Данные и ML вакансии

Задачи: — Чтение и запись коротких предложений — Прослушивание и сравнение аудиоклипов — Проверка произношения, ясности и естественности — Выявление неясных аудиозаписей — Следование предоставленным инструкциям и своевременная сдача заданий Требования: — Родной или свободный уровень владения хотя бы одним европейским языком (немецкий, французский, итальянский, испанский, португальский, нидерландский, шведский, польский и другие) — Понимание инструкций на английском языке — Чёткое и естественное произношение — Наличие смартфона или компьютера со стабильным интернет-соединением — Возможность записывать аудио в достаточно тихой обстановке — Ответственность и способность выполнять задания самостоятельно — Профессиональные навыки актёра озвучивания не требуются — Подходят начинающие Условия: — Полностью удалённая работа на неполный рабочий день — Гибкий график участия в проектах — Простые задания, которые можно выполнять из дома — Чёткие инструкции и поддержка команды — Возможность участия в будущих голосовых проектах Процесс подачи заявки: — Заполнить короткую форму заявки по ссылке — При необходимости предоставить краткий голосовой образец — Получить инструкции перед началом проекта Обратите внимание: команда регулярно рассматривает заявки. Для участия в проектах на малайском языке необходимо выполнить все шаги заявки.

Имплементация и поддержка в производстве высоконагруженных CV моделей. Создание, обсуждение и проверка гипотез по улучшению качества моделей.

разрабатывать с нуля AI-агентов и микросервисы для AI-продуктов. исследовать и внедрять новейшие технологические решения в ИИ - Claw-like & Ouroboros.

Твои задачи — RAG по методике и видеоурокам, файн-тюнинг LLM на русском и казахском, персонализация под профиль ребёнка. • Свой опыт файн-тюнинга (LoRA / QLoRA): сам собрал датасет, дообучил модель, измерил результат.

Задачи: — Проектирование, создание и поддержка надежных и масштабируемых ETL-процессов для обработки больших объемов данных. — Разработка и оптимизация SQL-запросов для извлечения и анализа данных. — Сотрудничество с командами аналитиков и разработчиков для определения требований к данным и обеспечению их доступности. — Участие в проектировании архитектуры данных и внедрении новых технологий. — Обеспечение качества данных и их интеграции из различных источников. Требования: — Хорошее владение SQL и PL/SQL; — Владение Python, Go; — Опыт работы с Apache Kafka.

Задачи: — проектирование и масштабирование корпоративного хранилища данных — интеграция источников и консолидация данных из учётных систем (в том числе SAP HCM/SAP BW) — проектирование витрин данных на основе требований бизнеса и топ‑менеджмента — внедрение процессов Data Quality и Data Governance для обеспечения качества данных Требования: — опыт в области DWH, ETL или Data Engineering от 3 лет — практический опыт проектирования и развития хранилищ данных — уверенное владение PostgreSQL, MS SQL, Python (для обработки данных, интеграций и автоматизации), Apache Airflow, Kafka, Git — приверженность подходу Data Governance — умение самостоятельно принимать, документировать и внедрять решения в промышленную эксплуатацию — будет преимуществом понимание принципов хранения данных в SAP HCM/SAP BW, требований BI‑систем к структуре и качеству данных, а также основных метрик HR‑отчётности.

TBC Uzbekistan is a digital financial services ecosystem powering some of Uzbekistan's most innovative financial experiences. Languages required: English (C1), Russian (B2). Work format: On-site in Tashkent, Uzbekistan.

