Данные и ML вакансии - в офисе

About Us & The Team Til-Qazyna is a national scientific and practical center dedicated to building the core digital and AI infrastructure for the Kazakh language. We develop foundational language resources, linguistic tools, and open-source models, including custom text corpora, morphological analyzers, RAG pipelines, and fine-tuned Large Language Models. We are looking for an AI Engineer to focus exclusively on natural language processing, corpus engineering, and LLM fine-tuning. Key Responsibilities • LLM Adaptation & Fine-Tuning: Fine-tune, evaluate, and benchmark open-source LLMs (Llama, Mistral, Qwen, Gemma) for Kazakh language understanding and generation using parameter-efficient methods (LoRA, QLoRA, PEFT). • NLP & Linguistic Tooling: Develop, maintain, and optimize rule-based and neural NLP components, including morphological analyzers, lemmatizers, tokenizers, and terminology parsers. • Corpus & Data Pipelines: Design automated pipelines for large-scale text crawling, data cleaning, deduplication, synthetic data generation, and dataset curation. • Inference & Deployment: Package NLP models and LLMs into containerized microservices (Docker, FastAPI) and optimize inference using modern serving frameworks (vLLM, Ollama, TensorRT-LLM, ONNX). Requirements • 1+ years of hands-on experience as NLP / AI / Machine Learning engineer. • Solid understanding of the Transformer architecture, attention mechanisms, embeddings, and tokenization. • Experience with core ML/NLP libraries: PyTorch, Hugging Face (transformers, datasets, accelerate, peft), Scikit-learn. • Experience building data preprocessing pipelines and working with structured/unstructured text data. • Practical knowledge of Docker, Linux, and Git. • Degree in Computer Science, Data Science, Applied Mathematics. Nice to Have • Hands-on experience with modern LLM serving and optimization engines (vLLM, TGI, llama.cpp, quantization techniques like AWQ/GPTQ). • Experience with RAG stacks (LangChain, LlamaIndex, ChromaDB, Qdrant, FAISS). • Understanding of the morphological, agglutinative, or grammatical characteristics of the Kazakh language. • Familiarity with alignment techniques (DPO, RLHF) or synthetic data generation. What We Offer • Direct impact on sovereign AI development and language technology used at scale. • Official employment in full compliance with the Labor Code of the Republic of Kazakhstan. • Access to high-performance GPU compute clusters for model training and experimentation.

Location: New York, NY; San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM: The LangSmith Engine team is building a proactive agent engineer that analyzes production traces, identifies important failures, recommends and writes fixes, and helps prevent those issues from coming back. We’re building agents that can understand complex software systems and continuously improve the quality of other AI agents. ABOUT THE ROLE: We’re looking for an experienced research engineer to help make the Engine agent more capable and more efficient. You’ll study real agent failures, build benchmarks that capture what matters, run experiments to improve performance, and turn successful ideas into production. This may include prompting and agent-harness improvements, model selection, fine-tuning and post-training custom models. The focus is on measurable improvements to the overall agent. This role also requires a understanding of production engineering and system-level tradeoffs. Engine is a production system, so improving an agent is not just about maximizing benchmark performance—it also means understanding the impact on cost, latency, reliability, and scalability. You’ll work in the same team with production engineers to design, test, and ship improvements that work reliably in real-world environments. Location: SF and NYC WHAT YOU’LL DO: - Build and maintain benchmarks and evaluations that measure the quality and efficiency of Engine agents on real-world tasks. - Design and run experiments to improve agent performance across models, prompting, context, tools, orchestration, and agent strategies. - Explore and implement post-training and fine-tuning techniques when they can meaningfully improve agent capabilities, quality, or cost. - Turn successful experiments into production improvements, working closely with engineers and researchers to measure impact and prevent regressions. - Help define the ML roadmap and technical direction for improving Engine agents, and mentor other engineers through strong technical leadership. WHAT YOU’LL BRING: - 4+ years of experience in ML/AI research, or a closely related field. - Master’s or Ph.D. in a relevant scientific field. - Hands-on experience working with LLMs and AI agents, including analyzing model behavior and improving real-world performance - Strong experience designing benchmarks, evaluations, and experiments for AI/ML systems; you know how to tell whether a change actually made an agent better. - Strong software engineering skills, with a track record of taking ideas from research prototype to measurable production impact. - You have maximum agency and strong research judgment: you can identify high-impact problems, work through ambiguity, move quickly, and communicate your findings clearly. NICE TO HAVE: - Ph.D. in Machine Learning, Computer Science or Physics. - Hands on experience with LLM-as-a-judge, automated graders, synthetic data generation, or human evaluation. - Hands on experience with reinforcement learning, preference optimization, SFT, RLHF/RLAIF, or other post-training techniques for LLMs. - Experience optimizing LLM agents for cost, latency, or task efficiency on productions - Experience with model serving, inference optimization, distributed systems, or GPU infrastructure. Compensation Salary Range: $240,000-$280,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Задачи: - разрабатывать надежные backend-сервисы для AI-помощников на основе GigaChat - создавать и поддерживать системы сбора и обработки данных: парсинг, логирование, аналитика - оптимизировать код, повышать стабильность и производительность сервисов под высокой нагрузкой - применять инструменты Data Science для улучшения работы систем и интеграции LLM в реальные бизнес-процессы. Требования: - рассматриваем студентов ВУЗа технической специальности, бакалавр 3-4 курс, магистратура 1-2 курс - уверенно владеете Python - знаете библиотеки FastAPI, aiohttp, SQLAlchemy, pandas, bs4 - имеете навыки асинхронного программирования - разбираетесь в SQL и ORM - понимаете принципы REST API, а также основы объектно-ориентированного проектирования (ООП, SOLID) - работаете с Git.

