Вакансии

FAIR (Meta) is the artificial intelligence research division of Meta. On-site position in Paris, France.

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About Collectly: Collectly is a fast-growing healthcare technology company transforming revenue cycle management (RCM) through AI-driven automation. Millions of patients navigate inefficient billing systems every day, while providers face delayed payments, rising administrative burden, and operational complexity. Collectly applies artificial intelligence to automate workflows, accelerate cash flow, and modernize the patient financial experience; enabling healthcare organizations to operate more efficiently and focus on delivering care. Healthcare is a $4.9T industry and is adopting AI technology at 2.2x the rate of the rest of the economy. Position Overview: We are seeking a highly organized and proactive Talent Coordinator and Sourcer to join our Talent team. In this role, you will partner with the Talent Manager and Hiring Managers to ensure a seamless and positive candidate experience throughout the recruitment process. You will be responsible for scheduling interviews, managing logistics, and providing support to candidates and hiring partners. Additionally, you will leverage your sourcing skills to identify and attract top talent through various channels. This is an excellent opportunity to contribute to our recruitment efforts, improve processes, and play a key role in shaping our organization's talent acquisition strategy.

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About our Machine Learning Business Banking team: Our mission in Business Banking is to simplify banking for small businesses; making business banking fairer, simpler and more transparent. Monzo Business Banking is fast-growing, is the UK’s most recommended business account for overall service quality. We recently hit 1 million customers and are used by 1 in 6 UK SMEs. We want to help businesses spend less time on financial admin and more time focused on running and growing their business. We’re building intelligent, data-driven and AI/ML-enabled product experiences that help small businesses feel more in control, make better decisions, and get more value from Monzo. ML is at the core of how we build and scale our products, enabling Monzo to make better decisions, faster, and helping us serve businesses more effectively. As a Lead Machine Learning Scientist in Business Banking, you’ll help build and ship models that power the next generation of Business Banking experiences. You’ll work closely with Product, Engineering, Design, Research, Data Science and Analytics Engineering to bring ML-enabled product capability into the heart of how we build for businesses. Whether it’s helping businesses understand their cash flow, reducing manual admin, surfacing the right insight at the right moment, or helping teams build intelligent product experiences responsibly, our work makes business banking smarter, simpler and more useful for SMEs. What you'll be working on As a Lead Machine Learning Scientist, you’ll be a technical leader and hands-on individual contributor, spearheading our ML and GenAI capabilities and shipping key models that powers magical Business Banking experiences. You’ll: — Be one of the first ML Scientists in Business Banking, bringing leadership through ambiguity by adding structure and direction to our ML capabilities while staying agile and building momentum. — Develop and deploy advanced ML models on our cloud-native data platform to serve hundreds of thousands of business customers. — Partner with Product, data science and other stakeholders to identify the highest-impact opportunities, size impact, and define success metrics. — Decide when to use ML, GenAI, or simpler approaches and be clear on trade-offs. — Design robust evaluation and monitoring so we can ship responsibly and measure impact in production. — Lead the design and implementation of batch and near-real-time models (e.g. LLM-powered experiences, predictive models, time-series forecasting). — Collaborate closely with MLOps and Backend Engineering to operationalise models end-to-end and raise the bar on ML lifecycle rigor. — Set technical standards, mentor others, and support experimentation and iteration. You should apply if: — What we’re doing here at Monzo excites you! — You have a multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems, preferably in a fast-moving tech company. — You have experience developing and shipping state-of-the-art ML models to production and delivering business impact. — You're impact-driven and excited to own the end-to-end journey that starts with a business problem and ends with your solution having a measurable impact in production. — You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so. — You speak Python fluently and have extensive, hands-on experience with scikit-learn. — You are comfortable using SQL, and keen to learn Go, which is used in many of our backend microservices. — You’re comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity. — You want to be involved in building a product that small businesses use to run and manage their financial lives every day. — You have a product mindset: you care about customer outcomes and you want to make data-informed decisions. — You’re excited about fast-moving developments in Machine Learning and AI and can communicate those ideas to colleagues who are not familiar with the domain. — You’re adaptable, curious and enjoy learning new technologies and ideas. — You’re excited by the opportunity to help Business Banking evolve into AI and ML-enabled product capability. — You can work closely with Product, Engineering, Design, Research and Data colleagues to shape product strategy, clarify trade-offs and build things that customers actually use. — You’re thoughtful about responsible ML/AI; especially in financial products where trust, transparency and customer control matter. Nice to haves: — Experience working on personalisation, ranking, recommendation, forecasting, classification or decisioning problems for customer-facing applications. — Experience working on ML systems for fintech, banking, accounting, payments, lending, invoicing, cash flow, tax, risk or business software. — Experience with GenAI, LLMs, agentic workflows, retrieval, evaluation frameworks, or human-in-the-loop product experiences. — Commercial experience writing critical production code and working with microservices. — Experience designing experiments, A/B tests or other approaches to measure product and customer impact. — Experience working in regulated environments or with products where explainability, auditability and customer trust are especially important. The interview process: Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions! — 30 minute recruiter call — 45 minute call with hiring manager — Full Loop: ML Modelling Interview, Product & ML interview, Behavioural Interview, Leadership interview Our average process takes around 3-4 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process but if you do have any specific questions ahead of this please contact us on tech-hiring@monzo.com. Please also use that email to let us know if there's anything we can do to make your application process easier for you, because of disability, neurodiversity or any other personal reason. What’s in it for you: — We can help you relocate to the UK — We can sponsor visas — This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London). — We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. — Learning budget of £1,000 a year for training courses and conferences — And much more, see our full list of benefits here If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.

