Данные и ML вакансии - удалённо

Location: United States Workplace: remote About the Project  We are looking for a Session Director to support live, supervised voice recording sessions for a multilingual conversational AI project. In this role, you'll facilitate recording sessions, provide real-time participant coaching, and monitor technical quality throughout, helping ensure recordings are natural, authentic, and meet project specifications.  What You'll Do  Manage session facilitation, real-time coaching, and recording quality monitoring throughout each session 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.     How to Apply?  Apply now by answering a few quick questions to join our database and become part of our growing community.    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: Germany Workplace: remote About the Project  We are looking for a Session Director to support live, supervised voice recording sessions for a multilingual conversational AI project in German (Germany). In this role, you'll facilitate recording sessions, provide real-time participant coaching, and monitor technical quality throughout, helping ensure recordings are natural, authentic, and meet project specifications.  What You'll Do  Manage session facilitation, real-time coaching, and recording quality monitoring throughout each session 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.     How to Apply?  Apply now by answering a few quick questions to join our database and become part of our growing community.    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: Remote USA; Canada Workplace: remote ABOUT YOU We are looking for an accomplished Principal Machine Learning Engineer to join our global ML organization. In this role, you will drive innovation across our machine learning ecosystem, architect advanced ML solutions, and mentor junior ML engineers around the world. You will play a key part in shaping our technical direction—leading complex ML initiatives, elevating engineering standards, and guiding teams as they build scalable, production‑ready machine learning systems. If you are ambitious, energized by solving challenging technical problems, passionate about developing talent, and excited to influence the future of ML/AI in the video game industry, this could be the perfect role for you. ABOUT US   Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Requirements: Modeling Depth Advanced Degree in Statistics, machine learning or related areas. Experience in statistics/ML expertise with a track record of leading high-impact data science initiatives at scale of billions of transactions. Hands-on experience creating, training and fine-tuning models not just integrating hosted model APIs. You should be able to walk through  the data, the objective, what broke, and the before/after evaluation numbers, and why the model did not perform as expected. Experience owning models in production: deployment, monitoring, drift detection, retraining — with real latency budgets, not just research notebooks. Production experience with classical ML for fraud/anomaly detection, recommendation, or churn/LTV (gradient boosting, deep learning, graph-based models). Technology Familiarity Supervised learning, transfer leaning on machine learning as well as neural networks Basic LLM knowledge, especially how to use it and where not to use it. MLOps foundations: feature stores, experiment tracking, model registries (MLflow/W&B-class), continuous training pipelines. Model serving and inference optimization (vLLM-class serving, quantization). Nice-to-Have: Publications, conference talks, or recognized open-source contributions to training/eval tooling . Graph-based fraud detection (fraud rings, device/account linkage).. Gaming, payments,  fraud, advertising  domain experience. Hands-on, up-to-date experience with modern AI tools (e.g., Claude, Copilot, Cursor) for code generation, review, and accelerating day-to-day engineering work. Benefits: We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes 100% company-paid medical, dental, and vision plans, unlimited Flexible Time Off, and a personalized career roadmap for each US employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.   Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the Data Scientist position, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification   Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements   Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com.

Задачи: — Проектировать микросервисы и API (REST/gRPC); — Создавать RAG и AI-агенты: разрабатывать системы генерации ответов на основе документов, цепочек рассуждений и логики Tool Calling (LangChain/LangGraph/LlamaIndex); — Работать с данными и текстом: парсинг, очистка и чанкинг текстов, извлечение сущностей (NER), классификация, реализация гибридного семантического и полнотекстового поиска; — Проектировать базы данных: работать с реляционными (PostgreSQL), векторными (Qdrant/Milvus/pgvector) и графовыми (Neo4j) базами под задачи GraphRAG; — Заниматься оптимизацией производительности, покрытием кода тестами (Pytest), написанием асинхронного кода на Python (FastAPI/Django); — Проводить code review и контейнеризацию приложений (Docker). Требования: — Опыт коммерческой разработки на Python от 2 лет для выпускников профильных факультетов ведущих вузов (МФТИ, НИУ ВШЭ, МГУ, ИТМО, МГТУ им.— Уверенное знание Python, асинхронного программирования, веб-фреймворков (FastAPI) и принципов проектирования микросервисной архитектуры (REST, Swagger, gRPC); — Практический опыт работы с LangChain, LlamaIndex, LangGraph, современными LLM (GPT, open-source модели) и фреймворками для создания AI-агентов; — Опыт обработки и классификации документов различных форматов (PDF, сканы), извлечения сущностей (NER, гибридный поиск) с использованием Transformers, BERT, SpaCy, Natasha; — Опыт работы с реляционными БД (PostgreSQL), NoSQL/кэшированием (Redis), векторными БД (Qdrant/Milvus/pgvector) и графовыми системами (Neo4j); — Опыт работы с брокерами сообщений (RabbitMQ, Kafka); — Владение инструментами контейнеризации и CI/CD (Docker, Git, S3); — Понимание полного жизненного цикла разработки ПО (SDLC); — Опыт работы по ТЗ с чтением схем (UML, BPMN).

