Вакансии

Ищем Python-разработчика / AI Engineer уровня Middle+ / Senior на проект по автоматизации обработки и сверки финансовых документов. Проект связан с разработкой сервиса, который будет принимать акты сверки и внутренние выгрузки, извлекать из них данные, сопоставлять документы, находить расхождения и формировать понятный результат для пользователя. Задачи: — Разбирать и обрабатывать документы в форматах Excel, PDF и сканы. — Извлекать табличные данные из документов. — Нормализовать даты, номера документов, суммы и другие поля. — Проектировать и реализовывать логику сопоставления данных. — Выявлять расхождения между двумя источниками. — Обрабатывать сложные кейсы: разные периоды, отличающиеся номера, частичные совпадения и другие неоднозначные ситуации. — Интегрировать OCR и Document AI-инструменты. — При необходимости использовать LLM для интерпретации и формирования человекочитаемых объяснений. — Разрабатывать backend/API для сервиса. — Участвовать в проектировании архитектуры MVP. — Работать с реальными обезличенными финансовыми документами и тестировать качество решения на исторических данных. Требования: — Коммерческий опыт разработки на Python от 3 лет. — Уверенное владение Python. — Опыт работы с pandas и табличными данными. — Опыт обработки Excel / CSV. — Опыт парсинга PDF. — Опыт разработки backend-сервисов и REST API. — Понимание алгоритмов сопоставления, нормализации и очистки данных. — Умение проектировать решение самостоятельно, а не только работать по готовому ТЗ. — Опыт работы с Git. Будет большим плюсом: — Опыт с OCR: Tesseract, PaddleOCR или аналогами. — Опыт с PyMuPDF, pdfplumber, Camelot, Tabula. — Опыт с fuzzy matching. — Опыт работы с Document AI / Intelligent Document Processing. — Интеграция LLM API: OpenAI, Azure OpenAI, YandexGPT или аналогов. — Опыт разработки систем reconciliation / data matching. — Опыт работы с финансовыми, бухгалтерскими или другими структурированными документами. — Опыт On-Premise решений. — Опыт построения решений, где нужно сочетать детерминированную бизнес-логику и AI. Что здесь не требуется: — Мы не ищем классического Data Scientist и не планируем обучение собственных ML-моделей с нуля. В проекте важнее: — сильная прикладная Python-разработка; — работа с документами и данными; — построение надежной логики сопоставления; — понимание, где действительно нужен AI, а где лучше использовать обычные алгоритмы. О проекте: — На первом этапе планируется разработка MVP без глубокой интеграции с внутренними учетными системами. — Базовый сценарий: пользователь загружает акт сверки и внутреннюю выгрузку, система извлекает и нормализует данные, выполняет сопоставление, показывает совпадения и расхождения, формирует структурированный результат для пользователя. — Ожидаемый результат — рабочий прототип, который можно проверить на реальных исторических данных. Условия: — Удалённая работа. — Проектная занятость / аутстафф. — Возможна полная или частичная загрузка — обсуждается индивидуально. — Проект стартует с этапа MVP, с возможностью продолжения. — Работа в составе небольшой проектной команды. Ожидаемый уровень: Middle+ / Senior Нам нужен специалист, который сможет самостоятельно разобраться в предметной области, предложить техническое решение и довести его до рабочего результата. Будет преимуществом в отклике: — опыт похожих задач: обработка документов, OCR, reconciliation / matching, financial data processing, Document AI, LLM-интеграции. — указание текущей доступности, возможной загрузки в часах в месяц, часовой ставки, формата работы (ИП / самозанятый / другой).

