Вакансии

Предстоит исследовать LLM и RAG, работать с неструктурированными данными, готовить датасеты и обучать chat- и embedding-модели. Среди задач также AI-инструменты и агенты для корпоративных продуктов.

Задачи: сбор и формализация функциональных и нефункциональных требований, управление их библиотекой, настройка интеграций с ИИ-агентами, работа с большими контекстами, выборочное код-ревью и проверка фронтенда и бэкенда на соответствие требованиям и дизайн-системе, контроль производственного процесса и архитектуры при подготовке релизов.

Location: Москва Мы строим высоконагруженные ML-системы для обеспечения банковской безопасности. Наш фокус — антифрод, управление рисками, обнаружение аномалий и оптимизация бизнес-процессов и тд. Ищем MLE грейда Middle+ с сильной инженерной базой. Ключевая задача — внедрение и адаптация высокопроизводительных runtime-шаблонов для инференса моделей, автоматизация процессов деплоя и оптимизация Time-to-Market при выводе ML/DL и LLM в промышленную эксплуатацию. Обязанности • развертывание и поставка моделей: Упаковка, деплой и поддержка runtime-шаблонов для быстрого вывода моделей в прод на основе готовых архитектурных решений Оптимизация инференса (ML Serving): • обеспечение требуемого уровня latency и пропускной способности для классического ML (LightGBM, CatBoost и тд) и нейросетей • конфигурирование и поддержка инференс-серверов (Triton Inference Server, vLLM и тд) Интеграция и оптимизация LLM: • вывод в продакшен LLM-агентов и RAG-систем с использованием готовых фреймворков • настройка производительных движков (vLLM, TGI) с применением базовых техник оптимизации (квантование, continuous batching) • реализация механизмов кэширования и фильтрации запросов (Guardrails) Автоматизация пайплайнов: • сборка end-to-end пайплайнов доставки данных и моделей (от логов до Real-time API) • интеграция с очередями сообщений (Kafka) для обработки данных в реальном времени • написание и поддержка DAG-ов переобучения моделей в Airflow Мониторинг и логирование: • настройка базового мониторинга метрик данных и моделей (Data/Model Drift) • интеграция трекинга экспериментов и логирования цепочек LLM (MLflow, Langfuse) • ведение реестра моделей в MLflow Model Registry. Требования • инженерный опыт: От 3-х лет в роли MLE / Backend-разработчика (Python) с опытом коммерческого вывода моделей в прод и пониманием специфики Highload-систем • уверенный Python: Чистый, типизированный код, знание асинхронного программирования (Asyncio) и базовых паттернов проектирования • работа с данными и очередями: Хорошее знание SQL (сложные запросы, оконные функции) и практический опыт интеграции приложений с Kafka MLOps и Инфраструктура: • уверенное владение Docker, базовый опыт работы со средой Kubernetes (запуск подов, просмотр логов, понимание манифестов) • опыт написания пайплайнов в Airflow и интеграции моделей с MLflow Data Science бэкграунд: • понимание математики классического ML и архитектур нейросетей • базовые навыки профилирования кода и оптимизации использования памяти • опыт работы с табличными данными и современным стеком NLP/LLM будет плюсом: • понимание принципов работы корпоративных Feature Store (например, Feast) • опыт работы с векторными базами данных (Qdrant, Milvus, PGVector) • понимание базовых принципов работы CUDA и компиляции моделей (формат TensorRT и тд). Условия * комфортный современный офис рядом с м. Кутузовская * офисный формат работы * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте (для Junior позиций) * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * 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.

