Вакансии

Задачи: — Архитектура и внедрение production-ready AI / LLM / Computer Vision систем — Декомпозиция сложных технических задач — Оптимизация стоимости и латенси production рабочих нагрузок — Сотрудничество с техническими и бизнес-командами клиентов — Разработка и обучение моделей машинного обучения — Подготовка данных и проведение аналитики — Деплой и мониторинг моделей Требования: Обязательные: — 2+ года опыта в Machine Learning / AI (Data Scientist, ML Engineer, NLP, CV, Audio Engineer) — 2+ года разработки production AI / LLM систем — Свободное владение Python, TensorFlow, PyTorch, vLLM, LangGraph, LangChain (или эквивалентные) — MLOps: оптимизация стоимости и латенси — Знакомство с agentic tooling (Claude Code, Cursor) — Опыт с LLM, NLP или Computer Vision Желательные: — Опыт с GCP (Google Cloud Platform) — Опыт в content generation — Знание оптимизации локального inference — Опыт работы с LLM и генерацией контента Приветствуется портфолио с примерами production AI систем, которые вы разрабатывали.

Зарплата не указана

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 Enterprise at Baseten means the companies with the most to gain from AI and the most complexity in getting there: large digital natives running products at massive scale, and category leaders in software, financial services, healthcare, and beyond. They have the data, the distribution, and the budget. Most are still deciding what to build, what to run themselves, and what it should cost. That makes this a consultative sale. You'll spend as much time helping a VP of Engineering pressure-test their AI strategy as you will selling against an alternative, mapping use cases, framing build-vs-buy, and giving clear recommendations grounded in what you've seen work at the frontier. Then you'll do the enterprise work: multithreading across a buying committee, navigating security and procurement, and turning a first workload into an eight-figure relationship. You'll work alongside our founders, forward-deployed engineers, and GTM leadership, in a seat where the playbook is still being written. RESPONSIBILITIES - Own a revenue target end to end, from prospecting and outbounding through closing Tier 1 accounts in your verticals - Act as a strategic advisor on AI adoption: identify use cases, shape architecture decisions, and lead with clear, opinionated recommendations - Multithread across large organizations, from the engineers running evals to the executives funding the program to security, legal, and procurement - Win lighthouse customers that become references for their entire industry - Partner with forward-deployed engineering on technical evaluations, POCs, and architecture reviews - Feed signal back to product and engineering. What enterprises need next is a roadmap input we don't get anywhere else REQUIREMENTS - 8+ years of enterprise B2B sales experience in technology, ideally infrastructure, API/platform, or developer tooling - A track record of closing seven- and eight-figure deals by navigating multi-stakeholder buying committees and long, complex cycles - Demonstrated ability to run a consultative sale. You've helped customers define a strategy, not just evaluate a product - Strong technical acumen: you can hold your own on model serving, GPU infrastructure, latency, and API architecture - Experience selling into large digital natives or regulated industries (financial services, healthcare/life sciences, insurance, government) - Excellent communication and comfort with high autonomy in a fast-moving environment NICE TO HAVE - Direct experience selling AI/ML infrastructure, cloud compute, or model deployment platforms 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).