Задачи: — разработка backend-сервисы и API на Python — создание AI-агентов и AI-пайплайны с использованием LangChain, LangGraph или аналогичных инструментов — работа с LLM: промптами, structured output, tool calling, контекстом и памятью — участие в создании RAG-систем: загрузке документов, поиске информации и формировании ответов на основе источников — интеграция решения с базами данных, внутренними API и внешними сервисами — работа с очередями задач, кэшированием, логированием и мониторингом — участие в проектировании веб-приложений: продумывать взаимодействие backend, frontend, баз данных, фоновых задач и внешних сервисов — интеграция backend с пользовательскими интерфейсами и при необходимости внесение базовых изменений во frontend — написание тестов, исправление ошибок и улучшение качества существующего кода — участие в обсуждении архитектурных и технических решений — быстрое создание прототипов, проверка гипотез и доработка решений по обратной связи пользователей. Требования: — коммерческий опыт разработки на python (fastapi, django или flask) и уверенное проектирование rest api — sql и реляционные бд (postgresql), git, docker; понимание клиент-серверной архитектуры и http-стека (авторизация, аутентификация, обработка ошибок) — базовая архитектура приложений: модульность, разделение ответственности, слои приложения, поддерживаемость кода и взаимодействие сервисов — синхронная и асинхронная обработка, фоновые задачи, очереди сообщений и брокеры (например, celery с rabbitmq/kafka) — практический опыт в ai/llm: разработка агентов и чат-ботов, использование langchain/langgraph, управление контекстом llm, оценка качества и защита данных — rag-системы, векторные базы данных, работа с полуструктурированными данными (pdf, таблицы) через pandas/numpy — кэширование, логирование и мониторинг (redis, elk/prometheus); базовое знакомство с ci/cd и развёртыванием — websocket и потоковая передача ответов от llm; базовое понимание frontend (html/css/js, react/vue/next.js) для интеграции интерфейса с api — использование современных ai-инструментов для ускорения написания кода, тестирования и подготовки документации Условия: — офисный формат работы: г. Москва — ежегодный пересмотр зарплаты и годовая премия — более 400 образовательных программ в СберУниверситете для развития — спортзал и зоны отдыха — расширенный ДМС, льготное страхование для семьи — гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ — подписка Прайм с возможностью совместного использования на трёх близких — вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: — Проектировать и развивать модели компьютерного зрения и видеоаналитики (детекция, трекинг, распознавание лиц, анализ поведения); — Интегрировать ML-модели в production (backend, edge); — Обучать и дообучать модели (fine-tuning, transfer learning); — Работать над реальными AI-проектами с бизнес-применением; — Сопровождать полный цикл разработки: от исследования до деплоя; — Оптимизировать модели и повышать качество CV-решений. Требования: — Уверенные знания Computer Vision и современных DL-подходов; — Глубокое понимание машинного обучения и нейронных сетей (CNN, detection/segmentation); — Уверенное владение Python; — Опыт работы с OpenCV, NumPy, PyTorch и/или TensorFlow; — Опыт работы с Git; — Опыт оптимизации моделей (speed/accuracy trade-offs, inference); — Опыт решения задач детекции, трекинга и анализа поведения людей. Условия: — Формат работы: офис, Астана.