Location: Distributed About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available location: Seattle, WA What you will do as a Customer Engineer The Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey. You will bridge the gap between technical strategy and business value—guiding enterprise clients from initial pre-sales technical validation through onboarding, deployment architecture, and full lifecycle expansion. Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, leveraging AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire customer journey. Key Responsibilities Technical Validation: Partner closely with Account Executives to lead technical deep-dive discovery, capture business requirements, and map complex customer infrastructure - DNS, CDN, Zero Trust, Network Security, Workers - to fit-for-purpose Cloudflare architectures and bespoke solutions. Define, scope, success criteria, and technical evaluations plans for Proof of Concepts (PoCs) and Technical Validations. Deliver tailored technical presentations, architectural diagrams, and demonstrations that show how Cloudflare solves specific performance, security, and reliability challenges. Proactively address complex technical objections, security compliance questions, and edge-case architectural requirements during the sales cycle. Take accountability for a suitable solution deployment strategy (Customer, Partner or Cloudflare Professional services) being an integral part of all proposals. Customer Adoption & Value Realization: Provide oversight to technical onboarding and implementation, but not execute the implementation, serving as the primary executive and engineering contact for the customer. Design structured migration and onboarding blueprints tailored to the customer’s environment (e.g. DNS migrations, Zero Trust rollouts, WAF tuning guidance), and act as the lead consultant for customer engineering teams, walking them step-by-step through configuration best practices.  Partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. Proactively monitor customer health scores and telemetry to ensure rapid time-to-value, resolve integration bottlenecks, and reduce deployment risk. Commercial Accountability & Expansion: Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. Be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data. Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for C-level executives. Trusted Advisory: Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with key stakeholders from initial onboarding through maturity, renewal, and expansion. Provide thought partnership on architecture, AI control layers, security posture, and deployment confidence. Identify potential deployment risks or integration bottlenecks early, and provide remediation strategies to de-risk customer outcomes. AI Orchestration & Workflow Automation: Leverage AI agents, Large Language Models (LLMs), and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, basic telemetry monitoring, and internal/external documentation, reclaiming your time for strategic customer advisory. Education & Enablement: Partner closely with the Enablement Team to design, build, and govern technical resources. Define, document, and educate both internal teams and customers on deliverables such as Standard Operating Procedures (SOPs), architectural best practices, and technical guides to continuously raise the technical baseline across the organization. Minimum Qualifications Experience: Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Professional Services,  Sales Engineering, Technical Account Management, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Architectural Mindset: Ability to white-board, design, and articulate complex enterprise network and security architectures clearly. Consultative & Advisory Skills: Excellent communication skills with the ability to translate deeply technical concepts into business outcomes for both hands-on engineers and C-level executives. Commercial Mindset: Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and enterprise sales cycles. Communication: Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level C-suite business strategy. Technical Breadth: We do not expect every candidate to be an expert in every domain. Qualified candidates will demonstrate depth in at least four of the technical areas below: Internet fundamentals: Deep understanding of how the Internet works, including OSI Model layers 1–7, BGP, GRE, TCP/UDP, DNS (authoritative and recursive), HTTP(S), and SSL/TLS. Security: Expertise in the security of Internet properties, including WAF, Bot Management, Firewalls, Rate Limiting, (M)TLS, Zero Trust, and SASE concepts. Performance: Expertise in the performance of Internet properties, including speed, latency, caching, video streaming, HTTP/2, and TLS 1.3. AI Proficiency: Familiarity with prompt engineering, AI-assisted scripting and log analysis, LLM utilization, and workflow automation to augment everyday CE workflows. Coding/Scripting: Proficiency in Python, JavaScript, Bash, Lua, Go, or similar languages to write custom integration scripts, API connectors, and edge computing functions. Developer Platform Fluency: Experience designing, building, deploying or scaling applications using RESTful/GraphQL APIs, SDKs, webhooks, and developer tooling in cloud-native environments. Familiarity with infrastructure-as-code (Terraform, Pulumi), CI/CD pipelines, and observability for developer-led deployments. Strongly Preferred Qualifications (The "Good-to-Haves") Technical Enablement: Track record of creating and delivering technical enablement - workshops, code samples, documentation, or developer onboarding - that accelerates customer adoption of complex platforms. Applied AI Knowledge: Experience with LLM orchestration, Retrieval-Augmented Generation (RAG) architectures, and model-access controls. Regulatory Knowledge: Understanding of regulatory requirements such as PCI DSS, HIPAA, and SOC 2. Hyperscaler / Digital Native Background: Talent coming out of hyperscalers, digital natives, distributed systems environments, or startups is strongly valued for its deeper cloud fluency and advanced architecture depth. Education Undergraduate or graduate degree in Computer Science, Engineering, or a related field. Travel This role may require travel up to 20–50% to attend customer meetings, conferences, industry events, and in-person team collaboration. Compensation This role features a competitive base salary and a variable compensation structure tied directly to the successful execution of full-lifecycle commercial targets, including new business acquisition, ongoing adoption milestones, and overall account expansion. Compensation Compensation may be adjusted depending on work location. This role is eligible to earn incentive compensation under Cloudflare’s Sales Compensation Plan. The estimated annual salary range includes the on-target incentive compensation that may be attained in this role under the Sales Compensation Plan. For Washington: Estimated annual salary of $204,000.00 - $321,000.00 Equity This role is eligible to participate in Cloudflare’s equity plan. Benefits Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S. Health & Welfare Benefits Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Financial Benefits Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Time Off Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Основные задачи Разработка инструментов для агентов и интеграций с корпоративными системами (1С, почта, файловые ресурсы). Обработка документов: договоры, счета, таблицы.

Проектировать, разрабатывать и оптимизировать ML-пайплайны: от подготовки данных и обучения моделей до внедрения в production. Разрабатывать и дообучать ML/NLP-модели под продуктовые задачи.

