Вакансии

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Field Marketing Manager, you will lead the development and execution of regional marketing strategies to support sales goals, drive demand, and enhance brand awareness. This role requires a strategic thinker with a builder mentality that has a strong understanding of the New York or San Francisco tech ecosystem.   RESPONSIBILITIES - Develop and execute regional field marketing plans and programs to align with sales priorities and pipeline goals. - Plan and manage events to drive demand, accelerate pipeline, and engage customers. - Own program management, including event logistics, budget oversight, and vendor coordination. - Analyze and report on campaign effectiveness, providing insights to optimize future initiatives. - Collaborate with product marketing to align messaging and go-to-market strategies with field initiatives. - Prioritize seller requests by expected revenue. - Represent Baseten at industry events and build brand presence in-market.   REQUIREMENTS - Bachelor’s degree in Marketing, Business, or related field. - 5-7 years of experience in field marketing in the technology or SaaS industry. - Proven track record in delivering and optimizing demand generation programs to meet pipeline goals. - Strong understanding of sales processes. - Proficiency with marketing tools such as Salesforce & HubSpot. - Excellent project management skills with the ability to prioritize and execute multiple initiatives simultaneously. - Collaboratively with a growth mindset. - Strong interpersonal and communication skills with a collaborative mindset. - You actively use AI tools to drive your own productivity - in how you analyze data, structure problems, draft communications, and accelerate your work. - Ability to travel up to 25% for events and meetings. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

150 000 – 175 000 $

Ищем Tech Lead для руководства командой NLP-инженеров и backend-разработчиков, которая развивает платформу парсинга документов в банке. Специалист будет отвечать за техническое развитие продукта, архитектуру LLM/NLP-решений, управление бэклогом и качество реализации.

Зарплата не указана

This is the senior product role on a small, high-leverage product team. You'll own key pieces of the product line — from how we position it, to how we price it, to how the field sells it.

Зарплата не указана

Задачи: — работать с большими данными в экосистеме Hadoop (PySpark, SQL) — от выгрузки и разведки до построения витрин для моделей — разрабатывать индивидуальные модели эластичности и клиентского поведения в сегменте B2C — от прототипа до продвинутого пайплайна обучения и предсказаний — проверять бизнес-гипотезы и превращать их в измеримый эффект: дизайн и оценка A/B-тестов (мэтчинг, продвинутые методы causal inference, интерпретация результатов) — выстраивать коммуникацию с заказчиками: согласовывать метрики, защищать подходы, показывать ценность данных на понятном языке — обеспечивать надёжность и мониторинг внедрённых решений — чтобы модель работала стабильно и приносила пользу каждый день. Требования: — опыт работы Data Scientist от 2х лет — техническое образование (будет плюсом если выпускник - МГУ, МФТИ, ВШЭ и других ведущих вузов страны) — понимание теории вероятностей и статистики — уверенное владение широким спектром ML-алгоритмов — регрессия, классификация, кластеризация, а также uplift-моделирование (способность оценивать причинно-следственные эффекты, а не просто предсказывать) — владение Python и ML библиотеками (numpy, sklearn, pandas, matplotlib/seaborn/plotly, catboost/lightgbm/xgboost, etc.) — плюсом будет опыт работы с pytorch, pyspark Условия: — комфортный современный офис рядом с м. Кутузовская — возможность выбрать удобный график – офис/гибрид — ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования) — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте (для вакансий уровня Junior) — 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.

