE TEAM The Automation team designs and implements the innovative processes, equipment and automation solutions that shape Rohlik's fulfillment network. Working closely with local and central teams, we drive scalability, efficiency and innovation across every part of our operations. THE ROLE As a Process Engineer, you'll own end-to-end improvement projects across our fulfillment network — from spotting a process that's slow, costly or manual, to delivering a live, working solution on the warehouse floor. Your projects will span both hardware (robotics, automated material handling, conveyor and packing systems) and software (control logic and orchestration optimisation), using whichever combination best solves the problem.   WHAT WE OFFER - Unlimited Vacation: Unlimited vacation days for a balanced work-life balance - Tax-Free Benefits: Monthly vouchers of €45 tax-free (via become.1) - Remote Allowance: €20 monthly allowance towards internet costs - Exclusive Shopping Perk: Knuspr Xtra account with 10% cashback in the form of Knuspr Credits - Corporate Discounts: Great discounts via CorporateBenefits (fitness, travel, tickets, shopping, and much more)   WHAT YOU'LL DO - Identify improvement potential across the fulfillment network — on the floor, in the data, and with operations teams — wherever automation or process redesign can meaningfully improve cost, throughput, quality or safety - Own the business case for each opportunity: quantify throughput gains and labour impact, calculate payback period, prepare capex/opex estimates, and defend the investment to senior stakeholders - Own the full solution end to end, whatever form it takes — physical automation, software/control changes, or a combination of both - Standardise delivered work into reusable templates, playbooks and best practices that accelerate future projects - Lead implementation from design through testing, installation, integration and piloting, coordinating internal teams, vendors and contractors to deliver a working solution on site - Partner with Procurement and Operations across the full lifecycle — from requirements, RFIs/RFQs, vendor evaluation and commercial negotiation, through to a clean handover with documentation, SOPs, support processes and training for operational teams - Feed insights from delivered projects into the group automation roadmap and warehouse planning concepts - Support site and regional leadership by translating process and performance data into prioritised improvement opportunities WHAT WE'RE LOOKING FOR Required: - Degree in engineering, a technical/analytical field (e.g., mechanical, mechatronics, industrial engineering, logistics), or an equivalent completed vocational training (Ausbildung) / relevant hands-on experience - 3+ years of experience in warehouse automation (e.g., robotics, AMRs, AutoStore, sorters, conveyors, packing systems) and process improvement, including end-to-end project ownership from concept to handover - Strong analytical skills, capable of both spreadsheet business modeling and floor-level process evaluation - Proven project management ability to align Operations, Engineering, Finance, and external vendors - Strong negotiation and engagement skills with third-party vendors and contractors - Broad interest in both the hardware and software sides of automation - Professional working proficiency in English (written and spoken) - Willingness to spend regular time on-site at fulfillment centers Nice to have: - Familiarity with control logic, orchestration software or WMS integration - Working knowledge of Lean or Six Sigma methodologies #LI-FK1 #knuspr

Location: Prague, Czech Republic Workplace: Hybrid Rohlik Group is Europe's leading online grocery delivery service. Using technology, we deliver a weekly shop of 25,000 SKUs in under three hours, in 15-minute delivery slots — giving our customers back their time, freedom and flexibility. We believe the world needs a better food system: more sustainable, more inclusive, and bringing healthier, more personalised food to everyone. In every city we operate, we handpick the best and freshest local produce — from butchers to bakeries — and work directly with farmers through our Farm-to-Door program, alongside the trusted brands and affordable own-label products our customers love.   ABOUT THE TEAM The Automation team designs and implements the innovative processes, equipment and automation solutions that shape Rohlik's fulfillment network. Working closely with local and central teams, we drive scalability, efficiency and innovation across every part of our operations.   THE ROLE As a Process Engineer, you'll own end-to-end improvement projects across our fulfillment network — from spotting a process that's slow, costly or manual, to delivering a live, working solution on the warehouse floor. Your projects will span both hardware (robotics, automated material handling, conveyor and packing systems) and software (control logic and orchestration optimisation), using whichever combination best solves the problem.   