Location: San Francisco Workplace: Remote Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data. As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI. THE TEAM AND YOUR IMPACT As our Senior Developer Relations Engineer in San Francisco, you'll lead Qdrant's developer engagement in one of the most active AI communities in the world. In this senior individual contributor role, you'll combine hands-on engineering (about 40% of your time) with public speaking, content, and community building (about 60%). Your impact will show up in two places. Externally, you'll turn your Bay Area relationships with engineers, founders, and event organizers into joint projects and workshops with our ecosystem partners, while your talks at premier conferences and your technical content reach hundreds of thousands of developers worldwide. Inside Qdrant, you'll bring what you hear from developers directly to our core engineering team to shape the roadmap, and you'll raise the bar for the DevRel team by starting new initiatives and mentoring others. WHAT YOU WILL OWN - Demos and applied research. Build and maintain open-source demo applications, such as end-to-end retrieval pipelines, recommendation engines, and AI search tools. Prototype new Qdrant use cases by experimenting with emerging patterns like neural sparse encoders, agentic workflows, and AI memory. - Technical content. Write in-depth technical articles, record video tutorials, and create practical guides that make complex concepts easy to follow. - Talks, events, and Bay Area partnerships. Give talks and live coding sessions at conferences, and lead Qdrant's presence at hackathons and workshops. Work with our partnerships team to turn local relationships into joint workshops, demos, and speaking opportunities. - Developer community. Answer technical questions on Discord, X, LinkedIn, and Reddit, and bring what developers need back to our product and engineering teams. WHO YOU ARE - Senior DevRel experience. You have 5+ years in software engineering, Developer Relations, or technical marketing, including at least 3 in Developer Relations. You've independently delivered technical talks, workshops, and community programs, and you can share examples of working applications and collaborations you started. - Technical depth and clear communication. You have strong software engineering skills in Python, Rust, TypeScript, or Go. You can build and debug applications that use vector search, embeddings, and large language models, and explain the "how" and "why" behind them, whether in writing or on stage. - Ownership of outcomes. You've owned a DevRel program or initiative end to end: you set the goals, chose what to build or say, and measured whether it worked, for example through adoption, community growth, or content reach. You can walk us through what you changed based on the results. - Influence beyond your own work. You've changed a product or engineering decision based on developer feedback, and you've helped other team members grow through mentoring, reviews, or shared practices. - Established San Francisco network. You're an active part of the Bay Area developer and AI community, with real relationships among engineers, event organizers, and founders. - Judgment and empathy for developers. You follow the AI ecosystem closely, test new tools for their practical value, and can tell useful technical work from hype. You understand what developers need and use that to choose topics and create content that respects their knowledge. NICE TO HAVE - Search and retrieval depth. You've worked on search or information retrieval systems, or at a search company, and understand how indexing, ranking, and relevance tuning work under the hood. - Applied research. You go deeper than tutorials. You read papers, run experiments or benchmarks, and turn what you find into something developers can use. - Video and social reach. You've built an audience through video or social media, for example YouTube tutorials, livestreams, or technical posts on X or LinkedIn. WHY JOIN US - A remote-first, international team working on cutting-edge AI infrastructure. - A competitive salary with additional perks. - Flexible working hours and async-friendly culture. - High ownership and real impact. - Open-source, engineering-driven culture. - Choose your own laptop equipment. For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy. Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist. Come build with us! FOR INFORMATION ON HOW WE HANDLE YOUR PERSONAL DATA, PLEASE REFER TO OUR RECRUITMENT PRIVACY POLICY https://qdrant.tech/legal/recruitment-privacy-policy/ #LI-REMOTE

— 2.5+ years of experience in Software QA and testing. — Hands-on experience with Azure AI Foundry / Azure OpenAI and Generative AI.

Location: Lisbon, Portugal Workplace: Remote Sensor Tower’s digital intelligence platform provides unparalleled insight into market trends, advertising, competitor’s strategies, and consumer/user audience across mobile, web, and gaming. Sensor Tower’s insights are trusted by more than 2,500 enterprises worldwide across tech, retail/commerce, entertainment/media, gaming, consumer packaged goods and finance. Our mobile gaming portfolio includes AppMagic and Playliner, which help game developers and publishers understand the mobile games market and how top games run their LiveOps. We’re looking for an AI Engineer to build LLM-powered prototypes for our gaming analytics products. You’ll turn product ideas into working prototypes on real data, find out quickly which ones are worth building, and then take the successful ones all the way to production together with our engineering teams. What you’ll do - Build AI prototypes for game analytics, with a focus on multimodal data: screenshots, images and gameplay video. For example, recognizing LiveOps events from in-game screenshots or extracting what changed in a game update. - Choose and use the right models for each task (mainly Claude), balancing quality, speed and cost. - Build data pipelines with our Data Engineer to run models on large volumes of game data. - Measure quality so we know what works and what doesn’t. - Build retrieval and multi-step pipelines. - Turn the best prototypes into real product features together with our engineers. Our tech stack Python, FastAPI, LangGraph, OpenCV, PostgreSQL, S3, Kubernetes, TypeScript, React What we’re looking for - Strong Python (TypeScript is a plus). - Experience with multimodal models: screenshots, images or video. - Hands-on experience building products on top of LLM APIs, not just chatbots. - Understanding