300 000 – 330 000 $

Meet Arago and the Aragonians Arago is an AI and computer hardware company whose mission is to drive the course of history forward. We do so by accelerating breakthroughs at the intersection of AI and semiconductors. Founded in 2024 by AI researchers and physicists with deep expertise in photonics, electronics, software, mathematics, and machine learning, Arago brings together a lean team of engineers and scientists from the world’s top companies and research labs. Composed of nine nationalities and operating from hubs in France, North America, and Israel, we believe in great science and fast achievements. Our work is guided by these core principles: Do great things: we deliver work we’re proud to sign our name to. High velocity: speed matters. We move quickly, one step at a time. One unit: we’re all in this together, with relationships grounded in trust, respect, and camaraderie. Arago is backed by executives from Apple, Arm, Nvidia, Microsoft, and Hugging Face, as well as prominent US and European deeptech venture firms and exited founders. Задачи: — Develop Arago’s quantization strategy for modern AI models, including precision studies, numerical format exploration, and model-level techniques to preserve accuracy under constrained precision. — Study the impact of analog noise on the performance and inference accuracy of machine learning models, including language models, diffusion, video generation, and world models. — Develop simulation tools to model analog behavior with minimal computational overhead. — Build and maintain Arago's internal experimentation pipelines for precision and performance studies on both physical and emulated prototypes. — Act as a technical point of contact between clients and Arago: analyze, port, and optimize client models onto Arago hardware, balancing throughput and accuracy. — Collaborate with the software and digital architecture teams to support architectural enhancements based on the operator content of frontier model architectures. Требования: — Background in mathematics, physics, computer science, or a related quantitative field. — Strong interest and skills in applied mathematics and statistics. — Strong experience with quantization of machine learning and AI models. — Strong understanding of modern model architectures, including language models, diffusion models, video generation models, and/or world models. — Experience studying the impact of numerical precision, noise, or approximation on model accuracy. — Experience with inference performance optimization. — Good knowledge of computer architecture, GPU architecture, or parallel computing. — Ability to build rigorous experimentation pipelines and translate research insights into practical engineering decisions. — GitHub profile with recent and relevant projects. — Language: English at a proficient level. French is a plus. Условия: — Competitive cash compensation, with final package based on location, experience, and the pay of team members in similar positions. — Meaningful stock option plan offered at the earliest stage of the company (included in the majority of full time offers). — Relocation bonus and coverage of moving expenses for relocation within 20 minutes of the company’s location. — Healthcare coverage (including family-friendly options), pension contributions, professional development support, and 25 days of PTO, in addition to public holidays. — Ownership of a key technical domain, with significant vertical and/or horizontal growth opportunities, based on performance and individual drive. — Reimbursement of 50% of the public transport subscription fee. — A high-paced, multicultural (with 10 nationalities), and engineering-led environment.

Meet Arago and the Aragonians Arago is an AI and computer hardware company whose mission is to drive the course of history forward. We do so by accelerating breakthroughs at the intersection of AI and semiconductors. Founded in 2024 by AI researchers and physicists with deep expertise in photonics, electronics, software, mathematics, and machine learning, Arago brings together a lean team of engineers and scientists from the world’s top companies and research labs. Composed of nine nationalities and operating from hubs in France, North America, and Israel, we believe in great science and fast achievements. Our work is guided by these core principles: Do great things: we deliver work we’re proud to sign our name to. High velocity: speed matters. We move quickly, one step at a time. One unit: we’re all in this together, with relationships grounded in trust, respect, and camaraderie. Arago is backed by executives from Apple, Arm, Nvidia, Microsoft, and Hugging Face, as well as prominent US and European deeptech venture firms and exited founders. What you’ll do As a Senior AI/ML Scientist, you will work at the intersection of modern AI models, numerical precision, and novel computing architectures. Your mission will be to develop the methods that allow AI models to run accurately, efficiently, and reliably on Arago’s computing system. This position combines strong quantization and “digital twin” aspects: understanding how frontier models tolerate reduced precision, defining the right numerical formats and quantization strategies, and building software representations of the processor to model the physical effects that impact AI model accuracy. This role is both scientific and practical. You will help shape the bridge between AI models and Arago’s hardware. Required Skills and Experience Background in mathematics, physics, computer science, or a related quantitative field. Strong interest and skills in applied mathematics and statistics. Strong experience with quantization of machine learning and AI models. Strong understanding of modern model architectures, including language models, diffusion models, video generation models, and/or world models. Experience studying the impact of numerical precision, noise, or approximation on model accuracy. Experience with inference performance optimization. Good knowledge of computer architecture, GPU architecture, or parallel computing. Ability to build rigorous experimentation pipelines and translate research insights into practical engineering decisions. GitHub profile with recent and relevant projects. Language: English at a proficient level. French is a plus. Responsibilities Develop Arago’s quantization strategy for modern AI models, including precision studies, numerical format exploration, and model-level techniques to preserve accuracy under constrained precision. Study the impact of analog noise on the performance and inference accuracy of machine learning models, including language models, diffusion, video generation, and world models. Develop simulation tools to model analog behavior with minimal computational overhead. Build and maintain Arago's internal experimentation pipelines for precision and performance studies on both physical and emulated prototypes. Act as a technical point of contact between clients and Arago: analyze, port, and optimize client models onto Arago hardware, balancing throughput and accuracy. Collaborate with the software and digital architecture teams to support architectural enhancements based on the operator content of frontier model architectures. Pay and benefits Competitive cash compensation, with final package based on location, experience, and the pay of team members in similar positions. Meaningful stock option plan offered at the earliest stage of the company (included in the majority of full time offers). Relocation bonus and coverage of moving expenses for relocation within 20 minutes of the company’s location. Healthcare coverage (including family-friendly options), pension contributions, professional development support, and 25 days of PTO, in addition to public holidays. Ownership of a key technical domain, with significant vertical and/or horizontal growth opportunities, based on performance and individual drive. Reimbursement of 50% of the public transport subscription fee. A high-paced, multicultural (with 10 nationalities), and engineering-led environment.