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We are seeking an experienced technical product manager to design and deliver high-value AI Agent solutions across the Veeva Quality Cloud suite of products. Veeva Quality Cloud accelerates the manufacturing of high-quality products to a greater number of patients. The cloud platform unifies applications, processes and partners across content management, training, Quality Management System (QMS) and QC lab solutions (LIMS). In this role, you will be an expert in the use of AI to design and build AI agents that analyze document content and intelligently extract the information to map & store them as structured data within the Veeva Quality Cloud data model (i.e. ‘Docs to Data’).

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RELOCATION TO GERMANY adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we’ve become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually. Architecting Intelligence to Optimize 200M+ Daily Decisions As the intelligence core of our engineering organization, our Data Science team doesn’t just deploy models, we engineer the fundamental decision engine that powers our platform. At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time. Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision. We aren’t just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange. Engineered for performance, our stack leverages Tensorflow and PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation. Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem. Your Mission & Who We Are Looking For: — Proven track record in production ML with 5+ years in Data Science and deployed models that moved real business metrics. — Building models that predict LTV, conversion, and user behavior across 770 million users, impacting advertiser ROAS and publisher revenue. — Deep learning as primary tool with strong hands-on experience in PyTorch or TensorFlow and production deployment handling 1M+ daily predictions. — Full ML lifecycle ownership from data extraction using Trino, Spark, or AWS Athena, through model development, A/B validation, to production deployment. — Experience with Airflow or model hosting is a strong plus. — Fluent in Python and data at scale, comfortable with pandas/polars, numpy, scikit-learn, LightGBM, CatBoost, XGBoost, and advanced SQL skills. — Ability to translate product requirements into ML logic and explain model behavior and impact to non-technical stakeholders. — AdTech experience is a strong plus. What’s in It for You? — Relocation support to Hamburg, Germany for worldwide talent. — Opportunity to build infrastructure behind impactful adtech platform reaching hundreds of millions of users and powering billions of decisions daily. — Ownership of projects impacting 770M users and pushing adtech boundaries. — Fast-paced environment with multiple daily solution deployments and learning from results. — Collaborative culture with diverse global team from over 40 countries. — Enjoy daily victories and energetic work environment.