of RAG and vector search, and when they’re not needed. - You measure results and can show how well your solution works. - You can work independently and explain your decisions clearly. - Ability to pass technical interview both in Russian & English. What we’d be particularly excited about - Interest in or experience with mobile games, LiveOps or market analytics. - Hands on experience in building AI projects - Experience with LangGraph, LlamaIndex or similar frameworks, and an opinion on when they’re worth using. Fraud warning: It's common for scammers to create positions that look legitimate on other sites. To ensure your submission is considered, only apply for positions at Sensor Tower through our company website or through posts directly associated with Sensor Tower company profiles on sites such as LinkedIn, Indeed, BuiltIn or Hackajob. At no point will Sensor Tower ever ask for money, credit card, or bank account information to complete a job application. Communications received from Sensor Tower are only sent by e-mail addresses ending in sensortower.com http://sensortower.com. All Sensor Tower interviews will be conducted via phone or Zoom. At no time will a conversation be moved to an alternative email outside of sensortower.com http://sensortower.com or text. Should an issue arise that you feel we should be aware of, please contact us. Please provide your resume when applying. To all recruitment agencies: Sensor Tower does not accept third party resumes. Please do not send resumes to our jobs alias, Sensor Tower employees or any other organization location. Sensor Tower is not responsible for any fees related to unsolicited resumes. Sensor Tower will not pay any third-party agency or company that does not have a signed agreement with Sensor Tower. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: Belgrade, Serbia Workplace: Remote Sensor Tower’s digital intelligence platform provides unparalleled insight into market trends, advertising, competitor’s strategies, and consumer/user audience across mobile, web, and gaming. Sensor Tower’s insights are trusted by more than 2,500 enterprises worldwide across tech, retail/commerce, entertainment/media, gaming, consumer packaged goods and finance. Our mobile gaming portfolio includes AppMagic and Playliner, which help game developers and publishers understand the mobile games market and how top games run their LiveOps. We’re looking for an AI Engineer to build LLM-powered prototypes for our gaming analytics products. You’ll turn product ideas into working prototypes on real data, find out quickly which ones are worth building, and then take the successful ones all the way to production together with our engineering teams. What you’ll do - Build AI prototypes for game analytics, with a focus on multimodal data: screenshots, images and gameplay video. For example, recognizing LiveOps events from in-game screenshots or extracting what changed in a game update. - Choose and use the right models for each task (mainly Claude), balancing quality, speed and cost. - Build data pipelines with our Data Engineer to run models on large volumes of game data. - Measure quality so we know what works and what doesn’t. - Build retrieval and multi-step pipelines. - Turn the best prototypes into real product features together with our engineers. Our tech stack Python, FastAPI, LangGraph, OpenCV, PostgreSQL, S3, Kubernetes, TypeScript, React What we’re looking for - Strong Python (TypeScript is a plus). - Experience with multimodal models: screenshots, images or video. - Hands-on experience building products on top of LLM APIs, not just chatbots. - Understanding of RAG and vector search, and when they’re not needed. - You measure results and can show how well your solution works. - You can work independently and explain your decisions clearly. - Ability to pass technical interview both in Russian & English. What we’d be particularly excited about - Interest in or experience with mobile games, LiveOps or market analytics. - Hands on experience in building AI projects - Experience with LangGraph, LlamaIndex or similar frameworks, and an opinion on when they’re worth using. Fraud warning: It's common for scammers to create positions that look legitimate on other sites. To ensure your submission is considered, only apply for positions at Sensor Tower through our company website or through posts directly associated with Sensor Tower company profiles on sites such as LinkedIn, Indeed, BuiltIn or Hackajob. At no point will Sensor Tower ever ask for money, credit card, or bank account information to complete a job application. Communications received from Sensor Tower are only sent by e-mail addresses ending in sensortower.com http://sensortower.com. All Sensor Tower interviews will be conducted via phone or Zoom. At no time will a conversation be moved to an alternative email outside of sensortower.com http://sensortower.com or text. Should an issue arise that you feel we should be aware of, please contact us. Please provide your resume when applying. To all recruitment agencies: Sensor Tower does not accept third party resumes. Please do not send resumes to our jobs alias, Sensor Tower employees or any other organization location. Sensor Tower is not responsible for any fees related to unsolicited resumes. Sensor Tower will not pay any third-party agency or company that does not have a signed agreement with Sensor Tower. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: Yerevan, Armenia Workplace: Remote Sensor Tower’s digital intelligence platform provides unparalleled insight into market trends, advertising, competitor’s strategies, and consumer/user audience across mobile, web, and gaming. Sensor Tower’s insights are trusted by more than 2,500 enterprises worldwide across tech, retail/commerce, entertainment/media, gaming, consumer packaged goods and finance. Our mobile gaming portfolio includes AppMagic and Playliner, which help game developers and publishers understand the mobile games market and how top games run their LiveOps. We’re looking for an AI Engineer to build LLM-powered prototypes for our gaming analytics products. You’ll turn product ideas into working prototypes on real data, find out quickly which ones are worth building, and then take the successful ones all the way to production together with our engineering teams. What you’ll do - Build AI prototypes for game analytics, with a focus on multimodal data: screenshots, images and gameplay video. For example, recognizing LiveOps events from in-game screenshots or extracting what changed in a game