Location: Hyderabad, Telangana, India About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role: Forward-Deployed AI Engineer — Enterprise AI Location: Hyderabad, India Experience Level: 8+ years Work Model: Hybrid, 3 days per week in office Employment Type: Full Time Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you’ll define the frontier by building beyond it. You’ll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world’s leading enterprises. As a Forward-Deployed AI Engineer, you’ll own outcomes end to end—from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You’ll develop generative AI solutions in the real world, driving measurable impact and return on investment within large institutions. Enterprise AI is intense, intellectually challenging work. It won’t be for everyone, but it may be exactly the challenge you’re looking for. As a Forward-Deployed Engineer, You Will Find the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate complex business needs into clear technical direction. This requires curiosity and business acumen as you discover business workflows and jointly define the outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems, from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Own the Outcome You won’t simply be given a list of responsibilities—you’ll have the authority to own the outcome for your client and make a real-world impact through your work. You’ll lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. You’ll work with clients who have uncompromising expectations for quality, making this a demanding environment—and an ideal proving ground for people who seek difficult, high-impact challenges. Client-first and hybrid: This role is based in Bengaluru or Hyderabad and requires working from the office three days per week. Candidates must currently be based in one of these two cities. Relocation assistance is not available. You’ll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you’ll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Deep production engineering experience: Typically 8+ years building and operating sophisticated software systems, with expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure. Hands-on agentic AI experience: Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows. Strong retrieval depth: Experience building and improving production retrieval systems, with a practical understanding of embeddings, vector and hybrid search, reranking, evaluation, and diagnosing retrieval quality. End-to-end systems ownership: A track record of taking complex systems from architecture through deployment and scale, with a practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost. Exceptional customer and technical leadership: The ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, challenge assumptions constructively, and communicate effectively with senior engineers and business executives. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: Bengaluru, Karnataka, India About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role: Forward-Deployed AI Engineer — Enterprise AI Location: Bengaluru, India Experience Level: 8+ years Work Model: Hybrid, 3 days per week in office Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you’ll define the frontier by building beyond it. You’ll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world’s leading enterprises. As a Forward-Deployed AI Engineer, you’ll own outcomes end to end—from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You’ll develop generative AI solutions in the real world, driving measurable impact and return on investment within large institutions. Enterprise AI is intense, intellectually challenging work. It won’t be for everyone, but it may be exactly the challenge you’re looking for. As a Forward-Deployed Engineer, You Will Find the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate complex business needs into clear technical direction. This requires curiosity and business acumen as you discover business workflows and jointly define the outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems, from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Own the Outcome You won’t simply be given a list of responsibilities—you’ll have the authority to own the outcome for your client and make a real-world impact through your work. You’ll lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. You’ll work with clients who have uncompromising expectations for quality, making this a demanding environment—and an ideal proving ground for people who seek difficult, high-impact challenges. Client-first and hybrid: This role is based in Bengaluru or Hyderabad and requires working from the office three days per week. Candidates must currently be based in one of these two cities. Relocation assistance is not available. You’ll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you’ll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Deep production engineering experience: Typically 8+ years building and operating sophisticated software systems, with expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure. Hands-on agentic AI experience: Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows. Strong retrieval depth: Experience building and improving production retrieval systems, with a practical understanding of embeddings, vector and hybrid search, reranking, evaluation, and diagnosing retrieval quality. End-to-end systems ownership: A track record of taking complex systems from architecture through deployment and scale, with a practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost. Exceptional customer and technical leadership: The ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, challenge assumptions constructively, and communicate effectively with senior engineers and business executives. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: Zurich, Switzerland 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: 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.