Задачи: - Участвовать в разработке моделей для продуктивной среды; - Строить модели машинного обучения, улучшать качество; - Писать код, проводить code-review; - Предлагать способы оптимизации и совершенствования существующих инструментов. Требования: - Знание Python; - Опыт работы в рекомендательных системах/поиске; - Опыт работы в роли mle/ds от 5ти лет; - Знание теоретических и практических продвинутых методов машинного обучения; - Знание SQL, знакомство с hadoop-стэком; - Опыт работы с docker, kubernetes, pyspark, kafka, postgres, airflow; - Наличие опыта вывода разработанных решений в прод.

Задачи: - Поддержка и развитие существующих AI-модулей системы онлайн-прокторинга - Определение отсутствия лица и нескольких лиц в кадре - Реализация Face ID и проверки личности пользователя - Разработка Liveness-проверки (моргание, улыбка, движения головы, контроль дистанции до камеры) - Определение поворотов головы и направления взгляда - Анализ положения тела и правильности посадки пользователя - Выявление ухода пользователя из кадра и поворота от рабочей зоны - Обнаружение посторонних людей и объектов в кадре - Детекция смартфонов, наушников, часов и других гаджетов - Распознавание мониторов, ноутбуков, клавиатур, мышей и других объектов рабочего места - Определение посторонних движений и плохого освещения - Снижение количества ложных срабатываний моделей - Обучение, дообучение и замена AI-моделей - Оптимизация моделей с использованием CUDA - Интеграция AI-модулей через API - Развертывание локальных LLM на собственных серверах - Работа с моделями Qwen, Llama, Mistral, Gemma и другими open-source LLM - Интеграция GPT, Claude, Gemini и других LLM через API - Подбор и оптимизация AI-моделей под задачи продукта - Внедрение новых AI-библиотек и технологий Требования: - Уверенное владение Python - Практический опыт работы с Computer Vision - Практический опыт работы с LLM - Опыт локального развертывания open-source LLM - Опыт интеграции облачных LLM через API - Умение работать с существующим кодом и готовыми моделями - Опыт запуска и оптимизации моделей на GPU - Готовность поддерживать существующие AI-модули и разрабатывать новые - Самостоятельность и умение доводить решения до production - Проживание в Астане Будет плюсом: - Опыт работы с Hugging Face и Ollama/vLLM - Опыт использования TensorRT, ONNX и OpenVINO - Опыт разработки систем реального времени - Опыт создания AI-продуктов для Computer Vision Условия: - Полная занятость - Возможна стажировка - Официальное трудоустройство - Формат работы: удаленно - График 5/2 или свободный - Рабочий день — 8 часов или по договоренности - Заработная плата от 400 000 до 600 000 ₸ до вычета налогов - Долгосрочная работа над действующим AI-продуктом - Формат работы и уровень оплаты обсуждаются индивидуально

Задачи: — Анализировать опоздания и "плохо построенные" маршруты. — Писать промышленный код и выводить его в продакшн. — Общаться с заказчиком, формализовывать требования. — Креативить, предлагать новые идеи. Требования: — Уверенное знание Python и стандартных DS библиотек. — Знание хотя бы одного диалекта SQL (предпочтительней PostgreSQL). — Знание основ ML и задач дискретной оптимизации. — Высшее образование в одной из сфер: математика, компьютерные науки.