update. - Choose and use the right models for each task (mainly Claude), balancing quality, speed and cost. - Build data pipelines with our Data Engineer to run models on large volumes of game data. - Measure quality so we know what works and what doesn’t. - Build retrieval and multi-step pipelines. - Turn the best prototypes into real product features together with our engineers. Our tech stack Python, FastAPI, LangGraph, OpenCV, PostgreSQL, S3, Kubernetes, TypeScript, React What we’re looking for - Strong Python (TypeScript is a plus). - Experience with multimodal models: screenshots, images or video. - Hands-on experience building products on top of LLM APIs, not just chatbots. - Understanding of RAG and vector search, and when they’re not needed. - You measure results and can show how well your solution works. - You can work independently and explain your decisions clearly. - Ability to pass technical interview both in Russian & English. What we’d be particularly excited about - Interest in or experience with mobile games, LiveOps or market analytics. - Hands on experience in building AI projects - Experience with LangGraph, LlamaIndex or similar frameworks, and an opinion on when they’re worth using. Fraud warning: It's common for scammers to create positions that look legitimate on other sites. To ensure your submission is considered, only apply for positions at Sensor Tower through our company website or through posts directly associated with Sensor Tower company profiles on sites such as LinkedIn, Indeed, BuiltIn or Hackajob. At no point will Sensor Tower ever ask for money, credit card, or bank account information to complete a job application. Communications received from Sensor Tower are only sent by e-mail addresses ending in sensortower.com http://sensortower.com. All Sensor Tower interviews will be conducted via phone or Zoom. At no time will a conversation be moved to an alternative email outside of sensortower.com http://sensortower.com or text. Should an issue arise that you feel we should be aware of, please contact us. Please provide your resume when applying. To all recruitment agencies: Sensor Tower does not accept third party resumes. Please do not send resumes to our jobs alias, Sensor Tower employees or any other organization location. Sensor Tower is not responsible for any fees related to unsolicited resumes. Sensor Tower will not pay any third-party agency or company that does not have a signed agreement with Sensor Tower. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: Tbilisi, Georgia Workplace: Remote Sensor Tower’s digital intelligence platform provides unparalleled insight into market trends, advertising, competitor’s strategies, and consumer/user audience across mobile, web, and gaming. Sensor Tower’s insights are trusted by more than 2,500 enterprises worldwide across tech, retail/commerce, entertainment/media, gaming, consumer packaged goods and finance. Our mobile gaming portfolio includes AppMagic and Playliner, which help game developers and publishers understand the mobile games market and how top games run their LiveOps. We’re looking for an AI Engineer to build LLM-powered prototypes for our gaming analytics products. You’ll turn product ideas into working prototypes on real data, find out quickly which ones are worth building, and then take the successful ones all the way to production together with our engineering teams. What you’ll do - Build AI prototypes for game analytics, with a focus on multimodal data: screenshots, images and gameplay video. For example, recognizing LiveOps events from in-game screenshots or extracting what changed in a game update. - Choose and use the right models for each task (mainly Claude), balancing quality, speed and cost. - Build data pipelines with our Data Engineer to run models on large volumes of game data. - Measure quality so we know what works and what doesn’t. - Build retrieval and multi-step pipelines. - Turn the best prototypes into real product features together with our engineers. Our tech stack Python, FastAPI, LangGraph, OpenCV, PostgreSQL, S3, Kubernetes, TypeScript, React What we’re looking for - Strong Python (TypeScript is a plus). - Experience with multimodal models: screenshots, images or video. - Hands-on experience building products on top of LLM APIs, not just chatbots. - Understanding of RAG and vector search, and when they’re not needed. - You measure results and can show how well your solution works. - You can work independently and explain your decisions clearly. - Ability to pass technical interview both in Russian & English. What we’d be particularly excited about - Interest in or experience with mobile games, LiveOps or market analytics. - Hands on experience in building AI projects - Experience with LangGraph, LlamaIndex or similar frameworks, and an opinion on when they’re worth using. Fraud warning: It's common for scammers to create positions that look legitimate on other sites. To ensure your submission is considered, only apply for positions at Sensor Tower through our company website or through posts directly associated with Sensor Tower company profiles on sites such as LinkedIn, Indeed, BuiltIn or Hackajob. At no point will Sensor Tower ever ask for money, credit card, or bank account information to complete a job application. Communications received from Sensor Tower are only sent by e-mail addresses ending in sensortower.com http://sensortower.com. All Sensor Tower interviews will be conducted via phone or Zoom. At no time will a conversation be moved to an alternative email outside of sensortower.com http://sensortower.com or text. Should an issue arise that you feel we should be aware of, please contact us. Please provide your resume when applying. To all recruitment agencies: Sensor Tower does not accept third party resumes. Please do not send resumes to our jobs alias, Sensor Tower employees or any other organization location. Sensor Tower is not responsible for any fees related to unsolicited resumes. Sensor Tower will not pay any third-party agency or company that does not have a signed agreement with Sensor Tower. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: AU: Sydney (45 Clarence St) Workplace: Hybrid The role / impact As a Lead Engineer within the Internal AI Accelerator Squad, you will be at the forefront of Xero’s transformation into an AI-native company. You will act as a forward-deployed engineer, embedding yourself within various internal business teams to co-design and operationalise agentic AI workflows that remove manual toil and fundamentally reshape how our people work end-to-end. Your impact extends beyond the code; you will lead the delivery of high-stakes AI agents from discovery to production, while acting as a technical partner and evangelist. By defining the patterns, guardrails, and tooling for intelligent automation, you will create the blueprint that enables the rest of Xero to harness the power of AI safely and effectively. The team / how they connect You will join a dedicated, high-velocity squad focused on boosting the adoption of agentic AI and intelligent automation across the global business. The team connects through a shared mission of rapid experimentation and "vibe-coding," working closely with product owners and SMEs to turn complex, messy workflows into elegant, automated solutions. The team is currently working on / Initially, you will focus on - Designing and iterating on AI agents and workflow orchestrations using tools like Claude, Gemini, and MCP. - Integrating AI systems with core enterprise platforms including Salesforce, Workday, Slack, and NetSuite. - Developing reusable automation patterns and shared templates to be used by the business - Building evaluation and monitoring frameworks to measure performance and ensure the safety of AI-native workflows. Where and how you can work At Xero, we embrace a hybrid way of working that prioritises both flexibility and meaningful connection. You will have the autonomy to work from home, supported by regular boost days in our modern office spaces designed to foster collaboration, brainstorming, and team bonding. Here are some of the things we are looking for - You bring a wealth of experience in building and operating applications or automations within production environments, particularly involving APIs and cloud infrastructure. - Your background includes hands-on delivery of AI-driven solutions such as agents, copilots, or RAG systems using LLMs like Claude or Gemini. - You possess proficiency in programming languages such as Python or TypeScript and feel comfortable navigating SDKs and webhooks. - A systems-thinking approach is part of your toolkit, allowing you to design agents with security, auditability, and controlled blast radius at the forefront. - You have a track record of partnering with non-technical stakeholders to translate business pain points into technical solution designs. - You are a natural coach who enjoys uplifting the AI fluency of those around you through pairing, workshops, and clear communication.

Location: CAN: Vancouver (333 Seymour St) Workplace: Hybrid The role / impact As a Senior Engineer within the Internal AI Accelerator Squad, you will be at the forefront of Xero’s transformation into an AI-native company. You will act as a forward-deployed engineer, embedding yourself within various internal business teams to co-design and operationalise agentic AI workflows that remove manual toil and fundamentally reshape how our people work end-to-end. Your impact extends beyond the code; you will lead the delivery of high-stakes AI agents from discovery to production, while acting as a technical partner and evangelist. By defining the patterns, guardrails, and tooling for intelligent automation, you will create the blueprint that enables the rest of Xero to harness the power of AI safely and effectively. The team / how they connect You will join a dedicated, high-velocity squad focused on boosting the adoption of agentic AI and intelligent automation across the global business. The team connects through a shared mission of rapid experimentation and "vibe-coding," working closely with product owners and SMEs to turn complex, messy workflows into elegant, automated solutions. The team is currently working on / Initially, you will focus on - Designing and iterating on AI agents and workflow orchestrations using tools like Claude, Gemini, and MCP. - Integrating AI systems with core enterprise platforms including Salesforce, Workday, Slack, and NetSuite. - Developing reusable automation patterns and shared templates to be used by the business - Building evaluation and monitoring frameworks to measure performance and ensure the safety of AI-native workflows. Where and how you can work At Xero, we embrace a hybrid way of working that prioritises both flexibility and meaningful connection. You will have the autonomy to work from home, supported by regular boost days in our modern office spaces designed to foster collaboration, brainstorming, and team bonding. Here are some of the things we are looking for - You bring a wealth of experience in building and operating applications or automations within production environments, particularly involving APIs and cloud infrastructure. - Your background includes hands-on delivery of AI-driven solutions such as agents, copilots, or RAG systems using LLMs like Claude or Gemini. - You possess proficiency in programming languages such as Python or TypeScript and feel comfortable navigating SDKs and webhooks. - A systems-thinking approach is part of your toolkit, allowing you to design agents with security, auditability, and controlled blast radius at the forefront. - You have a track record of partnering with non-technical stakeholders to translate business pain points into technical solution designs. - You are a natural coach who enjoys uplifting the AI fluency of those around you through pairing, workshops, and clear communication. COMPENSATION & TOTAL REWARDS At Xero, we value the impact and skills you bring to the team. We don’t just hire for a role, we invest in people. We believe in a Total Package philosophy which means your value isn't just a single number on a paycheck. While base salary is a core component, we look at your compensation through a holistic lens that includes equity, performance incentives, and world-class benefits. The expected base salary range for this role in: - CAD $180K – CAD $210K - Plus bonus and equity Individual pay is determined by various factors, including geography, level of experience, and the specific skills you bring to the role. In addition to base pay, Xero’s roles are eligible for the following forms of variable compensation: - Variable Pay: Permanent employees are eligible to participate in our equity (RSU) programs. You may also be eligible for performance-based cash or equity (RSUs) incentives depending on your role level, and company performance. - Comprehensive Benefits: Medical, dental, vision, 401(k) match, and 21 days PTO. Xero also provides eligible employees with Wellbeing leave, volunteer leave, holidays, paid parental leave. Further information included on our Xero Perks page.