We're building AI agents for performance marketing. Plurio, the AI agent for media buying teams running $300K–$15M/month on Google, Meta, and TikTok. It connects to your internal backend data and your ad accounts, automates analysis and optimization, saves 50% of time, and boosts ROAS by 10–30%. Our agents already run $500M+/year in ad spend. Since our public release in March, our customer base has grown 4× in 10–12 weeks. Our goal is the autonomous user acquisition factory that runs 10× better than anything before, growing budgets under management to $30B/year. Задачи: — Вы будете руководить командой и агентом, отвечать за рост клиентских метрик. — Улучшать и обучать агента, формировать методологию его работы: как он читает данные, анализирует сигналы, автоматизирует решения и действия, взвешивает параметры. — Встраивать логику медиабаинга в рабочие процессы и правила агента. — Собирать лучшие практики из собственного опыта, клиентского портфеля и рынка, адаптировать их для агента и клиентов разных вертикалей. — Совершенствовать агента совместно с продуктовой командой и AI маркетинговыми инженерами. — Работать с клиентским портфелем: обучать команды клиентов работе с агентом, улучшать и контролировать рабочие процессы, правила и процессы внутри агента для роста метрик клиентов. — Общаться с руководителями по привлечению пользователей, CMO и лидерами перформанс-маркетинга клиентов, обучать их, разбирать кейсы, находить новые задачи для агента. — В случае, если агент управляет рекламой клиента, вы вместе с агентом и AI маркетинговыми инженерами становитесь командой клиента по Meta Ads, определяете логику и механику работы. Требования: — Опыт управления рекламным бюджетом в Meta от $1M в месяц. — Опыт разработки стратегии, структуры, подходов к тестированию, автоматизации и найму команды, как лично, так и через команду. — Глубокое понимание работы Meta: сигналы, аукционы, структура аккаунтов, логика оптимизации. — Опыт управления командой из минимум 3-4 человек: медиабаеры, аналитики, креативные продюсеры. — Умение объяснять логику и механику работы команде и отстаивать решения на уровне CMO. — Опыт работы с автоматизацией: создание собственной или интеграция внешних сервисов, понимание CPA, правил масштабирования и остановки, логики принятия решений. — Знание потребительских воронок: мобильные, веб, web-to-app, app-to-app, особенности окон конверсии, задержек атрибуции и отслеживания доходов. — Опыт создания или соучастия в создании креативной фабрики для Meta: анализ, механика тестирования и генерация. — Свободное владение английским языком, уверенное общение и письменная коммуникация с англоязычными клиентами. Условия: — Работа в команде, использующей AI-агентов во всех функциях: инженерия, продажи, операции, клиентские проекты. — Обучение использованию и созданию агентов, интеграция вашего опыта в них. — Прямая работа с основателями и руководством компании. — Компенсация до $15K в месяц, включая базовую часть и бонусы за результат.

О компании Мы компания-разработчик экосистемы Directum. Наши решения помогают комплексно управлять крупными компаниями на всех уровнях: от стратегических целей до конкретных задач на местах. Более 3500 компаний используют наши решения. Чем предстоит заниматься Разрабатывать решение Directum Projects для организации командной работы, планирования проектов и ресурсов, управления базами знаний. Наше решение заменяет Asana, Jira, Trello, Confluence, MS Project. Основные инструменты и технологии Backend: ASP.Net Core. Frontend: TypeScript, React, WebPack. Работа с данными: MS SQL Server, PostgreSQL. Инструменты разработки: MS Visual Studio, VS Code. Инфраструктура: Docker, Docker-compose, Python. Работа с задачами и кодом: Gitlab, Git. Команда не ограничена в выборе технологий. Использует те, которые лучше всего подходят для решения конкретной задачи. Ожидания от кандидата Опыт разработки на React от 5 лет. Базовый опыт backend-разработки на C#. Опыт разработки трехзвенных приложений и оптимизации клиентской и серверной части. Умение быстро изучать новые технологии и применять их на проекте. Приветствуется Опыт работы по Agile. Опыт работы с ORM — NHibernate или Entity Framework. Опыт работы в соответствии с Continuous Integration. Почему к нам стоит идти Работа в команде профессионалов. Для каждого из нас, программирование не только работа, но и главное увлечение в жизни. Наставничество. Для новичков у нас есть обучающие программы, помогающие лучше узнать нашу систему и без стресса погрузиться в работу. Возможность развития. Собираем свои митапы, выступаем на крупных ИТ-конференциях, проводим мозговые штурмы и инженерные дни. Выделяем рабочее время на внутреннее обучение. Команда отвечает за фичи. Разработчики сами определяют сроки реализации, архитектуру и способы выполнения задач. Выделяется время на исследование и прототипирование. Заботимся о качестве кода. Выделяем время на рефакторинг, техдолг, code review, анализ производительности. Гибкий график и нет переработок. Мы уважаем личное время своих сотрудников. Заработная плата обсуждается индивидуально. Мы аккредитованная ИТ-компания, возможна бронь/отсрочка при соблюдении необходимых условий Минцифры.