Location: Canada; Calgary; Winnipeg; Vancouver; Halifax; Edmonton; Toronto; Victoria; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models, to be exact) learn in similar ways to humans, by way of feedback. By labelling, ranking, auditing, and correcting model output, you will improve Large Language Models' performance for iterations to come, thus having a lasting impact on Cohere's technology. We are hiring Generalist professionals with broad backgrounds that span multiple consumer-facing or personal domains. This is a judgment-driven role, not passive data entry. You will review, assess, and provide structured feedback across a broad and evolving range of tasks, evaluating, stress-testing, and improving our models on English-language data spanning multiple modalities (text, image, and structured formats such as JSON, CSV/TSV, and Markdown). This is a great opportunity for professionals with strong analytical skills to contribute to high-impact annotation projects. Please Note: This is a part-time independent contractor position available within Canada only. We seek candidates who can commit to 16 hours per week at a CAD $30/hour contract rate. This role is BYOD 💻 (Bring Your Own Device, laptop). This position is remote. As an Data Annotation Specialist, you will: - Evaluate and rank model outputs: Complete preference and comparison tasks, assessing which responses best conform to project guidelines for accuracy, helpfulness, tone, and safety, and writing clear justifications for your judgments. - Stress-test and break models: Probe models adversarially to surface failure modes, unsafe behavior, and capability gaps, and document reproducible cases that engineering and research teams can act on. - Create datasets: Author high-quality prompts, responses, and exemplars to build training and evaluation datasets, following detailed specifications and editing machine-written or human-written outputs to standard. - Build and apply rubrics and taxonomies: Contribute to the design of grading criteria and rubrics, then apply them consistently to produce structured, high-quality annotations across task types. - Annotate and correct multimodal data: Label, audit, and rectify inaccuracies across text, image, and structured data, maintaining a high standard of data integrity and accuracy. - Calibrate and maintain consistency: Participate in calibration exercises and inter-annotator agreement checks to align on standards, and flag ambiguous or uncovered edge cases rather than guessing, since a single misjudgment replicated at scale degrades a model. - Adapt to experimental work: Take on new and evolving task types as project needs shift, applying sound judgment in areas where guidelines are still being developed. - Report on model performance: Surface and communicate quality and performance trends in model and agent behavior, giving cross-functional partners clear, well-evidenced feedback on where models succeed, fail, and degrade. You may be a good fit if you have: - 1+ years of experience in AI data annotation, LLM evaluation, content moderation, research, or a related analytical role, with exposure to quality assurance, and/or preference ranking. - Experience applying detailed guidelines to complex and often ambiguous content, with strong contextual and sociocultural judgment, sensitivity to nuance, tone, and register, and the ability to reason well in cases where there is no single correct answer. - Comfort with ambiguity: a willingness to flag unclear or uncovered edge cases rather than guess, and to work productively on novel, experimental tasks whose definitions are still evolving. - A sharp, curious eye for inconsistencies, subtle errors, and model failure modes, including the instinct to probe models adversarially and surface where they break. Familiarity with how large language models behave, such as hallucination, sycophancy, and instruction-following gaps, is a plus. - Excellent command of written English and strong reading comprehension, with the ability to clearly justify your evaluations, including why an output is correct or incorrect, high-quality or low-quality, and to write clear prompts and exemplars that explain your reasoning. Bonus points if you are fluent in another language! - Strong attention to detail and commitment to accuracy, with the ability to maintain consistency across high-volume and monotonous tasks. - Comfort working with annotation platforms and structured formats such as JSON, CSV/TSV, Markdown, XML, and YAML. - Strong execution in a remote environment, including good time management, comfort using new tools, and the ability to work independently in a global, asynchronous team. Candidate Journey - Initial Screening: Our Talent Team will review your application. - First Assessment: If selected to move forward, you’ll receive a multiple-choice assessment by email. - Second Assessment: Candidates who achieve a passing score will be contacted by a member of our team to complete a more comprehensive assessment focused on their area of expertise. - Video Screen: If selected to move forward, you’ll have a short video call with a member of our Operations Team. - Final: Selected candidates will receive an Independent Contractor Agreement. As an independent contractor, you maintain control over how you complete your work and may work with multiple clients simultaneously, although we ask you to declare if any of these are with a direct competitor of Cohere and maintain IP confidentiality of the Cohere project. Independent contractors are not eligible for health benefits or other benefits provided to employees. Compensation for services is provided to contractors by contractors invoicing for services provided pursuant to the terms of our agreement with the contractor. It is important to understand that as an independent contractor, continuous work is not guaranteed. The client-contractor relationship is fundamentally project-based, meaning engagements may be temporary, periodic, or intermittent based on our organizational needs and project availability. As an independent contractor, you should anticipate fluctuations in workflow and, therefore, compensation for services when Cohere does not require as many hours of services in a week. Prospective candidates, please be advised: this role involves working with human-generated and model-generated tasks that may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material.