Location: Москва AI-команда блока развития клиентского опыта B2C приглашает опытного AI-инженера для участия в создании AI-агентов и LLM-решений, которые улучшают взаимодействие с клиентами - как внешними, так и внутренними пользователями Сбера. Мы строим передовые AI-инструменты на основе LLM, автоматизируем процессы и делаем сервисы персонализированными. Вы станете ключевым участником команды, которая внедряет AI-решения в реальные бизнес-процессы. Наше управление состоит из 45+ специалистов: Data Scientists, AI и ML-инженеров, MLOps и Project-менеджеров. Мы активно развиваем решения на базе LLM, трансформируя клиентский опыт. Обязанности * разрабатывать и внедрять LLM-пайплайны и AI-агентов: от генерации идеи и сборки MVP до успешного запуска в продакшн * дообучать LLM (на базе GigaChat) под конкретные бизнес-задачи и предметные области (Fine-tuning, LoRA) * оборачивать разработанные модели и бизнес-логику в надежные микросервисы на Python * переводить бизнес-потребности на язык машинного обучения и предлагать оптимальные архитектурные решения. Требования * опыт: от 3 лет в Data Science или NLP с уверенным практическим применением LLM * LLM & Agents: опыт разработки LLM-пайплайнов, RAG-систем или AI-агентов. Знание основных фреймворков: LangChain, LangGraph или аналогов * NLP & ML: глубокое понимание NLP - от классических подходов (TF-IDF) до современных трансформеров и LLM; знание основных принципов и алгоритмов классического ML * Python Backend: понимание принципов проектирования микросервисной архитектуры (REST API); опыт написания асинхронных и многопоточных приложений (aiohttp, asyncio, multiprocessing) * Инженерная культура: умение писать чистый, поддерживаемый и тестируемый код на Python * Владение Git, SQL, Bash, Docker. будет плюсом: * опыт интеграции AI-агентов и ML-моделей в высоконагруженные сервисы * интерес к SOTA-подходам в агентной разработке * практическое применение фреймворка DeepAgents в PET проектах * опыт работы с Kubernetes. Условия * комфортный современный офис рядом с м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * 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.

Location: Москва Мы новое подразделение Сбера, занимающееся созданием инструментов и решений для внутренней безопасности с помощью AI. Наши задачи направлены на развитие AI-агентов, создание RAG, запуск локальных инстансов LLM и их файнтюнинг. Наши планы имеют широкий спектр - начиная от разработки DL-моделей для скоринга, поведенческого моделирования и заканчивая графовыми нейронками для выявления скрытых связей. Сейчас мы в поисках Middle Data Scientist, который будет разрабатывать AI-агентов, адаптировать LLM под специфику задач, строить RAG-системы. Если ты хочешь иметь возможность погрузиться в глубины LLM и Deep Learning, пробовать новые методы к файнтюнингу LLM, строить AI-агентов, то мы ждем тебя в нашу команду. Обязанности * cоздание и развитие решений с задействованием LLM-агентов (полноценные мультиагентские системы) * cоздание RAG-систем * разработка и поддержка ML/DL моделей, включая их обновление и адаптация к меняющимся условиям и требованиям бизнеса * дообучение и адаптация открытых LLM * создание системы мониторинга качества моделей и контроль их эффективности. Требования * опыт работы от 3-х лет в коммерческой разработке на позиции Data Scientist / ML Engineer с подтверждённым опытом вывода моделей в продакшен * понимание математики классического ML и архитектуры нейросетей (PyTorch/TF) * уверенное понимание архитектуры трансформеров, опыт работы с LLM API и локальными моделями через PyTorch / Hugging Face * уверенный Python (чистый код, ООП, знание numpy/pandas/scikit-learn) и понимание принципов микросервесной архитектуры (Asyncio, FastAPI) * опыт создания агентов на LangChain/LangGraph * знание основных концепций промпт-инжиниринга и использования Structured Outputs и Function Calling * опыт проектирования и развития RAG-систем (Multi-stage Retrieval, Dense + Sparse/BM25, Rerankers, Chunking strategies) * опыт развертывания локальных open-source моделей (Llama, Mistral, Qwen, DeepSeek и др.) в продакшн-окружении и настройки высокопроизводительного инференса LLM с помощью vLLM * опыт проведения Fine-tuning LLM-моделей (PEFT, LoRA/QLoRA) * настройка мониторинга data drift и model decay, а также валидация моделей * навыки работы с генеративными AI-моделями; опыт создания AI-агентов и использования их в работе будет преимуществом * опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов * инструментальное владение AI для анализа, генерации и автоматизации. Условия * комфортный современный офис рядом с м. Кутузовская * офисный формат работы * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте (для Junior позиций) * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * 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.