Задачи: — Проектирование целевой и переходной архитектуры стрима Ипотеки — Участие в развитии, масштабировании и сопровождении текущих решений с ориентацией на надёжность, расширяемость и соответствие бизнес-целям — Взаимодействие с командами разработки, архитекторами других доменов и заинтересованными сторонами — Актуализация архитектурной документации, проведение технических оценок и архитектурных демо и митапов Требования: — Не менее 5-ти лет опыта в роли Solution / Software / System Architect либо Tech Lead с архитектурной ответственностью — Опыт проектирования высоконагруженных и отказоустойчивых систем: желательно с пользовательской базой от 1 млн клиентов, нагрузкой от 500+ RPS, и SLA по доступности 99.9%+ — Глубокое понимание микросервисной архитектуры и (желательно) микрофронтов, принципов модульности, API-ориентированной интеграции, стратегий масштабирования и изоляции доменов — Знание нотаций BPMN и ArchiMate для документирования процессов и архитектурных решений — Опыт участия в архитектурных ревью, архитектурного надзора, ведения технологического долга — Опыт работы с актуальным технологическим стеком Будет плюсом: — Навыки разработки прототипов и PoC-решений, проведения R&D — умение быстро собирать прототипы для проверки архитектурных гипотез Стек: — Backend: Java + Spring Boot — Frontend: JavaScript + React — Мобильная разработка: знание архитектур нативных мобильных приложений — Контейнеризация и оркестрация: Kubernetes — Хранение данных: PostgreSQL, Cassandra, Redis, MinIO — Асинхронное взаимодействие: Kafka, ArtemisMQ — Camunda 8 Stack — ключевой компонент, обеспечивающий оркестрацию платёжных процессов

Задачи: — улучшение решений в области Data Science — обеспечение качества и производительности моделей машинного обучения Требования: — опыт в QA, преимущественно в backend тестировании, с сильным владением Python (Pytest) для написания и поддержки автоматизированных тестов не менее 3 лет — опыт работы с Linux и сопутствующими инструментами — уверенные знания Bash скриптинга — понимание принципов Docker/Kubernetes, базовые знания CI/CD — умение анализировать логи backend сервисов, включая использование Open Lens или аналогичных инструментов — опыт работы с Kafka и Kibana или готовность быстро их освоить — навыки тестирования RESTful и gRPC API — уровень английского от Intermediate и выше

Задачи: — Разрабатывать продукты с нуля и на базе MVP — Проектировать архитектуру и принимать технические решения — Работать с frontend, backend, базами данных, API и интеграциями — Управлять AI-агентами и проверять сгенерированный код — Настраивать инфраструктуру и деплой — Анализировать логи и устранять ошибки — Отвечать за продукт от прототипа до production Требования: — Опыт работы с Claude, Replit, Cursor, Codex, Vercel, Figma Make или аналогами — Умение проверять и дорабатывать AI-сгенерированный код — Навыки работы с frontend, backend, базами данных, API, S3, деплоем — Владение Git — Знания в области авторизации, прав доступа, безопасности секретов — Опыт работы с доменами, SSL, окружениями и деплоем — Способность самостоятельно разбираться в бизнес-задачах и предлагать решения — Понимание производительности и масштабируемости Будет плюсом: — Опыт запуска продуктов в production — Знания CI/CD и мониторинга — Опыт работы с несколькими AI-агентами — Опыт в нескольких направлениях разработки Условия: — Работа в офисе в Москве, м. Бутырская / Фонвизинская — График 5/2 — Официальное оформление, самозанятость или другой формат — Зарплата 130 000 ₽ в месяц В отклике обязательно ответить: — Какие приложения разрабатывали + ссылки — Какие AI-инструменты используете — Готовы ли работать в офисе — Какое приложение последним собрали с AI и за сколько времени

Location: Hong Kong, Hong Kong SAR OKX will be prioritising applicants who have a current right to work in Hong Kong, and do not require OKX's sponsorship of a visa. Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Opportunity We are looking for talented, impact-driven Mobile Engineers to join our engineering organization in Hong Kong. In this role, you will build and scale high-performance, resilient native mobile applications that power OKX’s core product ecosystems—ranging from high-concurrency payment and trading engines to user acquisition, engagement, and product growth systems. You will work on cross-functional engineering challenges at global scale, partnering closely with product design, backend architecture, security, and regional teams. What You'll Be Doing Build & Scale Native Mobile Apps: Design, develop, and maintain modular, reliable