Задачи: — Разработка ИИ-решений для образовательных систем — Разработка автоматизированных пайплайнов для проверки и оценки ответов — Проведение экспериментов с большими языковыми моделями (LLM), промптами и методами дообучения — Подготовка, обработка и анализ данных Требования: — Опыт работы в Data Science, Machine Learning или NLP от 2 лет — Хорошее знание основ машинного и глубокого обучения — Уверенное владение Python — Продвинутый уровень SQL — Опыт работы с библиотеками для анализа данных и машинного обучения: NumPy, pandas, scikit-learn Условия: — Работа в офисе в Астане

Location: New York; San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. WHAT YOU’LL WORK ON: - Improve existing methods and develop new techniques for large-scale model training, optimization, and inference - Extend models to long-context and long-horizon tasks - Improve inference-time efficiency, reliability, and robustness in high-stakes real-world deployments YOU MAY BE A FIT IF: - You’re currently pursuing a PhD in computer science, machine learning, or a related field - You have a demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas - You have experience developing and evaluating large-scale models or machine learning systems - You’re familiar with distributed training, large-scale inference, or multi-GPU environments - You have publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR - You have strong programming and engineering skills and can translate research ideas into working implementations - You have a collaborative, mission-driven mindset and can work effectively across research and engineering teams

Location: Paris Workplace: OnSite ABOUT VOODOO Voodoo is a consumer tech company founded in Paris in 2013, with one mission: entertain the world. Today we are 1,000 people, generating $1b+ in annual revenue, profitably. Our games and apps have passed 7 billion downloads and reach 200 million+ active users every month, making Voodoo the #3 mobile publisher worldwide in downloads, after Google and Meta. We were backed by Goldman Sachs, Tencent and GBL along the way. TEAM Blitz is a gaming platform launched by Voodoo in 2021, allowing players to compete on mobile games for real cash prizes (head-up, tournaments, leagues, etc.). It is leveraging Voodoo's unique game portfolio to engage users in a fun and rewarding way. ROLE This role sits at the intersection of the Data and Gaming teams. You'll be the analytical partner to game designers and product managers, owning the measurement and tuning of the games themselves — from difficulty and game parameters to matchmaking fairness and the in-game economy. Your work directly shapes what players experience and how the games perform. MISSIONS: - Own the A/B testing cycle for games and game parameters — designing experiments, validating changes, and reading out results that drive core KPIs (engagement, RTP, rake, fairness, retention). - Analyze and calibrate game parameters — difficulty, scoring, completion rates, seed selection, and payout structures — to hit target player experience and economic goals. - Translate analyses into clear, actionable recommendations that shape game design and the product roadmap. - Build simulations and prototypes to pressure-test parameter and economy changes before rollout, then monitor them live once shipped. - Collaborate closely with game designers and engineers to embed data-driven decisions across the full game lifecycle. - Build and maintain dashboards and reports that keep the Gaming and Data teams aligned on critical game and economy metrics. PROFILE - 3+ years in analytical roles, ideally within gaming or a data-intensive product environment, comfortable working directly with product and design teams. - Skilled in SQL and Python; experience with large, complex datasets. - Strong grasp of A/B testing and statistical methods. - Comfortable with simulation and modeling to reason about game parameters, difficulty, and game economy outcomes. - Thrives in a fast-paced environment with rapid iteration. - Player-first mindset with genuine curiosity about games, player behavior, and game balance. BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office - Remote days on Fridays