Зарплата не указана

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. Before you apply, we encourage you to explore our culture page https://www.kraken.com/culture to understand what drives us and how we work. PROOF OF WORK   THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools. You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.   THE OPPORTUNITY - Build and ship AI-powered agent systems that automate internal workflows and decision paths - Design and implement inference pipelines that reason over user interactions across internal systems - Prototype quickly to validate agent behaviors, then productionize what proves valuable - Architect backend services that integrate with multiple internal APIs and data sources - Define patterns for safe, observable, and controllable agent execution - Collaborate cross-functionally to identify high-leverage automation opportunities - Improve system speed, reliability, and signal quality as usage scales - Contribute to foundational design decisions for a 0→1 agent platform   SKILLS YOU SHOULD HODL - 5+ years of experience building and shipping production software systems - Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability) - Experience building fullstack systems, with comfort working across backend and occasional frontend surfaces - Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production - Ability to prototype rapidly while maintaining a clear path to production-grade architecture - Strong systems thinking — able to reason about orchestration, failure modes, and observability - Comfort operating in ambiguous, 0→1 environments with high ownership   NICE TO HAVES - Experience building or operating agent-based systems or autonomous workflows - Familiarity with prompt engineering, evaluation frameworks, or model performance tuning - Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.) - Background in building developer platforms or internal tooling - Experience designing guardrails, sandboxing, or safety layers for AI systems Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: United Kingdom; Brazil; United Arab Emirates; Ireland; Peru; Sweden; Colombia; Argentina; Romania; Cyprus; Switzerland; Portugal; Lithuania; South Africa; Czech Republic; Canada; Hungary; Mexico; Chile; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. Before you apply, we encourage you to explore our culture page https://www.kraken.com/culture to understand what drives us and how we work. PROOF OF WORK   THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools. You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.   THE OPPORTUNITY - Build and ship AI-powered agent systems that automate internal workflows and decision paths - Design and implement inference pipelines that reason over user interactions across internal systems - Prototype quickly to validate agent behaviors, then productionize what proves valuable - Architect backend services that integrate with multiple internal APIs and data sources - Define patterns for safe, observable, and controllable agent execution - Collaborate cross-functionally to identify high-leverage automation opportunities - Improve system speed, reliability, and signal quality as usage scales - Contribute to foundational design decisions for a 0→1 agent platform   SKILLS YOU SHOULD HODL - 5+ years of experience building and shipping production software systems - Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability) - Experience building fullstack systems, with comfort working across backend and occasional frontend surfaces - Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production - Ability to prototype rapidly while maintaining a clear path to production-grade architecture - Strong systems thinking — able to reason about orchestration, failure modes, and observability - Comfort operating in ambiguous, 0→1 environments with high ownership   NICE TO HAVES - Experience building or operating agent-based systems or autonomous workflows - Familiarity with prompt engineering, evaluation frameworks, or model performance tuning - Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.) - Background in building developer platforms or internal tooling - Experience designing guardrails, sandboxing, or safety layers for AI systems       Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Развивать и сопровождать инфраструктуру AI-платформы. Разворачивать и поддерживать сервисы в Kubernetes.

Зарплата не указана

Задачи: — Разработка генеративных ИИ-моделей для синтеза визуального и проектного контента на основе структурированных данных товарного каталога в рамках проверки гипотез (PoC) внутри корпоративной платформы по оценке ИИ-инициатив — Разработка архитектуры агентов: управление состоянием диалога и контекстом, динамический выбор инструментов (tool calling), настройка уровней автономности и сценариев human-in-the-loop — Построение системы метрик: разработка офлайн- и онлайн-показателей, кросс-валидация, прямая оценка бизнес-эффекта — Непрерывный мониторинг дрейфа моделей и качества данных в продакшене — Построение пайплайнов оценки (LLM Evals): контроль галлюцинаций, релевантности ответов и мониторинг поведения системы — Обеспечение безопасности: защита от prompt injection, предотвращение утечек персональных данных (PII/privacy) и аудит прав доступа агента — Оценка стоимости, latency и масштабируемости LLM-решений Требования: — Глубокое понимание жизненного цикла ML-модели: от подготовки признаков до интерпретации результатов — Знание методов борьбы с переобучением, data leakage, регуляризации — Уверенный выбор алгоритмов под задачу — Владение матстатистикой для проверки гипотез, расчета доверительных интервалов и самостоятельного дизайна A/B-тестов — Опыт работы хотя бы в одном из направлений: классическое машинное обучение, временные ряды и прогнозирование — Языки и библиотеки: Python (pandas/polars, NumPy, scikit-learn, CatBoost/XGBoost/LightGBM, PyTorch), продвинутый SQL — Написание поддерживаемого production-кода: модульная архитектура, юнит-тесты, логирование, документация, работа с GitFlow и код-ревью — Практический опыт работы с API языковых моделей, платформой Hugging Face и orchestration-фреймворками — Опыт работы в e-commerce, retail или других продуктовых highload-системах — Инфраструктура и оркестрация: Airflow, MLflow, Kafka, Redis, Kubernetes — Мониторинг и наблюдаемость: Prometheus, Grafana, OpenTelemetry — Опыт эксплуатации GPU-инфраструктуры и оптимизации inference — Адаптация моделей через fine-tuning (LoRA/PEFT) — Опыт проектирования agentic workflows или multi-agent-систем — Понимание принципов информационной безопасности, privacy и работы с персональными данными

260 000 – 300 000 ₽

As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale.

248 000 – 341 000 $

🔭Чем у нас занимаются стажеры? - Сразу после этого получают свою первую настоящую боевую задачку (и НЕ страдают, так как ментор всегда под рукой) на дизайн или оценку будущего эксперимента.