Задачи: — Разработка и развитие AI-платформы для healthtech-продукта на рынке США — Проектирование архитектуры продукта: модульный монолит / микросервисы, event-driven архитектура — Работа с Go как основным backend-языком — Разработка и интеграция AI/ML-сервисов на Python / FastAPI — Интеграция LLM, AI-агентов, RAG и self-hosted inference в продуктовую систему — Работа с workflow orchestration через Temporal — Проектирование API и интеграций: REST, API Gateway, FHIR / HL7, gRPC — Работа с базами данных и инфраструктурой данных: PostgreSQL, pgvector, Redis, Neo4j / Amazon Neptune — Участие в построении облачной инфраструктуры на AWS — Настройка и развитие DevOps-процессов: Docker, Kubernetes, GitLab CI/CD, Terraform — Обеспечение наблюдаемости систем через Prometheus / Grafana, CloudWatch, OpenTelemetry — Участие в вопросах безопасности, авторизации и compliance: OAuth2 / OIDC, управление секретами, шифрование данных, HIPAA / SOC 2 — Hands-on разработка платформенной части, не только архитектурное проектирование Требования: — Сильный опыт системного дизайна: сервисы, API, интеграции, базы данных, распределённые системы и облачная инфраструктура — Опыт разработки на Go и готовность писать код — Понимание AI / LLM на архитектурном уровне — Понимание интеграции AI-агентов, RAG и инференса в продуктовые системы — Опыт проектирования отказоустойчивых и масштабируемых систем — Понимание принципов event-driven архитектуры и workflow orchestration — Самостоятельность, ownership и готовность работать в условиях неопределённости стартапа — Английский язык для чтения технической документации и взаимодействия с партнёрами из США — Высшее образование в области IT, системного анализа, прикладной математики или инженерии Будет плюсом: — Архитектурный опыт построения AI / LLM-систем: агенты, RAG, self-hosted inference, vLLM — Опыт использования Temporal или аналогичных систем оркестрации workflow — Понимание распределённых систем: масштабирование, согласованность, отказоустойчивость — Опыт работы с графовыми базами данных — Опыт работы в стартапах или в роли founding / lead engineer — Понимание требований безопасности и compliance: HIPAA, SOC 2 или аналогичные стандарты — Опыт работы с AWS Условия: — Официальное трудоустройство по ТК РК — Работа из офиса в Астане — После 7–8 месяцев возможен гибридный или удалённый формат — Зарплата: $3 000–$4 000 — Опционы / доля в компании обсуждаются отдельно — Работа в healthtech-стартапе для рынка США — Возможность влиять на архитектуру продукта и технические решения — Участие в создании AI-платформы с реальным impact для healthcare-сферы

3 000 – 4 000 $

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 - Lead large-scale brand campaigns across digital, events, and out-of-home. - Partner with engineering and product marketing on major product launches. - Turn complex technical ideas into clear, compelling visual communication. - Evolve the Baseten visual identity into a brand system that scales. - Own projects end-to-end, from concept through launch, collaborating directly with marketing, product, engineering, and leadership. - Shape our employer brand and help define how new hires experience Baseten. - Raise the bar for craft across every customer touchpoint. REQUIREMENTS - You have a portfolio of exceptional work with outstanding visual craft and attention to detail. - You care deeply about quality and sweat the details. - You communicate ideas clearly and thrive in collaborative environments. - You know when to build systems, not just execute on assets. - You default to ownership and are comfortable leading highly cross-functional projects from concept through launch. - You're excited by technical products and know how to make complex ideas feel consumable without oversimplifying them. - You thrive in a fast-moving environment with a high bar for quality. - You have strong opinions about design and can articulate why something works - and why it doesn't. NICE TO HAVE - Motion design and animation experience - Experience designing for developers or highly technical audiences. 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).