Location: Hybrid - San Francisco, New York City About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role We're looking for an Engineer to lead the design and development of Vercel's Financial Data Platform, the foundational system that powers revenue reporting, consumption-based billing, financial forecasting, and compliance across the business. This is a unique opportunity to architect the data infrastructure that Finance, Accounting, and Revenue Operations depend on to close the books accurately, forecast revenue with confidence, and scale with the business. Reporting directly to the Senior Director of Data Engineering, you'll define the technical vision for Vercel's financial data ecosystem, partner closely with Finance, Accounting, and Revenue leadership to translate business and compliance requirements into scalable systems, and build reliable, auditable pipelines using modern technologies like Kafka, ClickHouse, Tinybird, and Snowflake. You'll lead from the front, writing production-grade code, setting the bar for data accuracy and governance in a domain where correctness isn't optional, and mentoring a team of engineers as the function grows. If you're excited by the challenge of building financial-grade data systems that the business trusts for reporting, forecasting, and audit, we'd love to hear from you. What You Will Do Design and implement a data platform that supports revenue recognition, consumption-based billing, and financial reporting across batch and real-time workloads, leveraging Kafka and streaming technologies to power real-time usage and billing pipelines feeding revenue and consumption forecasts. Work directly with FP&A, Accounting, and RevOps to understand reporting requirements, close-cycle timelines, and forecasting needs, translating them into technical architecture and ensuring data availability and accuracy align with financial reporting deadlines, audit cycles, and board-level reporting needs. Define and maintain guidelines for financial data ingestion, transformation, and storage, with a focus on auditability, lineage, and data integrity, while overseeing data modeling, ETL, and warehousing (ClickHouse, Tinybird, Snowflake) to support low-latency analytics and reliable historical reporting. Develop end-to-end solutions across the finance data stack, setting the example for engineering excellence in a high-accountability domain, and mentor engineers on both technical craft and the added rigor required when data feeds directly into financial statements. Partner with Security, Compliance, Legal, and Internal Audit to ensure financial data pipelines meet SOX, SOC 2, and other regulatory requirements, and champion high availability, fault tolerance, and auditability through comprehensive monitoring, alerting, and incident response. Drive architectural decisions and roadmap planning that balance efficiency, scalability, and the strict correctness requirements of financial systems, and evaluate build-vs-buy tradeoffs across financial and billing tooling (e.g., ERP, billing, and revenue platforms). Build the data infrastructure that translates raw usage into revenue, supporting the forecasting models Finance and GTM rely on for target-setting and reporting, and collaborate with data science and FP&A teams on forecasting, incrementality analysis, and revenue modeling at scale. Act as a key decision-maker for evaluating and selecting data architectures and technologies critical to Vercel's financial operations, and establish a multi-phase roadmap for finance data platform maturity aligned with company growth and audit readiness. About You 8+ years of experience in data engineering, analytics engineering, or a closely related field, with a track record of owning production data pipelines end-to-end. Proven track record designing and operating large-scale data infrastructures in a complex, fast-paced environment, with experience across Kafka and its ecosystem (e.g., Kafka Streams, Confluent Platform), ClickHouse, Tinybird, Snowflake, and broader big data frameworks. Prior experience building data pipelines that feed financial reporting, revenue recognition, billing, or consumption-based pricing models, with familiarity with financial/ERP systems (e.g., NetSuite, Workday) or billing platforms considered a strong plus. Proficiency in cloud platforms (AWS, GCP, or Azure) and associated big data services. Strong background in data governance, security, and compliance, including direct experience supporting audit, SOX, or SOC 2 requirements, and a rigorous approach to data lineage and accuracy. Outstanding communication and collaboration skills, with the ability to translate financial and accounting requirements into technical architecture and influence both technical and non-technical stakeholders, including Finance and Audit leadership. A leadership mindset, with demonstrated ability to mentor teams, drive consensus, and advocate for best practices in high-accountability data environments. Industry recognition or notable contributions in data engineering (e.g., published works, open-source contributions) is a plus. Compensation & Benefits: Competitive compensation package, including equity. Inclusive Healthcare Package. Learn and Grow - we provide mentorship and send you to events that help you build your network and skills. Flexible Time Off. We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed. The San Francisco, CA base pay range for this role is $264,000 - $396,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. Disclosures: Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data. Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

-Участвовать в разработке AI-решения для анализа документов, изображений и текста (KYC-верификация), включая работу с Computer Vision (CV), OCR и NLP. -Подбирать и адаптировать модели под бизнес-задачи.