Задачи: — Разработка и внедрение AI агентов и моделей машинного обучения — Создание и экспериментирование с GenAI моделями и агентными рабочими процессами Требования: — Владение Python и другими релевантными языками программирования — 3 года практического опыта с фреймворками и библиотеками машинного обучения (TensorFlow, PyTorch или аналогичные) — 2 года практического опыта в разработке и развертывании AI агентов и моделей машинного обучения — Глубокие знания облачных технологий, с акцентом на Microsoft Azure, включая платформы Azure Data и AI (Databricks, Fabric, AI Foundry)

Обязанности: - Разрабатывать и обучать модели машинного обучения, включая генераторы кандидатов - Улучшать модели оценки стоимости автомобилей - Разрабатывать решения для антифрода и модерации контента - Подготавливать и трансформировать данные для обучения и продакшена моделей - Упаковывать модели в сервисы и внедрять их в продакшен Требования: - Опыт оркестрации ML‑пайплайнов с помощью Airflow или Luigi - Умение программировать на Python или C++ - Навыки работы с SQL и NoSQL для подготовки и трансформации данных - Умение разворачивать решения в виде микросервисов с использованием FastAPI, gRPC или Docker - Хорошие теоретические знания в области машинного обучения - Понимание устройства и принципов работы одного из ML‑фреймворков или библиотек, например CatBoost или PyTorch

Location: Mexico Workplace: remote About the Role We're looking for an Automation Specialist to join our Movie and TV Metadata team — a unique, blended role for someone who wants to combine hands-on content work with the chance to build real AI and automation solutions. You'll start by working as a fully contributing project specialist, gaining first-hand knowledge of our workflows, and then progressively apply your technical skills to streamline and automate them. This is an exciting opportunity for those with a passion for movies, TV shows, and the film industry, who are also keen to apply their automation and AI skillsets to help streamline and improve operations — working closely with Project Managers and program leadership every step of the way. Project Details Job Title: Automation Specialist-1 Working Hours: 10:00-18:30 CDT (40 hours/ week)* Tuesday to Saturday or Sunday to Thursday shift  Duration: Contract -indefinite . Salary/Compensation: 480,000 MXN/ yearly Location: Mexico (Remote) Responsibilities Get hands-on with the Movie & TV Metadata project Perform quality assurance on movie and TV metadata by accurately following testing instructions and test cases. Ensure content review and curation adhere to project-specific quality standards, trademarks, style guides, and client-preferred checklists and glossaries. Complete assigned tasks to a high standard and on time, including repetitive work. Prioritise tasks and issues quickly and effectively, especially as requirements shift. Find opportunities to improve how we work Analyse workflow data and operational performance to identify inefficiencies, bottlenecks, and automation opportunities. Document opportunities, build a prioritised backlog, and translate your findings into clear, actionable recommendations for Project Managers and leadership. Track the impact of the solutions you build and iterate based on feedback and performance data. Design and build automation & AI tools Design, develop, and deploy automation and AI-assisted tools using approved platforms, under the guidance of your Project Manager. Use scripting or programming skills (Python, JavaScript, or equivalent) to build robust, maintainable solutions starting with proofs of concept and building toward a steady cadence of delivery. Create clear documentation and share knowledge with the wider team to support adoption of what you build. Keep an eye on emerging AI and automation tooling and bring good ideas back to the team. What We're Looking For Education No minimum degree requirement. Relevant technical certifications or demonstrable equivalent experience will be considered. Required Passion for and knowledge of the film and TV industry. Proven analytical capability — you can examine a complex workflow, identify the root cause of a problem, and design a structured solution independently. Proficiency in at least one scripting or programming language (Python, JavaScript, or equivalent). Advanced spreadsheet skills, including macros, formulas, and data models. Strong written and verbal communication in English (native or business-level), with the ability to explain technical ideas to non-technical audiences and navigate ambiguity with sound judgement. Highly organised and self-directed, able to stay motivated and deliver consistent results — even on repetitive tasks — in a high-volume, fast-paced, evolving environment. Nice to Have Practical experience with automation tools, scripting, or AI-assisted workflows in a professional or project setting. Background in data operations, content review, localisation, or a related field. Familiarity with automation platforms and AI tooling; experience with prompt engineering. Proficiency in one or more additional languages at a business level. No specific degree or minimum years of experience required — we care about what you can demonstrate. Good to Know This is a stationary, computer-based role requiring extended periods at a screen. You'll be working in a high-volume, evolving environment where priorities may shift. As part of standard project workflows, this role may involve exposure to content that could be considered sensitive (e.g. related to health, adult themes, violence, or other mature topics). Work Environment Requirements Comfortable maintaining focus in a stationary role with extended computer use. Willingness to work in a high-volume, evolving environment where priorities may shift. This role may involve exposure to content that could be considered sensitive (e.g. content related to health,adult themes, violence, or other mature topics) as part of standard project workflows.