100 000 – 100 000 ₽

Задачи: - Разрабатывать, обучать и оптимизировать ML/AI-модели на PyTorch или TensorFlow - Проектировать end-to-end пайплайны обработки и подготовки данных - Работать с синтетическими данными и автоматизацией разметки - Интегрировать AI/ML-модели с backend и другими компонентами продукта - Подготавливать модели к production-деплою и масштабированию - Настраивать процессы мониторинга, версионирования и экспериментов с использованием MLOps-инструментов - Контейнеризировать ML-процессы с помощью Docker - Работать с облачной инфраструктурой AWS или аналогами - Участвовать в оптимизации inference и производительности моделей - Взаимодействовать с инженерами и другими участниками AI-команды на всех этапах разработки - Определять техническое направление AI-проектов, принимать ключевые архитектурные решения и обеспечивать техническое руководство командой на всех этапах разработки. Требования: - Опыт 4+ года коммерческого опыта в Machine Learning / AI Engineering - Практический опыт разработки и внедрения ML-моделей в production - Английский (свободный) - Уверенное понимание основ Machine Learning и Deep Learning - Знание методов оптимизации моделей и ключевых ML-метрик - Практический опыт с MLOps (MLflow/Kubeflow/AWS SageMaker или аналогичные) Условия: - Формат: Full-time - Локация: Ташкент (Офис) - Официальное трудоустройство по ТК УЗ - Занятость: полный рабочий день

Зарплата не указана

• Оптимизировать выдачу на страницах категорий, каналов и тегов. • Строить text-to-video поиск, embedding-модели, ранжирование, семантический поиск.

от 5 000 $

-Строить конвейеры подготовки данных: сбор, очистку, нормализацию, дедупликацию и разметку. -Формировать обучающие, валидационные и независимые оценочные выборки, контролировать утечки и пересечения.

Зарплата не указана

Location: San Francisco, California; New York, New York Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE: Notion has been at the cutting edge of AI since before ChatGPT launched. The job of the Model Capabilities team is to keep us there. We own the model layer of Notion AI: integrating frontier models as they ship, keeping inference reliable and economical at scale, and building new capabilities that other teams take advantage of.   This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. WHAT YOU'LL ACHIEVE: - Bring new frontier models into production quickly, making them available for our users and our engineers. - Make inference reliable: better error categorization, self-healing retries, and cross-provider failover. - Own observability for the model layer, driving down both time to detection and time to fix. - Build new model-level capabilities and help product teams adopt them. - Act as connective tissue across Notion's AI teams: find the gaps, unblock people, and make sure fixes land with the right owner. SKILLS YOU'LL NEED TO BRING: - Comfort with a moving frontier: The model landscape changes monthly. You keep up with it, form your own view of what's real, and stay pragmatic about what's worth adopting now. - AI fluency as a practitioner: You use AI tools seriously in your own work and have opinions about where they help and where they don't. - Production AI systems experience: You've built and operated systems on top of LLM APIs, not just prototyped with them. You understand token economics, streaming, tool calling, context limits, and how each of these fails in production. - Measurement before conviction: You don't ship a prompt or model change on vibes. You define what "better" means, build or use the evaluation to test it, and are willing to be proven wrong by your own data. - Cost and performance instincts: You treat latency and dollars as product qualities, not afterthoughts, and you can reason about the tradeoff between them and output quality. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $255,000 – $300,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy https://notion.notion.site/Notion-Global-Recruiting-Privacy-Policy-fc3eb4e829354a26a2bb6fd5e289b550?pvs=74 and NYLL 144 https://notion.notion.site/Ashby-AI-Bias-Audit-2b0efdeead05803bbbfae159ec86c528. #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Location: New York; Stockholm; San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. ABOUT THE DATA TEAM: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: - Self-serve AI analytics tools (Hex, Snowflake) - Embedding with teams as a “data adviser”, providing strategic analysis and consulting WHAT YOU'LL DO: - Contribute to building the most modern analytics stack https://modal.com/blog/analytics-stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting - Influence work on new products like LLM Inference Endpoints https://modal.com/blog/qwen3-8-2-4t-a95b-now-available-on-modal through product analytics tracking - Identify millions of dollars of cost savings and optimization across our tools and financial operations - Write data pipelines that power the operations of our business, such as our cloud compute economics or sales comp - Create foundational datasets that can be used by people and AI tools to answer questions around product use cases, financial reporting, and marketing campaigns WHAT YOU SHOULD HAVE: - SQL fluency, Python proficiency - Professional experience with at least 2 of the following tools: Snowflake, dbt, dlt, Modal, Hex, Posthog - Ability to extend their work beyond just data reporting and into action and impact - High attention to detail - Excellent and precise communicator - Strong personability and relationship building skills NICE-TO-HAVE: - Experience with AI products, especially LLM inference and sandboxes - Experience in fin ops, fraud, sales ops, or risk, especially in the context of AI (e.g. token cost optimization) - Project management skills - Strong presence in the data community online and offline