RELOCATION TO GERMANY adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we’ve become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually. Architecting Intelligence to Optimize 200M+ Daily Decisions As the intelligence core of our engineering organization, our Data Science team doesn’t just deploy models, we engineer the fundamental decision engine that powers our platform. At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time. Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision. We aren’t just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange. Engineered for performance, our stack leverages Tensorflow and PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation. Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem. The data infrastructure behind this runs at real scale: 2TB ingested in real time every day, 100+ Airflow jobs and data pipelines, and ML models handling p99 latency of 100ms across 100,000+ predictions per second. As a Data Engineer on this team – you’ll be building and maintaining the infrastructure that makes them possible: the Feature Store, the data pipelines, the data quality systems, and the data architecture that data scientists depend on to move fast. Your Mission & Who We Are Looking For: Data engineering at ML scale. You have 5+ years in data engineering on a modern stack, with proven experience handling systems that process several TB of data per day and thousands of events per second. Flink is your default for real-time. You have hands-on experience with Apache Flink for stateful stream processing and real-time feature computation. You’ll translate Data Science requirements into high-performance streams, enable Data Scientists to contribute new features and implement features yourself when needed. Pipeline bottlenecks don’t survive long around you. You know how to identify and eliminate inefficiencies in complex ETL jobs, whether handling high-volume batch processing or real-time streaming systems like Kafka. At adjoe, data velocity is critical: slow pipelines directly impact model freshness and prediction quality at sub-100ms inference. You think in layers, not tables. You move beyond raw data to design robust, multi-layered data architectures using dbt, and can reason confidently about storage formats, Data Lakehouse models, and what belongs where in a 1PB+ data lake. Familiarity with Medallion Architecture is a strong plus. The bridge between Data Science and Backend. You’ve worked closely with Data Scientists on online ML systems with low latency requirements, and understand what it takes to make experimental research production-ready. Strong Java required; Go or Python a plus. Owns quality, not just delivery. You implement data validation, monitoring, and governance processes in production, because in a system where model inputs directly drive advertiser ROI, data integrity isn’t optional. Experience with Airflow, Kubeflow, AWS, Terraform, and Kubernetes is a strong plus. 🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. Go Big. Own projects with impact on 770M users and push adtech boundaries. Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. Be Direct. Solve problems openly and collaborate across teams. Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.

Задачи: — участие в крупнейшем AI Agentic Hackathon с попыткой установить мировой рекорд Гиннесса — работа над крупнейшим в Казахстане корпоративным курсом по искусственному интеллекту — участие в первом в стране GovTech Camp совместно с inDrive — запуск первых в Казахстане казахскоязычных курсов по Data Engineering, Vibe Coding, Artificial Intelligence Требования: — студенты и выпускники — хороший английский язык — быстрая реакция, организованность и инициативность — AI-native user Условия: — 4 недели неоплачиваемой стажировки — по результатам стажировки определится, кто попадет в команду — прошедшие стажировку попадают на 3-х месячную оплачиваемую стажировку — далее официальное трудоустройство Дедлайн подачи: 9 августа

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Задачи: — Участие в двух треках: Инкубатор (формирование команд с нуля вокруг реальных отраслевых проблем) и Акселератор (вывод существующих AI продуктов и исследований до MVP, пилота и реальных клиентов). — В августе провести валидацию проблемы с 10 интервью с клиентами. — В сентябре создать работающий MVP и привлечь первого внешнего пользователя. — В октябре запустить пилот с клиентом. — Достичь критерия выпуска: реальное развертывание продукта. Требования: — Быть студентом, исследователем, преподавателем, выпускником или амбициозным кандидатом, желающим создавать AI продукты для глобальных рынков. — Владение английским языком. Условия: — 12 недель интенсивной работы. — Работа с основателями и менторами из стартапов, венчурных фондов и глобальных технологических компаний из разных стран. — Целевые результаты: 15+ MVP, 3+ пилотных проектов с клиентами. — Отбор на основе интервью. Организаторы: — AI Institute — Institute of Automation and Information Technologies, Satbayev University Партнеры: — Center of Mathematical Finance (CMF) — Association for the Development of Artificial Intelligence in Education (Kazakhstan)