Location: New York; San Francisco 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. THE ROLE: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. WHAT YOU'LL DO: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. PREFERRED QUALIFICATIONS: - A PhD in computer science, machine learning, or a related field. Candidates with a master’s degree and significant research or industry experience will also be considered. - A demonstrated record of research accomplishments in reinforcement learning, machine learning, foundation models, or related fields. - Experience with large-scale training and inference infrastructure, including distributed systems and multi-node GPU clusters. - Experience developing, training, optimizing, or deploying state-of-the-art large-scale models. - First-author publications at leading venues such as NeurIPS, ICML, ICLR, CoRL, CVPR, UAI, JMLR, or TMLR. - A mission-driven mindset and a strong desire to translate research advances into meaningful product impact. - A collaborative spirit and the ability to work effectively across research and engineering teams.

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

Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. The Opportunity We are seeking a Marketing Analytics Director to lead the evolution of our marketing data stack and raise the analytical rigor of the entire marketing organization. This is a critical role for a builder-practitioner who works at the intersection of Data Science, Marketing Strategy, GTM, and AI Operations. You won't just report on the funnel. You will build the systems that make every analyst on this team sharper, including the AI agents themselves. As the Marketing Analytics Director , you will be the lead architect of our data-driven growth engine, connecting high-level strategy with advanced technical execution. You will move beyond traditional reporting to build a self-sustaining marketing ecosystem, leveraging Google BigQuery, Grafana, and agentic AI to create a unified source of truth and a culture of analytical rigor. Your mandate is to move the needle on demand generation across the entire marketing funnel, while raising the standard for how analytical work gets produced, challenged, and shipped across the org. You will architect a dual-track target-setting framework that balances high-velocity top-of-funnel growth with deep-funnel quality, ensuring GTM resources are directed toward high-converting user cohorts optimized for Grafana adoption and long-term retention. You will be expected to engineer the underlying data schemas, design predictive models, and implement the BI frameworks that shape our global GTM strategy. We are looking for a technical expert who can translate complex data into clear executive-level direction and who proactively builds systems that prevent AI-generated noise from drowning out actual signals. What You'll Be Doing Strategic GTM Partnership: Serve as the primary strategic partner to the GTM Leadership team (VP of Demand Gen, VP of Regional and Events, Head of Marketing Ops, CMO, Revenue Operations, Sales leadership and more), translating complex data into a clear roadmap for demand generation and revenue growth. Dual-Track Target Setting: Architect and own a sophisticated forecasting framework that balances top-of-funnel volume with high-intent lead quality, optimized for Grafana Cloud conversion and retention. Predictive Modeling and ROI: Develop and maintain machine learning models (Attribution, MMM, LTV) to predict campaign impact and steer budget allocation toward the highest-ROI channels. Data Warehouse Architecture: Oversee the structure of marketing data within Google BigQuery, ensuring a scalable single source of truth that connects product usage data with marketing touchpoints. Causal Inference and Inflection Hunting: Move beyond descriptive analytics to perform causal inference and predictive trend analysis. When the data shows an anomaly, whether a 3-month spike, a regional dip, or a campaign that overperformed, isolate the window and dig in. Executive Storytelling: Transform technical data outputs into clear, compelling narratives for the executive team and board. Deliver a succinct read and go deep where pushed. Utilizing AI and Automation Agentic Insights: Deploy LLM-powered agents (Claude Code, MCP-based tooling, or comparable) to monitor BigQuery datasets and automatically flag quality shifts in the funnel before they impact revenue. Autonomous Workflows: Implement orchestration patterns (N8N, custom MCP servers, or equivalent) to build self-healing data pipelines and automated responses to market signals, such as automated spend shifts based on conversion anomalies. Predictive Quality Scoring: Build and deploy AI-driven scoring models that separate high-value potential users from low-signal volume, helping Sales and Marketing prioritize effectively. What Makes You a Great Fit 8+ years in Marketing Analytics, GTM Strategy, or Data Science, with at least 2 years in a lead architect capacity (IC track or player-coach; people management not required) within a high-growth SaaS or PLG environment. Demonstrated history as a force multiplier. You can point to specific tooling, rituals, evaluator systems, or frameworks you built that made other analysts or the broader org measurably better. A portfolio of dashboards you personally produced is not sufficient. Data Science and Engineering: Mastery of SQL and Python required. Deep experience architecting data environments in Google BigQuery, Snowflake, or similar warehouses. Hands-on AI fluency as a builder, not a user. You have built and shipped agentic systems with Claude Code, MCP, or comparable tools. You understand where LLMs fail and how to design around those limitations. You have built evaluator agents, prompt-grading systems, or analytical quality tooling in production. Automation Proficiency: Hands-on experience building complex logic and integrations using N8N, custom API orchestration, or MCP-based tooling. Visualization and BI: Advanced proficiency in modern data stack visualization tools (Grafana, Looker, Tableau) to build executive-grade dashboards. Strategic Acumen: Proven ability to create structure in highly ambiguous environments and build target-setting frameworks from scratch. MarTech Ecosystem: Deep familiarity with connectivity between Salesforce, marketing automation, and product-led data streams. Executive presence with experience presenting to executive and board audiences, including sound judgment about what data is and isn't ready to share up the chain. Bonus Points For Education: Bachelor's or Master's degree in a quantitative field (Data Science, CS, Statistics, Business Analytics). MBA or MS in Data Science is a significant plus. In the US, the OTE compensation range for this role is $ 178,503 - $ 214,203. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Задачи: — Разработка и улучшение biometric и identity verification решений — Создание production-level Computer Vision и ML-систем — Разработка алгоритмов Face Verification, Liveness Detection, Anti-Spoofing и Deepfake Detection — Оптимизация моделей для высоконагруженных систем — Работа с большими датасетами и подготовка данных — Внедрение современных исследований SOTA в production — Разработка и поддержка полного ML/CV pipeline — Участие в подготовке решений к международным сертификациям и тестированиям — Работа над AI-продуктами для банков, финтех-компаний, криптоплатформ, телеком-операторов и государственных организаций Требования: — Опыт работы ML Engineer / Computer Vision Engineer от 3 лет — Опыт работы с Face Biometrics, KYC, Identity Verification или Anti-Fraud решениями — Глубокие знания Computer Vision и Deep Learning — Уверенное владение Python — Опыт работы с PyTorch и/или TensorFlow — Опыт построения production-grade ML/CV систем — Опыт работы с large-scale datasets — Опыт оптимизации inference, latency и производительности моделей — Понимание архитектуры enterprise biometric systems — Английский язык на уровне B2 — Обязательное преимущество: Опыт подготовки решений к сертификации iBeta Level 2 или Опыт прохождения / участия в сертификации iBeta Level 2 Будет большим плюсом: — Опыт работы в biometric, KYC или identity verification компаниях — Участие в NIST FRVT Evaluations — Опыт разработки Anti-Spoofing и Liveness Detection систем — Опыт работы с Deepfake Detection — Понимание международных biometric compliance и certification standards — Опыт внедрения SOTA research papers в production — Опыт teamleading Условия: — Работа в международной AI-компании — Участие в разработке production-grade AI-продуктов для международных рынков — Официальное трудоустройство по трудовому договору — График 5/2, 8-часовой рабочий день — Работа в офисе в Алматы — Финальный оффер зависит от уровня экспертизы — Возможность работать над сложными задачами в области Face Biometrics, Digital Identity, KYC, AML, Fraud Prevention и Identity Verification