Задачи: — разработка и обучение ML-моделей, систем инференса, численных вычислений, оптимизация производительности и программирование на Python; — создание, решение, проверка и валидация сложных задач в области ML Engineering; — реализация или модификация ML-модели; — создание воспроизводимого процесса обучения или инференса; — оптимизация использования памяти или производительности; — поиск и исправление численных или системных ошибок; — проверка соответствия реализации требованиям по корректности и производительности; — разработка и проверка ML-моделей, training pipelines, inference-систем и вспомогательной инфраструктуры; — реализация компонентов моделей, data pipelines, систем оценки и численных методов; — создание воспроизводимых программных процессов с использованием Python и инструментов командной строки. Требования: — степень магистра или PhD; — опыт использования coding agents с Python в рабочем процессе; — уровень английского языка C1. Условия: — 15 часов в неделю; — оплата $80–$150 в час; — полностью удалённая работа с гибким графиком, специалист самостоятельно выбирает дни и часы работы, включая выходные при желании.

80 – 150 $

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a Corporate Accounting Manager to support the general ledger, the close, and our accounting processes and controls as Baseten scales. This is a hands-on, individual-contributor role for someone who wants full ownership of the core accounting function at a company where the entity structure, transaction volume, and reporting requirements are growing quickly. You’ll join the corporate accounting team and take on the general ledger, vendor contract review, the close calendar, and our internal control environment as the business grows. We are focused on tightening close procedures, strengthening controls, and building reporting rigor to support the scale ahead. You’ll partner closely with FP&A, Data, and cross-functional partners to make sure the books close on time and accurately every cycle. Baseten is building the infrastructure layer for AI-native companies, and we're scaling quickly - in headcount, entity structure, transaction volume, and contract complexity and volume and vendor size. If you want real ownership over a growing function on a lean team, this role offers real scope. RESPONSIBILITIES General Ledger and Financial Reporting - Own day-to-day execution of general ledger journal entries, account reconciliations, and monthly financial statement preparation as the entity structure grows - Own recurring close areas, including accruals, prepaids, fixed assets, and equity compensation - Lead month-end and year-end close, setting the calendar and holding FP&A, Data, and cross-functional partners so the books close on time every cycle - Prepare and review monthly financial statements and flux analysis for accounting and finance leadership - Identify and automate the manual, error-prone steps that slow the close down Controls and Audit - Partner directly with cross-functional teams and external auditors to keep internal controls tight and the company audit-ready - Own audit deliverables, including technical accounting memos, schedules, and sample testing support Systems and Cross-Functional Partnership - Support day-to-day administration and maintenance of our accounting systems stack, including NetSuite and our spend management platform, and push for automation over manual workarounds - Partner with FP&A on reporting, forecasting inputs, and variance analysis - Support FP&A, Legal, and Procurement on the accounting implications of new entities, contracts, and programs REQUIREMENTS - 5+ years of progressive accounting experience, including 3+ years focused specifically on corporate accounting, general ledger, and close management - Deep working knowledge of US GAAP across core corporate accounting areas, including accruals, prepaids, fixed assets, debt and leases - Hands-on experience owning account reconciliations and preparing monthly financial statements - Experience owning the close calendar directly, not just contributing to a close run by someone else - Public company or audit-ready private company experience (Big 4 or industry, with audit exposure) - Builder mentality with a bias toward execution; comfortable operating on a lean team relative to company scale - Experience with NetSuite (or comparable ERP) and a modern spend management platform - Based in San Francisco or New York, with the ability to work in-person 3+ days per week NICE TO HAVE - Experience at a high-growth, venture-backed infrastructure or cloud company - Experience supporting multi-entity or international consolidations - Integrate AI tools to optimize/redesign workflows and drive measurable impact - CPA - Exposure to SOX or SOX-readiness controls work BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Задачи: — Развивать модели прогнозирования спроса и ценовой эластичности — Исследовать подходы к causal inference, uplift-моделированию и оценки эффекта изменения цены — Проектировать временную валидацию, backtesting и бизнес-метрики качества

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