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RELOCATION TO UAE CoreConnect, a flagship product by VentureOne, the commercialization arm of the Advanced Technology Research Council, acts as the digital glue within the complex ecosystem of autonomous mobility in logistics. CoreConnect is building the infrastructure layer for autonomous operations in complex ecosystems. We develop a robot orchestration platform that enables logistics and other operators to deploy, manage, and scale fleets of autonomous robots across real-world environments. Our technology sits at the intersection of robotics, operations software, and intelligent automation. Role Overview We are seeking a Senior Software Engineer (Backend) who prioritizes system reliability and product impact. You will be a key contributor to CoreConnect, developing a scalable Hexagonal Backend API service that serves as the primary interface for our commercial ecosystem. We value engineers who operate with a high degree of autonomy, technical pragmatism, and a commitment to operational excellence. We are specifically looking for candidates who demonstrate ownership, pragmatism, and feel comfortable with navigating ambiguity. Key Responsibilities Core Engineering & Architecture: Design, implement, and optimize scalable Kotlin Spring Boot backend services using a Hexagonal architecture for high-performance fleet orchestration. Data & Integration Strategy: Manage complex data layers (Postgres/PostGIS, TimescaleDB) and develop a Unified Abstraction Layer to integrate diverse autonomous vehicle APIs for fleet-agnostic control. Real-time Systems & Optimization: Drive the technical roadmap for real-time data engineering, resolving bottlenecks in high-frequency data ingestion (MQTT/WebSockets) to ensure sub-second latency. Security, Scalability & Observability: Enforce standards for platform security and observability, implementing Multi-tenant Architecture (RLS) and Role-Based Access Control (RBAC). Cross-Functional Collaboration: Partner closely with Product, Engineering Leadership, and DevSecOps to build high-quality solutions that drive measurable business outcomes. Engineering Culture: Mentor engineers, lead rigorous code reviews, introduce process improvements, and foster a culture of operational excellence. Qualifications Experience & Education: Bachelor’s degree or higher in Computer Science or other relevant fields and 5+ years of professional experience with Java or Kotlin and Spring Boot delivering well-tested, complex systems in a SaaS startup environment. Architecture & Data Mastery: Deep proficiency in distributed systems, Hexagonal Architecture, and scalable API design. Expertise in SQL (PostgreSQL), geospatial data (GIS/PostGIS), and time-series data (TimescaleDB). Real-Time & Integrations: Experience architecting low-latency communication (WebSockets, MQTT) and building abstraction layers for third-party vendor APIs. Mindset & Execution: Proven ability to navigate ambiguity, balance architectural purity with commercial objectives (managing technical debt, shipping MVPs), and take full ownership of the code lifecycle and incident management (root-cause analysis and prevention). Security & Quality: A consistent focus on software quality and security best practices with hands-on experience in automated testing (unit and integration test suites), SAST, DAST, and setting up platform observability tooling. Complementary Expertise: Frontend Proficiency: Practical experience building interfaces with React or Next.js and TypeScript. Infrastructure & DevOps: Mastery of cloud environments, specifically AWS and Kubernetes (EKS), along with CI/CD pipelines and Infrastructure as Code (Terraform or Helm). Industry Experience: Direct background in logistics, robotics, or fleet management systems. Communication: Fluency in Business English is a must. What We Offer We provide a competitive, tax-free salary and a comprehensive benefits package in a collaborative, innovative, and inclusive work environment. Our benefits include an education allowance, free on-site meals, annual flight allowance, health coverage, relocation support (if applicable), and access to well-being activities such as sports and recreational events. Join us to drive innovation and shape the future of technology!