Location: Remote, California, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role This is a unique role that sits at the intersection of economics, analytics, product, and strategy. You’ll combine rigorous quantitative analysis with customer research and commercial thinking to shape how Fivetran prices, packages, and monetizes its products. What You’ll Do Analyze product usage, deal, financial, and billing data to model pricing, packaging, and monetization scenarios. Design frameworks to assess willingness to pay, customer value, and price realization across customer segments and product lines. Conduct research on pricing strategies, packaging models, and monetization approaches across comparable and adjacent markets. Lead pricing and packaging strategy for new product launches, partnering with Product, GTM, and Finance to define commercial models Build value-based pricing and econometric models to quantify elasticity, customer ROI, and lifetime value. Design and execute pricing experiments Synthesize quantitative analysis, customer research, and competitive intelligence into executive recommendations that influence pricing strategy. Drive customer and prospect research to understand purchasing behavior, value perception, and pricing friction. Partner closely with Product, Analytics, Finance, Sales, Marketing, and Legal to deliver end-to-end pricing initiatives. Define KPIs and dashboards that measure pricing performance and identify optimization opportunities. Continuously evolve our pricing and packaging strategy to improve ARR growth, customer adoption, and value realization. Skills We’re Looking For 5–8 years designing or operating SaaS or sophisticated B2C pricing models, preferably with usage‑based or behavioral pricing experience Deep quantitative chops—an advanced degree (PhD/MSc) in Economics, Statistics, Operations Research, Applied Math, or similar Fluency in SQL and Python for large‑scale data analysis; proficiency with BI tools such as Looker or Tableau; bonus for dbt Hands‑on experience with conjoint, MaxDiff, Gabor-Granger, or Van Westendorp surveys and causal experiment design Strong attention to detail and data analysis skills – including interpreting results and recommending actions Proven record of turning complex models and analyses into recommendations and shipping changes that moved ARR, gross margin, or NRR Collaborative mindset with Product, Analytics, Finance, Sales, and Legal; you can navigate from whiteboard to contract terms with ease Strong communication and presentation skills with ability to influence at the executive level #LI-DJ1 #LI-Remote The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Pay Range $209,378 — $261,723 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: Spain; Serbia; Poland; Ukraine; Portugal; North Macedonia; Bosnia and Herzegovina; Romania Workplace: remote About Provectus Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.   Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.   Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX, Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for . Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire:   Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant  HR Interview. Soft skills and expectations HM interview. Tech questions; a live engine