Ищем исследователя, который будет разрабатывать стратегии дэска и доводить их до живой торговли. Разрабатывать стратегии на споте и бессрочных фьючерсах: рыночно-нейтральные и направленные.

- Оптимизация и масштабирование LLM-инференса (SGLang, vLLM, TensorRT-LLM). - Работа с моделями до 1T+ параметров и распределённой GPU-инфраструктурой.

Задачи: — Разработка на Oracle PL/SQL: хранимые процедуры, функции, пакеты, загрузки и витрины данных — Автоматизация процедур, обработка событий, мониторинг, логирование и алертинг — Валидация отправляемых данных, тестирование при выходе новых версий систем — Разработка и внедрение новых сценариев выявления в ГИС «Антифрод» (41-ФЗ) — Разработка моделей выявления мошеннических абонентов и вызовов: классификация, скоринг, поиск аномалий — Подготовка и обогащение данных (CDR, профили абонентов, сигнальный трафик, данные ГИС «Антифрод»), построение поведенческих и сетевых признаков — Обучение, валидация и оценка качества моделей, калибровка порогов под новые схемы мошенничества — Вывод моделей в промышленную эксплуатацию, мониторинг качества и переобучение — Работа с регулятором, операторами связи, банками и профильными подразделениями компании — Ведение документации по системам и сценариям, подготовка отчётов и презентаций — Выявление новых схем мошенничества, ведение матрицы рисков, участие в расследовании инцидентов вместе с безопасностью — Подготовка ТЗ на доработки ИТ-систем и участие в приёмке Требования: — Опыт от 4 лет в IT на позиции аналитика или разработчика (телеком, банки) — Техническое высшее образование (прикладная математика, информатика) — Продвинутый SQL и опыт разработки на Oracle PL/SQL — Python: pandas, NumPy, scikit-learn — Знание методов ML и метрик качества моделей — Знание видов телеком-мошенничества и методов их выявления, технологий мобильной сети — Excel (Power Query, OLAP, макросы), BI-инструменты — Желательно: Hadoop, Spark — Аналитический склад ума, коммуникабельность, умение работать со смежными подразделениями — Английский язык на базовом уровне — Опыт разработки антифрод- или скоринговых моделей (будет плюсом) Условия: — Гибридный формат (4 дня в офисе, 1 удалённо) — Полная занятость — Оформление по ТК РФ с первого дня — ДМС со стоматологией — Компенсация расходов на спорт и изучение языков — Материальные выплаты

Разрабатывать и сопровождать потоковые приложения на Apache Flink: подключать новые домены и типы событий, реализовывать дедупликацию, идемпотентную обработку, обогащение через Redis и маршрутизацию невалидных событий в DLQ; участвовать в восстановлении и дозагрузке данных;

• Опыт работы в сфере AI/ML от 5 лет.

-В первую очередь ищем сильного человека на усиление команды DE, поэтому фокус на разработку и оптимизацию текущих ключевых регламентных процессов. -50% времени - реализация задач по развитию DWH (анализ, разработка объектов DWH, dbt-моделей, потоков данных).

Задачи: — изучать материалы компании, искать идеи и референсы для видео — писать сценарии с помощью нейросетей — генерировать видео, озвучку, аватары и визуальные элементы — создавать обложки и описания для роликов — дорабатывать контент по обратной связи и пробовать новые AI-инструменты Требования: — интерес к ИИ и созданию контента — готовность самостоятельно разбираться в новых инструментах — насмотренность и интерес к трендам социальных сетей — инициативность, креативность и готовность предлагать идеи — умение работать с обратной связью и спокойно относиться к правкам Условия: — частичная занятость — график 5/2 — формат работы: удалённо или гибрид или офис