native mobile features (iOS or Android) used by millions of global users. Architect Core Systems: Drive technical decision-making on mobile architecture, API design, performance optimization, and offline/network resiliency. Collaborate Cross-Functionally: Partner closely with Product Management, Design, and Backend Engineering to translate complex user and commercial requirements into intuitive, reliable mobile experiences. Ensure Quality & Rigor: Write clean, testable, and maintainable code while maintaining high engineering standards for code reviews, testing, security, and monitoring. Integrate AI Workflows: Apply AI coding tools actively in your workflow—not only for code generation, but also to build and maintain repeatable personal AI development workflows. Modernize Engineering Tooling: Leverage modern development tools, automated CI/CD pipelines, and productivity workflows to maintain rapid iteration speeds. What We Look For In You Solid software engineering fundamentals with hands-on experience building, shipping, or maintaining production native mobile applications (iOS with Swift/Objective-C or Android with Kotlin/Java). Strong understanding of mobile system design, clean architecture, memory management, testing, and performance tuning. Ability to actively apply AI coding tools in your workflow and continuously optimize personal engineering productivity. Problem-solving mindset with the ability to take ownership of end-to-end features and drive execution independently. Nice-To-Haves Experience in fintech, crypto, digital payments, high-concurrency consumer apps, or growth systems. Familiarity with mobile architecture patterns, CI/CD pipelines, experimentation frameworks, or attribution tools. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! #LI-ML1 #LI-ONSITE Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Требования: — 5+ лет опыта в QA, преимущественно с backend-приложениями — 2+ года опыта устранения неполадок в Java-приложениях — Strong English (B1+) и русский язык О компании: Spotware — финтех компания, специализирующаяся на разработке продуктов для брокеров, банков и трейдеров. Условия: — Работа на Кипре — Помощь с релокацией

Задачи: — Разрабатывать и поддерживать Android-приложения на Kotlin — Реализовывать новый функционал и дорабатывать существующие решения — Участвовать в проектировании архитектуры и обсуждении технических решений — Интегрировать REST API и взаимодействовать с backend-разработчиками — Оптимизировать производительность приложений и повышать качество пользовательского опыта, писать поддерживаемый, читаемый код, участвовать в code review — Исправлять ошибки, проводить отладку и участвовать в тестировании приложений — Работать в кросс-функциональной команде с разработчиками, дизайнерами, аналитиками и QA Требования: — От 2 лет коммерческого опыта Android-разработки — Уверенное владение Kotlin и Android SDK — Опыт разработки приложений с использованием Jetpack Compose — Практический опыт работы с Kotlin Coroutines — Понимание принципов ООП, SOLID и популярных архитектурных подходов (MVVM/MVI) — Умение анализировать задачи, предлагать решения и работать в команде Условия: — Формат работы: удалённо, гибридно или из офиса на выбор

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. 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. About the role As a Staff Backend Engineer, you will provide technical leadership across your team and adjacent teams, solving the highest-scope and most complex problems in your area. You will lead large, cross-cutting backend initiatives, drive our modular architecture strategy, and define the standards that let teams move faster without compromising quality, security, reliability, or operability. This is a technical leadership role that combines deep backend expertise, systems judgment, product judgment, and influence across organizational boundaries. You will work with Product, Frontend, Infrastructure, Security, Data, Engineering Managers, and engineers across product groups, bringing subject matter expertise, and you will do it without relying on formal authority. Why you’ll love this role Leverage: Your work multiplies across teams. The platforms, standards, and architectural decisions you lead determine how quickly everyone else can ship. Genuinely Hard Problems: You’ll lead the modernization of a large monolith toward modular, reusable, appropriately independent systems — at the scale of a platform used by millions of users. Influence Without Bureaucracy: You’ll shape technical direction across teams through clear