Location: Home Based - Americas; Home based - EMEA The Workplace Engineering function sits at the intersection of traditional HR analytics and modern Product Engineering. We transform raw workforce data into a suite of "People Products" that drive high performance. We don’t just "report" on what happened; we engineer the tools and insights that determine what happens next. This new role will report directly to the Global Head of Workplace Engineering, and sits within our Data discipline inside of our People department. Experienced data professionals at Canonical live at the intersection of software, data, and the business. They don't just help surface analytic artifacts; they help transform them into a strategic asset that elevates decision making and innovation across our global operations (e.g., sales, marketing, engineering, and human resources). They balance technical precision with business pragmatism, designing and iterating on experiments, automations, and products that transform insights into valued outcomes. They shape tomorrow's AI/Data stack in open source, ensuring that Canonical remains at the forefront of data-driven excellence. Their curiosity is contagious and has an amplifying effect on data literacy and stewardship across the business teams they support. Location: This is a remote role based in the AMER or EMEA Region. The role entails Multi-Disciplinary Leadership:  Lead and mentor a specialized squad of People Data Scientists, Software Engineers, and UX Designers. You aren't just managing analysts; you are leading a product squad. Product Ownership on People Science: Bridge the gap between "HR-speak" and "Dev-speak", ensuring engineers understand the human behavioral intent behind the code. Strategic Insight & Business Outcomes: Move beyond descriptive metrics (e.g., turnover rate) to predictive and prescriptive insights (e.g., predicting attrition risk based on "Time-Product" engagement data). Data Stewardship & Product Storytelling: Act as the "Translator-in-Chief". Take complex data models and turn them into compelling narratives. Lead the development of AI Agents that can surface insights to managers in real-time. Ensure the "People Data Stack" is secure, GDPR/privacy-compliant, and acts as a "Single Source of Truth" across all People related offerings, products and services. “Effectiveness at Work” Strategy: Identify opportunities to leverage “High Tech” solutions in our People offerings, and free up more time for “High Touch”, human involvement, thereby maximizing human value. What we are looking for in you Background in data science, mathematics, or engineering, skilled in advanced statistics, data wrangling/science, databases (SQL, etc.) or software engineering. Strength in coding/scripting languages (Python, R, JavaScript, etc.), software engineering, visualization (e.g. Superset, Tableau), and automation. Ability to translate business questions to key research objectives. Ability to identify the best methodology to execute research, synthesize and analyze findings. Proven ability to lead and drive others to execute against well planned roadmaps, with a strong mentor/coaching mindset. Willingness to examine the status quo and be resilient in the face of challenges. Ambition to build tomorrow's AI/Data stack in open source. An exceptional academic track record from high school and university. Business level written and spoken English. Sincere personal motivation aligned with our mission. International travel 2-4 times a year for company events up to two weeks long. In addition we expect that you will match our values, by being: Precise, taking care to deliver correctness and clarity. Reliable, delivering high quality work that builds trust and confidence. Accessible, collaborating to build products and systems that are usable. Adroit, blending enthusiasm, knowledge, adaptability, style and character. Nice-to-have skills Experience with dbt (Data Build Tool), Airbyte, Ranger, Superset, Temporal, or Trino Basic understanding of containerization technologies such as Docker and Kubernetes Agentic Engineering Product management User experience and design What we offer colleagues We consider geographical location, experience, and performance in shaping compensation worldwide. We assess performance and revisit compensation twice annually to ensure we recognize outstanding colleagues. In addition to base pay, we offer a performance-driven annual bonus or commission. We provide all team members with additional benefits which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally. Distributed work environment with twice-yearly team sprints in person Personal learning and development budget of USD 2,000 per year Bi-annual compensation review Company recognition rewards 40 days annual leave per annum, including public holidays and our All Company holiday periods Maternity and paternity leave Team Member Assistance Program & Wellness Platform Opportunity to travel to new locations to meet colleagues, with Priority Pass for lounge access About Canonical Canonical is a pioneering tech firm at the forefront of the global move to open source. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. We are founder-led, profitable, and growing. Powered by worldwide distributed collaboration since our inception in 2004, we believe tech and business leadership can emerge anywhere. We have no central headquarters. Most of us work from home, but we are exceptionally disciplined about this. We have very high expectations of all colleagues, and are champions of excellence. Working here is a step into the future and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical is an equal opportunity employer We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.

Location: OPEN TO ALL LOCATIONS; Canada; New Zealand; South Africa; United Kingdom; Hong Kong; China; Rwanda; Uganda; India; switzerland; Kyrgyzstan; Spain; Bosnia and Herzegovina Workplace: remote Transcriber – Audio & Annotation Projects  Location - Global (Remote) We are looking to onboard Transcribers to support a range of upcoming audio processing projects. This role focuses on converting audio into accurate written text, with opportunities to contribute to annotation tasks depending on project needs. Key Responsibilities Transcribe audio files into clear, well-structured text Work with a variety of audio types, including: Single-speaker recordings Podcasts Multi-speaker conversations Identify speakers where applicable Ensure high accuracy and attention to detail Follow project-specific transcription and formatting guidelines Task Types 1. Transcription Tasks Convert audio content into written text Maintain consistency in formatting and structure Ensure clarity and completeness of transcriptions 2. Annotation Tasks (Project-dependent) Label or tag segments of text or audio Categorize content based on provided guidelines Support data quality and training datasets Requirements Proficiency in English Good written English Strong listening and comprehension skills Ability to follow detailed instructions and guidelines Previous transcription or annotation experience is a plus, but not required Availability Minimum 4 hours of availability required during scheduled transcription shifts Project Details Flexible working hours – complete tasks at your own pace within project timelines Tasks are completed via a secure online platform Full guidelines and instructions are provided for each task Ongoing support is available to ensure quality and consistency Multiple similar projects are planned throughout 2026, offering potential for continued work

Требования к кандидату: - Several years of experience as a Data Scientist - Strong Python skills - Strong SQL skills - Experience building production data products - Solid understanding of experimentation and statistics - Experience with modern data warehouses