Location: San Francisco Bay Area, CA Workplace: onsite Overview Get Paid to Help Shape the Future of Technology  We are building a community of participants for upcoming in-person data collection projects in San Francisco Bay Area. These projects help improve the next generation of smart devices and technology and we are looking for everyday people to take part.  No experience is required. No special skills are needed. Simply attend your scheduled session, follow a few simple instructions, and get paid for your time.  What You'll Do  Participants take part in short, moderated sessions involving simple, everyday activities such as walking, sitting, or moving through a space while smart devices record the session. A friendly moderator guides you through every step. A trained moderator will guide you through the entire process.  Project Details Job Type: Freelance/Independent Contract Time Commitment:Approximately 1 hour Location:San Francisco Bay Area (On-site) Project Type: Short-term, paid, in-person research sessions   Who Can Apply?  We welcome people of all ages and backgrounds from across the San Francisco Bay Area. To participate, you should:  Adults and minors are eligible (participants under 18 require parent/guardian consent)  Be comfortable following simple instructions in English (non-native English speakers are welcome).  Feel free to register with friends or family, you are welcome to participate together. Why Join Welo Data?   ✨ Limitless Flexibility   Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.    🌱 Limitless Growth   Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.    🌍 Limitless Support   Be part of a global contributor community with responsive guidance and support.    💡 Real Impact   Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.       About Welo Data  Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.   At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.

Location: Seattle, WA Workplace: onsite Overview Get Paid to Help Shape the Future of Technology  We are building a community of participants for upcoming in-person data collection projects in Seattle. These projects help improve the next generation of smart devices and technology and we are looking for everyday people to take part.  No experience is required. No special skills are needed. Simply attend your scheduled session, follow a few simple instructions, and get paid for your time.  What You'll Do  Participants take part in short, moderated sessions involving simple, everyday activities such as walking, sitting, or moving through a space while smart devices record the session. A friendly moderator guides you through every step. A trained moderator will guide you through the entire process.  Project Details Job Type: Freelance/Independent Contract Time Commitment:Approximately 1 hour Location: Seattle Metro Area (On-site) Project Type: Short-term, paid, in-person research sessions   Who Can Apply?  We welcome people of all ages and backgrounds from across the Seattle region. To participate, you should:  Adults and minors are eligible (participants under 18 require parent/guardian consent)  Be comfortable following simple instructions in English (non-native English speakers are welcome).  Feel free to register with friends or family, you are welcome to participate together. Why Join Welo Data?   ✨ Limitless Flexibility   Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.    🌱 Limitless Growth   Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.    🌍 Limitless Support   Be part of a global contributor community with responsive guidance and support.    💡 Real Impact   Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.       About Welo Data  Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.   At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.

Location: California; Sunnyvale, CA; San Francisco, CA; Seattle, WA; Redmond, Washington; Burlingame, CA; New York City Metropolitan Area; Los Angeles, CA; Washington, D.C.; Boston, MA Workplace: onsite Overview Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems. This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs. While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale. We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows. Project Details Job Title: Speech & Voice AI Analyst Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent)  Hours: Full-time, 40 hours per week Employment Type: W2 Full-Time Employee Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship) Pay Rate: $28/hour Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Los Angeles, Washington DC, Boston. Please only apply if you meet this location requirement. What You’ll Do Execute high-volume data labeling and annotation tasks across speech and voice datasets Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale Work with audio and language data, including transcription, categorization, and tagging Maintain strong throughput while meeting quality expectations Escalate unclear or ambiguous cases appropriately Adapt to evolving guidelines and workflows as systems and requirements change Support baseline data production needs for AI training pipelines Contribute to team calibrations and quality alignment sessions What We’re Looking For Native-level fluency in Portuguese (Brazil) Strong written communication skills and language fundamentals 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field. Ability to follow detailed instructions and apply guidelines consistently High attention to detail and ability to maintain accuracy in repetitive tasks Comfort working in structured, process-driven environments Ability to manage time effectively and maintain steady output Willingness to ask questions and escalate when needed Basic familiarity with AI, speech technology, or language data is a plus Benefits Paid Vacation: 6 days Paid Company Holidays: 2 days (Memorial Day and Labor Day) Paid Sick Leave: accrued per applicable state law and company policy Medical, Dental, and Vision Insurance (eligibility applies) Health Savings Account (HSA) 401(k) Retirement Plan Employee Assistance Program Additional voluntary benefits (life, accident, critical illness, etc.) Onsite Perks (where applicable): Free breakfast, lunch, and dinner Stocked micro-kitchens with snacks and beverages Commuter benefits, including shuttles and bike-to-work options Unique campus features depending on location Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.   To know more details (Click here)   In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.     As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com   To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions. Why This Role This role is a critical part of how modern AI systems are built. The data you produce directly impacts how speech and voice models understand and interact with real users. It’s a great entry point into AI operations, offering exposure to large-scale systems and the opportunity to build foundational experience in data, language, and AI workflows.