written proposals and decision records, and partner with Product and Engineering leadership on platform roadmap and investment trade-offs. Frontier AI Work: You’ll lead adoption of AI-assisted and agentic engineering workflows and define the review, quality, security, and privacy guardrails that make them safe to rely on. Autonomy: You’ll thrive in our remote-first, asynchronous organization, where clear written communication and self-direction are the pillars of success. What you’ll do Lead Cross-Cutting Initiatives: Lead the technical design and delivery of large backend initiatives that span teams, and identify and remove systemic bottlenecks across product and infrastructure groups. Own Architecture Strategy: Drive modular backend, service, data, and platform architecture. Lead modernization of the monolith and legacy backends toward modular, reusable, and appropriately independently operated systems — while preventing fragmentation and service sprawl. Set the Standards: Define and improve standards for APIs, contracts, compatibility, schema evolution, testing, security, performance, observability, operability, and maintainability — plus the build, test, deploy, release, rollback, and production-readiness practices needed to operate modular features safely. Establish Shared Patterns: Create the patterns for dependency management, data ownership, eventing, failure isolation, service maturity, and operational documentation. Establish Go service patterns and Kubernetes operating practices where they matter to our production estate, and guide Rust adoption where it solves a real systems, security, performance, or supply-chain problem. Own What You Build in Production: Take part in on-call and incident response for the systems your teams own, act as a technical escalation point during complex incidents, and turn what you learn into architectural and operational improvements that prevent recurrence. Influence and Partner: Shape technical direction across teams without formal authority, and partner with Product and Engineering leadership on platform-level roadmap decisions and investment trade-offs. Grow Engineers: Mentor Senior and Intermediate engineers, shepherd technical debt reduction and reusable patterns that improve throughput, and raise the technical capability of the wider team. Lead AI Adoption: Lead team-level adoption of AI-assisted and agentic workflows, including the quality, security, privacy, and operational guardrails, and help engineers direct, validate, reject, and course-correct agent output. On-Call Support: Take part in on-call or operational support where your team’s ownership model requires it. What you’ll bring Cross-Team Technical Leadership: A sustained record of technical leadership across more than one team or a broad product area. Deep Architecture Experience: Deep backend architecture and production experience in complex applications, services, or platforms, including scaling or governing APIs, service platforms, data systems, modular monoliths, or shared backend components. Modularization in Production: Experience modernizing a monolith or legacy backend architecture in production, and with modular architecture such as bounded contexts, package encapsulation, ports and adapters, service extraction, event-driven boundaries, or an equivalent approach. Influence Without Authority: A strong ability to create alignment through clear written proposals and decision records, so decisions are documented, understood, and adopted without constant escalation. Product Judgment: The ability to balance customer outcomes, delivery speed, technical health, reliability, and long-term platform investment. Mentorship: Experience mentoring engineers and shaping standards through code review, documentation, and example. Agentic AI Leadership: Production experience with AI-assisted or agentic engineering workflows, including the ability to evaluate and improve how a team adopts them. Helpful experience Go services and APIs at scale. Kubernetes and cloud-native operations, including deployment, scaling, observability, rollback, and production readiness. Rust adoption or production ownership for systems, security, performance, or platform components. Ruby/Rails modularization and large-monolith modernization. PostgreSQL scaling, data partitioning, queues, messaging, or distributed systems. Security-sensitive product or software supply chain engineering. Experience across SaaS, single-tenant, self-managed, or air-gapped deployment constraints. 