Location: Москва Мы - молодая и динамичная команда, работающая над ключевым направлением развития процесса поддержки в Центре Снабжения. Наша цель автоматизировать рутину, и создать интеллектуальную экосистему, которая изменит подход к сервису. Наша текущая зона ответственности: * разработка мультиагентной системы для платформы Центра Снабжения * создание удобных цифровых рабочих мест для специалистов и руководителей службы поддержки * внедрение сквозной автоматизации управленческой отчетности. Мы строим процессы по гибкой методологии Agile, что позволяет нам быстро адаптироваться к изменениям и находить нестандартные решения. Проект уже стартовал, но мы на ранней стадии - фундамент заложен, а ключевые решения ещё принимаются. Это отличный момент, чтобы присоединиться: вы сможете предлагать свои идеи и влиять на то, каким станет продукт, не тратя время на поддержку устаревшего кода. В нашей культуре ценится открытость: мы напрямую взаимодействуем с бизнес-заказчиками и пользователями, обсуждаем требования и не боимся предлагать смелые идеи. Если вы разделяете ценности ответственности, непрерывного развития и стремитесь делать продукт, которым можно гордиться, нам по пути. Обязанности * проектирование мультиагентной системы поддержки: описание логики взаимодействия агентов, сценариев обработки запросов и маршрутизации задач * сбор и формализация требований к функциональности рабочих мест специалиста и руководителя службы поддержки * разработка и описание бизнес-логики автоматизации управленческой отчетности (метрики, дашборды, KPI) * взаимодействие с бизнес-заказчиками и пользователями: проведение интервью, семинаров, презентаций прототипов * составление технического задания и проектной документации (Use Cases, User Stories, диаграммы потоков данных, BPMN) * совместная работа с разработчиками на всех этапах — от идеи до релиза: разбор ТЗ, уточнение деталей, приёмка результатов * участие в выборе AI-инструментов и сценариев их применения в системе поддержки (классификация запросов, суммаризация, генерация ответов, предсказание инцидентов, оценка качества моделей через метрики точности/полноты/F1, контроль галлюцинаций LLM) * анализ и оптимизация процессов службы поддержки с точки зрения эффективности и пользовательского опыта. Требования * опыт работы системным-аналитиком от 3 лет * опыт проектирования сложных систем с распределённой логикой (желательно в сфере поддержки, сервисных платформ или автоматизации бизнес-процессов) * понимание основ AI/ML: знаете, как применять NLP для работы с текстами (классификация, суммаризация, извлечение сущностей, генерация), понимаете ограничения и возможности моделей * уверенное владение нотациями - BPMN, UML (диаграммы классов, последовательностей, потоков данных) * навыки работы с API: понимание REST, OpenAPI/Swagger, умеете читать и писать спецификации и проектировать контракты новых эндпоинтов * опыт работы по Agile/Scrum: ведение бэклога, участие в спринтах, ретроспективах * умение работать с требованиями: от сбора до управления изменениями, знание разных уровней требований (бизнес, функциональные, нефункциональные - производительность, отказоустойчивость, доступность) * отличные коммуникативные навыки: умеете говорить на одном языке с бизнесом и разработчиками, объяснять сложное простыми словами. Будет плюсом: * понимание принципов работы LLM, RAG, LangChain/LangGraph * опыт создания AI-агентов и использования их в работе будет преимуществом * опыт работы в Сбере. Условия * комфортный современный офис в Москве (ул. Вавилова 23стр1) * график работы – офис на период испытательного срока, гибрид * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте (для Junior позиций) * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * 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

Разрабатывать серверную часть прикладных информационных систем и ИИ-сервисов на Python. Реализовывать программные модули обработки и анализа структурированных и неструктурированных данных, в том числе технических документов.