Задачи: — Разработка с нуля мультиязычного голосового ассистента (обязательно: английский + турецкий) для мобильного приложения и личного кабинета клиента. — Проектирование архитектуры: оценка решений «готовые API vs локальные модели» и последующий вывод open-source LLM в продакшн. — Интеграция AI-сервисов с текущим бэкендом платформы (основной стек: PHP/Laravel, есть элементы legacy на Yii/C#). — На перспективу: задачи на стыке Computer Vision (умный процессинг оплат) и телематики (анализ данных с датчиков топлива, предсказание поломок спецтехники). Требования: — Отличный Python (коммерческий опыт Middle+ / Senior). — Понимание архитектуры бэкенда (будет плюсом опыт соприкосновения с PHP/Laravel или Go). — Опыт разработки голосовых решений (STT/TTS, ASR/NLP), опыт развертывания и кастомизации локальных моделей (LLM) на своих серверах в проде. — English: уровень B2 и выше (чтение документации, работа с зарубежными AI-ресурсами и проектами). Условия: — Локация: Алматы, офис (для сильных кандидатов возможен гибрид или удаленка). — Занятость: Full-time.

Задачи: — Сбор, валидация и анализ данных из внутренних систем, разработка новых метрик и KPI. — Разработка ML-моделей для анализа временных рядов, прогнозирования сальдо счетов, LTV и оттока клиентов. — Кластеризация и сегментация базы, разработка моделей скоринга и расчет Life Time (LT). — Прогнозирование объема обращений и моделирование показателей эффективности (KPI) сервиса. — Формирование и проверка гипотез для улучшения ключевых бизнес-показателей на основе математических моделей. Требования: — Высшее образование в математике, финансах, экономике, информатике, физике, инженерии или аналогичных областях. — Исследовательский склад ума, творческий подход, настойчивость, инициативность, внимательность к деталям. — Критическое мышление и способность находить нестандартные подходы. — Уверенное владение инструментами BI аналитики, знание MySQL, Google Big Query, Python, Git. — Английский язык на уровне B2. Условия: — Работа в европейском офисе с отличным климатом. — Компенсация перелета и помощь с легализацией (релокационный пакет). — Конкурентная заработная плата, ДМС и пакет бенефитов. — Амбициозные задачи. — Работа в команде профессионалов в комфортабельном офисе в регионе с отличным климатом.

Задачи: — Разрабатывать и оптимизировать Spark-пайплайны для обработки данных в масштабе (200+ млн строк ежедневно) — Настраивать хранение и доступность данных в DWH — Автоматизировать интеграцию данных: продажи, акции, цены, остатки, погода, календари — Работать в связке с Data Science-командой, обеспечивая стабильный и качественный поток данных для моделей — Участвовать в развитии платформы прогнозирования спроса, делая её более надёжной, масштабируемой и удобной Требования: — null Условия: — null

Задачи: — Развертывать и оптимизировать локальные AI-модели. — Разрабатывать AI-агентов и RAG-решения. — Интегрировать AI-сервисы с корпоративными системами. — Выводить AI-продукты в промышленную эксплуатацию. Требования: — Практический опыт локального развертывания LLM. — Опыт работы с RAG, LoRA/QLoRA, Hugging Face, PyTorch. — Умение доводить AI-продукты до промышленной эксплуатации. — Для Strong Middle обязателен подтвержденный опыт самостоятельной разработки и внедрения AI-решений в production. — Действующее право на трудовую деятельность в Республике Казахстан (оформление разрешений на привлечение иностранной рабочей силы не осуществляется). Условия: — Работа в офисе в Астане, full-time. — Трудовой договор. — Возможность участвовать в создании собственной AI-платформы компании. — Зарплата до 2 000 000 тенге net по результатам интервью.