WHAT YOU'LL DO - Identify improvement potential across the fulfillment network — on the floor, in the data, and with operations teams — wherever automation or process redesign can meaningfully improve cost, throughput, quality or safety - Own the business case for each opportunity: quantify throughput gains and labour impact, calculate payback period, prepare capex/opex estimates, and defend the investment to senior stakeholders - Own the full solution end to end, whatever form it takes — physical automation, software/control changes, or a combination of both - Standardise delivered work into reusable templates, playbooks and best practices that accelerate future projects - Lead implementation from design through testing, installation, integration and piloting, coordinating internal teams, vendors and contractors to deliver a working solution on site - Partner with Procurement and Operations across the full lifecycle — from requirements, RFIs/RFQs, vendor evaluation and commercial negotiation, through to a clean handover with documentation, SOPs, support processes and training for operational teams - Feed insights from delivered projects into the group automation roadmap and warehouse planning concepts - Support site and regional leadership by translating process and performance data into prioritised improvement opportunities WHAT WE'RE LOOKING FOR Required: - Degree in engineering, a technical/analytical field (e.g., mechanical, mechatronics, industrial engineering, logistics), or an equivalent completed vocational training / relevant hands-on experience - 3+ years of experience in warehouse automation (e.g., robotics, AMRs, AutoStore, sorters, conveyors, packing systems) and process improvement, including end-to-end project ownership from concept to handover - Strong analytical skills, capable of both spreadsheet business modeling and floor-level process evaluation - Proven project management ability to align Operations, Engineering, Finance, and external vendors - Strong negotiation and engagement skills with third-party vendors and contractors - Broad interest in both the hardware and software sides of automation - Professional working proficiency in English (written and spoken) - Willingness to spend regular time on-site at fulfillment centers Nice to have: - Familiarity with control logic, orchestration software or WMS integration - Working knowledge of Lean or Six Sigma methodologies WHAT’S IN IT FOR YOU - Fair reward - You’ll get a strong fixed salary — no bonus games, no politics. Great work is rewarded clearly and fairly. - Good food every day - You’ll enjoy a free lunch every day and fresh fruit & veggies in the office. Because good food fuels great work. - Life, not just work - You’ll have real flexibility – three days in the office, 2 days Home Office where it suits you. And unlimited paid vacation based on trust. - Personal growth - You’ll grow as fast as Rohlik does. Every challenge is a chance to learn and make an impact. - Real impact - What you do here matters. You’ll see your work changing how people eat and live — from day one. - Recognition among colleagues - Your effort won’t go unnoticed. You can recognise others (and be recognised) through peer credits to use in our internal cafeteria. - Xtra membership - You’ll get free Xtra membership and 10% cashback on everything you buy on Rohlik.cz http://Rohlik.cz. - Sport & wellbeing - You’ll stay active with company sports challenges or a subsidised Multisport card. - A team that sticks together - You’ll work with people who move fast, support each other and celebrate wins together. - If this sounds like you…You’re someone who takes ownership, acts fast and gets things done. Ready to bake something great with us? #LI-FK1

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. An overview of this role We're looking for an Intermediate Site Reliability Engineer to join the Cells Infrastructure team in GitLab's Scale & Architecture organization. In this role, you'll help build and operate Cells, the architecture that lets GitLab.com scale horizontally. Cells splits GitLab.com into many independent units, each with its own application and data stack, behind a shared routing layer. This is a build-it-and-run-it role. You'll provision cells, route traffic to them, deploy them safely, and keep them reliable in production. You'll also help move customer organizations onto Cells, one of GitLab's most important scaling initiatives. What you'll do Operate Cells in production: join the on-call rotation, respond to incidents, lead post-incident reviews, and drive corrective actions to completion. Define and monitor service level objectives (SLOs) for routing and cell health, and build the dashboards, alerts, and runbooks behind them. Provision and operate cell