RELOCATION TO LONDON OR BARCELONA | PERK Company Perk is an intelligent platform for travel and spend management, automating manual processes to help businesses reclaim lost productivity. What you will do Design and maintain efficient ELT pipelines using dbt to transform raw data into clean models. Implement best-practice data modeling and software engineering techniques, including CI/CD and testing. Develop comprehensive data quality checks and monitoring scripts to ensure reliability. Collaborate with analysts and business users to optimize data models for specific analytical use cases. Tune SQL queries and data models to improve warehouse performance and reduce latency. Build scalable, compelling data visualizations in Looker for large teams. Requirements 3+ years of experience in a data-focused role such as Analytics Engineer, Data Analyst, or BI Developer. Expert-level proficiency in SQL. Hands-on experience with dbt or similar transformation frameworks. Experience with cloud data warehouses like Snowflake, BigQuery, or Redshift. Solid understanding of dimensional modeling and ETL/ELT principles. Proficiency with Git for version control. Must be based within commuting distance of London or Barcelona. Nice to have Python expertise for automation and orchestration. Experience with semantic layers and orchestration tools like Airflow. Knowledge of modern software engineering practices applied to data. Culture & Benefits IRL-first culture emphasizing connectivity and collaboration. Opportunity to work in a global, diverse environment with teams across 12 offices. Focus on professional growth and impact within a fast-growing SaaS company. Equal opportunity employer committed to diversity and inclusion.

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MDiet — early-stage HealthTech стартап, разрабатывающий AI-powered платформу, которая помогает снижать количество повторных госпитализаций пациентов. Продукт ориентирован на рынок здравоохранения США. Возможна релокация в США при успешном росте компании, обсуждается индивидуально. Tech Stack: • LangGraph + LangChain / Agentic AI • vLLM + Hugging Face • PyTorch + PEFT / LoRA / QLoRA • Vector databases: pgvector, Qdrant, Weaviate, Chroma, Pinecone • Advanced RAG, Prompt Engineering, Embeddings • FastAPI + PostgreSQL • Docker + Kubernetes + async processing: Arq / Celery / Redis Streams • Apache Airflow для data pipelines • AWS Cloud: EC2, S3, SageMaker, Lambda, RDS, Bedrock • Structured output: Outlines / Guidance / Instructor • Evaluation & observability: Langfuse, RAGAS / DeepEval, Prometheus + Grafana • MLOps practices Задачи: • Проектирование и разработка multi-step LLM agents и pipelines для обработки медицинских данных • Разработка production RAG-систем с высоким уровнем grounding и качеством citation • Деплой и оптимизация self-hosted LLM inference через vLLM с фокусом на cost и throughput optimization • Fine-tuning open-source моделей на domain-specific medical data с измеримым улучшением результата • Построение data pipelines и versioning для документов, embeddings и training data • Создание evaluation frameworks, guardrails и систем контроля hallucinations • Реализация reliable structured output и data extraction • Тесное взаимодействие с physicians и Platform Architect Требования: • Сильный hands-on опыт с production LLM systems: RAG, agents, inference • Опыт fine-tuning open-source LLMs: LoRA / QLoRA / PEFT, с измеримыми результатами • Опыт построения data pipelines и versioning для LLM / RAG workloads • Сильные навыки в evaluation, hallucination reduction и structured output • Production Python + FastAPI + async processing • Опыт с self-hosted inference: vLLM или аналогичные решения • Опыт GPU optimization • Английский язык на уровне C1: strong written and spoken communication skills • Bachelor’s degree или выше в Computer Science, Artificial Intelligence, Machine Learning, Data Science или смежной технической области • 5+ лет опыта в ML/AI • 1.5–2+ года опыта в production LLM projects • Опыт с MLOps Будет плюсом: • Опыт в medical / clinical NLP или regulated domains • Cost modeling и optimization of LLM workloads • MLOps и production fine-tuning pipelines • Apache Airflow, Prometheus / Grafana или AI Solution Architecture • Publications in relevant fields Условия: • Работа в early-stage HealthTech startup с продуктом для US healthcare market • Возможность участвовать в создании AI-powered платформы с реальным влиянием на healthcare-процессы • Офисный формат в Астане первые 7–9 месяцев, далее возможен hybrid/remote • Зарплата $4 000 – $5 000 USD gross + equity • Возможность релокации в США при успешном росте компании, обсуждается индивидуально