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: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As Claude's capabilities grow, so does our responsibility to ensure those capabilities reach the right people. The Access Programs team builds the systems that verify who our customers are, grant access to advanced model capabilities for approved use cases, and ensure that access is not misused. As a software engineer on this team, you will build the identity, vetting, and access management infrastructure that underpins our trusted access programs, along with the monitoring and enforcement tooling that keeps them safe. This work sits at the center of how Anthropic deploys frontier capabilities responsibly, balancing broad access with rigorous safeguards. Responsibilities: Build identity verification and vetting systems (KYC/KYB) that establish who our individual and business customers are Design and implement access control systems that grant, scope, and revoke access to advanced capabilities based on approved use cases Build infrastructure to configure safety systems and detection thresholds on a per-customer basis for trusted access programs Develop monitoring to detect misuse of expanded access, and tooling that enables enforcement teams to act on it Partner closely with policy, enforcement, threat intelligence, product, research, and go-to-market teams so that access decisions are well-informed and consistently applied Build systems that identify account compromise and takeover, apply mitigations in real time, and carry affected accounts through to full remediation Design and build the dashboards, alerting, and internal admin tooling that give the team and its partners clear visibility into the health and outcomes of our access programs Integrate with third-party identity verification and data enrichment vendors You may be a good fit if you have: A Bachelor's degree in Computer Science, Software Engineering, or comparable experience Experience building and operating backend systems in production Strong coding skills in at least one general-purpose programming language, and experience building software with AI coding tools Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Care about the societal impacts of AI and want your work to make powerful systems safer Strong candidates may also: 8+ years of industry software engineering experience Experience building shared platforms or foundational services that many teams and products depend on, rather than one-off solutions for a single use case A track record of working across functions (for example engineering, product, policy, operations, and go-to-market) to gather requirements, reconcile competing needs, and drive adoption of what you build Experience with identity, authentication, or authorization systems at scale Experience with KYC/KYB workflows or identity verification vendors Experience in trust and safety, integrity, fraud, or abuse detection Experience detecting and responding to account takeover or credential compromise Experience partnering with operational teams to build custom internal tooling The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Задачи: — Разрабатывать и поддерживать frontend и backend — Создавать адаптивные интерфейсы — Разрабатывать API, backend-сервисы и работу с БД — Работать с лекарствами, рецептами, клиентами, заказами и инвентаризацией — Реализовывать аутентификацию и управление доступом — Интегрировать сторонние сервисы и API — Тестировать, дебажить и оптимизировать продукт — Обеспечивать безопасность и защиту данных Требования: — Коммерческий опыт Full Stack разработки — JavaScript / TypeScript, HTML, CSS — Современные frontend-фреймворки — Опыт backend-разработки — Базы данных и API — Git — Понимание безопасности веб-приложений — Хорошие коммуникационные навыки Условия: — Рабочая виза и разрешение на работу за счёт компании — Ежемесячный рабочий кредит €100 — Медицинская страховка — Спортивные льготы после испытательного срока — Пн–Чт: 09:00–18:00 — Пт: 09:00–15:00