infrastructure on Amazon Web Services (AWS) and Google Cloud Platform (GCP), including Kubernetes, networking, Identity and Access Management (IAM), PostgreSQL, Redis, and object storage. Develop infrastructure as code with Terraform, Helm, and GitOps tooling such as Argo CD. Operate and extend the global routing layer, built on Cloudflare Workers, Envoy, and a Go service backed by Cloud Spanner, and expand routing to more protocols and services. Improve the continuous integration and continuous delivery (CI/CD) pipelines behind ring-based deployments, covering promotion, database migrations, quality assurance validation, and rollback. Support organization migrations by preparing destination cells and helping with dry runs and production cutovers. Work with product teams to make their services cell-compatible, and write documentation so others can operate Cells with confidence. Take part in on-call or operational support where your team’s ownership model requires it. What you'll bring Professional experience running production infrastructure at scale on AWS, GCP, or both, including Kubernetes, along with strong Terraform and Helm skills. Proficiency in Go, or strong experience in another systems language and willingness to work in Go daily. Solid grounding in site reliability engineering (SRE) best practices: SLOs and error budgets, blameless post-incident reviews, reducing toil through automation, capacity planning, and designing for graceful degradation. Experience owning services in production, including on-call, incident response, and monitoring with tools such as Prometheus and Grafana. Practical knowledge of progressive delivery: how to roll changes safely across a fleet and how to roll them back. A strong understanding of distributed-systems fundamentals, such as request routing, proxies, consistency, and failure domains. Experience working effectively in distributed, all-remote teams: you default to asynchronous, written-first communication, document decisions in issues and merge requests, hand off work cleanly across time zones, and stay transparent about progress and blockers. Experience with Cloudflare, Spanner, Argo CD, TypeScript, or operating GitLab at scale is a plus, not a requirement. About the team Every team in our organization owns its services end to end, from design through on-call.We own the control plane that tracks cells and decides where each request belongs, and keep the fleet in step with GitLab's release cadence.We work closely with delivery, database, migration, and product teams across GitLab. Feature teams own how their services behave on the platform; we own the underlying infrastructure.We're an all-remote, asynchronous team. We make decisions in GitLab issues, use directly responsible individuals (DRIs) to own technical direction, demo our work weekly, and use AI-assisted workflows every day. 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 .

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Software Engineer, ML Platform, you will work on our ML Data Team and be instrumental in architecting, implementing, and maintaining foundational ML infrastructure powering Feeds Ranking, Content Understanding, Recommendations, Ads, and much more to fulfill Reddit’s mission of bringing community and belonging to everyone in the world. You will create ML data-governance tools that help MLEs discover and reason about signals, while contributing across the broader ML data platform—including prediction logging and training data systems. Lead the design, development, testing, and operation of ML signal-governance capabilities that help MLEs discover signals and understand their ownership, lineage, quality, and usage. Build tools that help teams assess signal importance and make informed lifecycle decisions. Partner with MLEs and cross-functional teams to define governance workflows and deliver reliable, intuitive ways to explore and act on signal metadata. Contribute across the ML Data Platform, including prediction logging and training data platforms, to design, develop, test, and operate batch and streaming pipelines processing petabyte-scale data. Drive complex projects end to end from technical planning and design through implementation, testing, rollout, and ongoing operation. Who You Might Be: 5+ years of experience in the ML Platform domain. Strong customer focus and experience driving projects from requirements to production in close collaboration with multiple cross-functional partners (XFN). Experience with large-scale batch and streaming data processing. Experience building production-quality systems with testing, monitoring, observability, and reliability practices. Deep understanding of distributed systems and data-intensive architectures, with strong communication and collaboration skills. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700 — $303,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.