About Mistral: At Mistral AI, we develop AI technology to simplify tasks, enhance learning and creativity, integrating seamlessly into daily work life. We offer high-performance, optimized, open-source AI models and solutions for enterprise needs on-premises or in cloud. Our AI assistant product is le Chat. Our teams are distributed across France, USA, UK, Germany, and Singapore. Role Summary: Seeking an experienced product manager to define and execute strategy for Forge, a product enabling customers to build, fine-tune, and deploy custom AI models at scale. Forge powers model fine-tuning, reinforcement learning, and post-training workflows, translating research into enterprise-ready solutions. Responsibilities: — Define and evangelize product strategy for Forge aligned with company goals and market opportunities — Lead market and UX research to identify unmet needs and trends in AI post-training capabilities — Own product lifecycle from ideation to launch and iteration, balancing speed, quality, and user experience — Collaborate with design and research to create intuitive, impactful user experiences using data and feedback — Work with marketing and sales on go-to-market strategies including pricing, positioning, and adoption — Align engineering, design, and business teams on priorities, trade-offs, and timelines — Maintain a dynamic roadmap delivering quick wins and long-term goals Requirements: — 5+ years product management experience in fast-paced, ambiguous environments with AI/ML or infrastructure solutions — Strong understanding of AI training pipelines, reinforcement learning loops, and model deployment architectures — Expertise in AI model lifecycle management including fine-tuning, evaluation, and serving — Experience with Infrastructure as Code, containerization, scalable deployment (on-prem, VPC, cloud) — Familiarity with Kubernetes/Slurm is a strong plus — User-focused with data-driven problem solving — Proven cross-functional influence without direct authority — Strong communication skills to explain complex technical concepts clearly — Adaptability to dynamic priorities — Collaborative, low ego, high emotional intelligence — Self-directed with ownership of outcomes Preferred: — Strong knowledge of model training and architectures — Proficient coding skills recommended — Kubernetes expertise recommended — Experience with product-led growth strategies — Founder or early-stage PM experience — Ability to prototype or dive into code Location & Work Format: — Based in Paris, France or London, UK offices — Remote work possible from France, UK, Germany, Belgium, Netherlands, Spain, Italy — Encouraged to work in office at least 3 days per week Conditions: — Competitive salary and equity (stock options) — Health insurance — Transportation allowance — Sport allowance — Meal vouchers — Private pension plan — Generous parental leave — Visa sponsorship

О ПРОЕКТЕ Мы строим передовую аналитическую платформу на базе AI для экосистемы Solana. Наша система обрабатывает миллионы транзакций в реальном времени, предоставляя трейдерам и институционалам глубокую аналитику: Wallet Intelligence (скоринг поведения), Token Health (ликвидность, манипуляции), детектирование аномалий (фрод, rug pull) и предиктивные прогнозы на базе ML. О ПОЗИЦИИ (ABOUT THE ROLE) Вам предстоит проектировать и внедрять интерфейсы для систем с низкой задержкой (low-latency). Основной фокус — визуализация сложных потоков данных, создание умных алертов и аналитических дашбордов, которые работают непрерывно в распределенной среде. ВАШИ КЛЮЧЕВЫЕ ЗАДАЧИ — Разработка: Создание масштабируемых веб-приложений на React/Next.js и TypeScript. — Real-time системы: Реализация UI-паттернов для живых данных (WebSockets, SSE, оптимизированный поллинг). — Визуализация: Разработка переиспользуемых компонентов для графиков, таблиц, фильтров и таймлайнов. — Оптимизация: Работа с производительностью для часто обновляемых тяжелых датасетов (виртуализация, мемоизация). — Инфраструктура: Участие в развитии дизайн-системы и тесное взаимодействие с бэкенд-командой по части API-контрактов. — Качество: Проработка состояний кэширования, обработки ошибок и обеспечение кроссбраузерности. ТРЕБОВАНИЯ К КАНДИДАТУ — Стек: Уверенное владение JavaScript/TypeScript, React и современным Frontend-инструментарием. — Опыт: Подтвержденный бэкграунд в создании Dashboard-систем или приложений с высокой плотностью данных. — Технологии: Опыт интеграции REST API и эффективного управления состоянием на стороне клиента. — Performance: Глубокое понимание оптимизации (lazy loading, memoization) и работы с Tailwind / CSS Modules. — Soft Skills: Способность работать автономно и полностью «владеть» фичами от идеи до продакшена.

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