Location: Toronto; San Francisco; Canada; United States; New York; Ottawa; Montreal Workplace: Hybrid 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’re building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most driven, and most curious people to help us do it. As the head of the Data Foundation pillar of our Analytics and Data Insights team, you’ll lead the team that makes Cohere’s data trustworthy, governed, and available: the warehouse every analytics surface runs on, the pipelines that keep it fresh, the access model that keeps it secure, and the agentic analytics layer that lets anyone at Cohere (and their agents) ask questions of governed data directly. Your team owns the full data lifecycle. You’ll run ingestion into BigQuery from internal and external data sources, orchestrate it in Airflow and Cloud Run, model the data warehouse in dbt, and serve the results through Looker, export APIs, and customer-facing analytics surfaces. Everything is provisioned as code in Terraform, and governance is part of the design: VPC service controls, IAM patterns, and documented access paths that let people and agents move fast without putting data at risk. This role is both highly visible and highly impactful, and you’ll inherit a solid structure on which to build the rest of the stack: a Terraform-provisioned warehouse framework, dbt modeling conventions, an alerting and incident-response practice, and documentation patterns to keep everything discoverable. The roadmap is set with big bets in flight: scaling that framework across the company, standing up an internal analytics agent with a real eval harness, and consolidating institutional knowledge into a self-correcting and self-maintaining system that keeps context centralized, current, and documented, rather than dispersed and in people’s heads. Responsibilities As the head of the Data Foundation pillar, you will: - Build and lead the team. Hire and grow a team of data and infrastructure engineers; set the technical bar; develop strong talent and raise team performance, building leadership capability beneath you. - Set the roadmap from company strategy. Own and sequence the Data Foundation roadmap: the warehouse buildout, the agentic analytics program, data governance, and the platform work that unblocks our other pillars. You’ll make the trade-offs and carry the cross-functional impact that comes with them. - Own the data platform end to end. Ingestion (managed connectors and an open-source connector framework), orchestration on Airflow and Cloud Run, warehouse modeling in BigQuery with dbt (raw, core, mart layers), and serving through Looker, export APIs, and semantic layers. All of it provisioned as code in Terraform. - Own data governance. Define how humans, service accounts, and agents get access to governed data: VPC service controls, IAM patterns, documented onboarding paths, audit logs, and sensitive requests (including legal holds) handled to deadline. - Operate for reliability. Run the alerting and anomaly-detection framework, own data freshness SLAs, lead incident response and postmortems, and turn every incident into a durable standard so the same class of failure doesn’t recur. - Lead the agentic analytics program. Wire the semantic layer into an internal analytics agent, build the eval harness that measures its accuracy, and make the eval-driven call on where AI earns its way into production. Apply the same discipline to automating data engineering work itself. - Set the standard for analytics across the company. The medallion framework, naming conventions, and testing patterns your team maintains become the way other teams ship analytics data. You’ll onboard new domains onto it and keep the docs accurate to how the systems actually work. - Partner across the org. Work with the North product and engineering teams on the analytics surfaces that ship in the product (including a customer-facing analytics export), with Business Insights on marts for the business, with Security on data governance, and with Legal on compliance-critical data requests. QUALIFICATIONS You may be a good fit, if you have: - 10+ years of experience across data engineering, data infrastructure, or analytics platform work, with a strong management track record leading data platform or infrastructure teams - Serious hands-on history in data engineering or infrastructure before management. You can still read a Terraform plan, a dbt DAG, or an Airflow scheduler log and ask the question that matters - Production experience with cloud data warehouses (BigQuery, Snowflake, or similar), workflow orchestration (Airflow or similar), and infrastructure as code (Terraform or similar) - Depth in data modeling: you think in fact and dimension tables, raw/core/mart separation, and semantic layers, and you have opinions on where tests and contracts belong - A record of setting a team’s roadmap from company or function strategy and delivering outcomes that span teams, with the cross-functional partnerships to match - Operational excellence you can point to: alerting you trust, SLAs you meet, incidents you run to ground and write up so they teach - Exposure to data security and governance: IAM, access management, VPC service controls or equivalent, audit and compliance workflows - Genuine excitement about AI: you follow the research, have opinions, and are energized by building the data foundation an AI company (and its AI agents) runs on - Comfort operating in ambiguity, leading a multi-workstream roadmap, and working directly with executives on priorities If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Разработка и поддержка ETL/ELT пайплайнов на Python. Интеграция данных из различных источников (API, базы данных, файлы, облачные хранилища).