Location: New York, NY (HQ) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. Explore our Engineering Blog https://builders.ramp.com & Emerging Talent https://builders.ramp.com/emerging-talent Blog to learn more about how we build at Ramp and what it’s like to start your career here. ABOUT THE ROLE Ramp is, at its core, an engineering company, and is on a mission to build the best engineering team in the US! We are looking for iOS interns (12 or 16 weeks) who are excited to be part of our story and help us build a diverse and vibrant tech community. We hire engineers with a broad set of technical skills, who are highly cross-functional, and eager to solve a wide range of engineering challenges. Our ideal candidate has a strong sense of ownership and enjoys owning projects from inception to scaling them in production. We value people who take pride in their work, and show an aptitude for learning quickly whether they’re familiar with our stack or not. You'll be working with a nimble team of committed and talented engineers and having a large, long-term impact on technical design and engineering culture. WHAT YOU’LL DO - Build and ship new features for Ramp’s iOS app - Work alongside experienced engineers and contribute to our mobile codebase - Collaborate with Product and Design to bring new features and experiences to life - Learn from customer feedback and help continuously improve our product - Contribute to engineering tools and processes that help the team move quickly and scale WHAT YOU’LL NEED - Currently pursuing a B.S. or higher in Computer Science or a related technical field, graduating December 2027 or later - Experience with Swift and/or iOS development through internships, coursework, or personal projects - Strong programming fundamentals and understanding of mobile development concepts - Experience building a mobile app, feature, or relevant project - Ability to turn product ideas into thoughtful engineering solutions - Desire to learn quickly, take ownership, and work in a fast-paced environment NICE TO HAVES - Experience with SwiftUI - Familiarity with mobile design patterns and best practices - Experience shipping an iOS app or feature to real users - Exposure to technologies in our mobile stack, including Swift Concurrency, The Composable Architecture, Bazel, OpenAPI, or Buildkite - Experience with web or backend development COMPENSATION - The monthly rate for this internship is $12,500 USD + housing stipend RAMP BENEFITS - Apple MacBook - Catered Lunches in NYC office Monday-Friday BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Кто мы Positive Technologies — вендор продуктов и услуг в области кибербезопасности. Более 20 лет наша основная задача — предотвращать хакерские атаки до того, как они причинят неприемлемый ущерб бизнесу и целым отраслям экономики. Наши технологии используют около 4000 организаций по всему миру. Ищем сильного инженера, который будет развивать PTree - платформу для проведения нагрузочного тестирования, сбора и анализа результатов, работы с метриками и формирования отчетов. Нам нужен человек, который способен работать от пользовательской задачи до готового сервиса: разобраться в потребности, спроектировать решение, реализовать frontend и backend, обеспечить его качество и сопровождение. Задачи: • проектировать архитектуру компонентов и сервисов, определять технические решения и обеспечивать их масштабируемость и сопровождаемость; • разрабатывать новые и развивать существующие сервисы платформы, реализовывать frontend и backend-функциональность; • повышать производительность, надежность и масштабируемость платформы; • взаимодействовать с заказчиками и пользователями PTree, собирать и анализировать пользовательские требования, переводить пользовательские задачи в технические решения; • развивать процессы сборки, тестирования и поставки сервисов, автоматизировать процессы развертывания и сопровождения, участвовать в настройке окружений и инфраструктуры; • взаимодействовать с командами разработки, эксплуатации и смежными продуктами, помогать коллегам в технических вопросах. Требования: • проектирования и развития микросервисной архитектуры; • разработки высоконагруженных и сложных прикладных систем; • создания backend-компонентов на Go и Python; • создания frontend-компонентов со сложными пользовательскими интерфейсами на React; • работы с метриками, логированием, мониторингом и диагностикой производительности; • проектирования и оптимизации баз данных; • создания и сопровождения CI/CD и автоматизации развертывания; • разработки и сопровождения автоматизированных тестов. Условия: • условия для постоянного развития: внешние и внутренние образовательные программы, митапы, научпоп-лекции, экспертное обучение, обучение для руководителей и не только; • гибкий подход к отдыху: 28 календарных дней отпуска, доплату отпускных до полного оклада и 10 day off в год; • заботу о здоровье: ДМС с первой недели работы, включая стоматологию, ежегодный чекап; • компенсацию до 50% расходов на занятия спортом и английским языком в рамках ежегодного бюджета; • работу в аккредитованной ИТ-компании и возможность использования льгот Министерства цифрового развития.