1 000 000 – 4 000 000 ₸

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 The Field Productivity & Enablement Lead is responsible for making our sales motion clear, practical, and repeatable. This person will help define how we sell at Baseten: how managers run the business, how reps qualify and advance deals, how sales works with FDE, product, marketing, and support, and how those expectations get turned into training and day-to-day habits. This is a senior individual contributor role for someone who excels at both strategy and execution. You'll shape the system, but you won't stop at slides or frameworks. You'll build the playbooks, run the training, coach to the behaviors, and help managers ensure the process is followed consistently. We're not looking for someone who wants to force-fit a single methodology onto the business. We're looking for someone who is fluent in MEDDIC/MEDDPICC, Command of the Message, Challenger, and similar approaches, and can take the best ideas from each, adapt them to a technical sales motion, and build an approach that fits how Baseten actually sells. You'll report to the Head of Enablement and Productivity. Frontline managers and reps are your primary customers. RESPONSIBILITIES - Manage operating model. Define the core rhythms for frontline managers, including 1:1s, forecast calls, pipeline reviews, deal reviews, and coaching cadences. Create clear expectations for how managers inspect deals, coach reps, and drive consistency across the team. - Sales process and stage design. Partner with sales leadership and RevOps to define stages, exit criteria, qualification standards, and pipeline mechanics. Help turn the sales process into something managers and reps can actually use, and make sure CRM and tooling reinforce the process instead of creating workarounds. - Cross-functional engagement. Clarify how sales engages FDE, solutions architects, product, marketing, and customer support. Define the handoffs, decision points, and joint working models that help teams support customers without confusion or duplicated effort. - Methodology, skills, and training. Help codify the sales methodology and build the training behind it. Deliver enablement sessions, coach managers and reps, and raise the quality of qualification, deal progression, and account planning over time. - Behavior change and adoption. Make the work stick. Measure whether the process is being used, where managers or reps are getting stuck, and what needs to change to improve ramp time, pipeline quality, forecast accuracy, and win rates. REQUIREMENTS You know what good sales execution looks like and can translate that into a system other people can follow. You can move from diagnosing a broken forecast call, to redesigning a stage framework, to standing in front of a room and teaching managers how to run a better pipeline review. You bring credibility with sales leaders, managers, and reps because you've seen how strong sales teams operate and you know how to make process useful instead of bureaucratic. You are structured, practical, and comfortable driving change across functions. Strong candidates may come from a mix of backgrounds such as: - A former AE or sales leader who has carried a quota, managed teams, and later moved into enablement, strategy, or operations. - A sales enablement or sales effectiveness leader with strong experience in methodology, manager training, and curriculum design. - A RevOps or sales strategy professional with deep process rigor and a strong point of view on pipeline, qualification, and inspection. - A management consulting or sales transformation background with experience building operating models and driving adoption in fast-growing teams. 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).

adjoe builds technologies behind mobile apps growth and monetization, leading in rewarded advertising with their product Playtime Arcade, connecting advertisers and publishers with over 770 million users annually. The Cloud Engineering team is responsible for the infrastructure supporting 5.5 billion daily ad requests, ensuring systems stay online, performant, and cost-efficient. They handle 400 million user events daily, traffic spikes of 150,000+ requests per second, and maintain a data lake for data scientists, BI, and real-time ML inference. The team runs Kubernetes with event-driven autoscaling and Karpenter, manages Kafka clusters for real-time streaming, and provisions infrastructure through Terraform. They prefer open-source alternatives over managed AWS services, using tools like Druid, Airflow, Grafana, Prometheus, Spark, Trino, MLFlow, Jupiter Hub, Elasticsearch, and Fluentbit to maintain a cloud-agnostic architecture. Cost efficiency is a key engineering constraint, including AI-based anomaly detection on infrastructure costs. Requirements: — 3+ years in DevOps, SRE, or Platform Engineering. — Experience designing and operating cloud infrastructure at scale. — Hands-on experience deploying and managing containerized applications in Kubernetes. — Experience with Kafka, Druid, Airflow, Spark, Terraform, and Gitlab on Kubernetes clusters. — Strong understanding of AWS services including EKS, DynamoDB, SNS, SQS, IAM, Lambda. — Infrastructure as code expertise with Terraform. — Knowledge of tradeoffs between managed AWS services and open-source alternatives. — Familiarity with microservice event-driven architecture, including topics, queues, and object storage. — Ability to support backend teams building high-performance Go services in distributed environments. — Experience building reliable, fast, predictable, and low-maintenance CI/CD pipelines. — Comfortable migrating workloads to self-hosted solutions and introducing new infrastructure tools. Relocation support to Hamburg, Germany is provided for candidates worldwide ready to join the team. Benefits: — Work on impactful infrastructure reaching hundreds of millions of users and powering billions of decisions daily. — Ownership of projects affecting 770 million users. — Fast-paced environment with multiple daily solution deployments. — Open problem solving and cross-team collaboration. — Diverse global team from over 40 countries. — Positive work culture celebrating wins and daily victories.

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adjoe builds technologies behind mobile apps growth and monetization, leading in rewarded advertising with their product Playtime Arcade, connecting advertisers and publishers with over 770 million users annually. The Cloud Engineering team is responsible for the infrastructure supporting 5.5 billion daily ad requests, ensuring systems stay online, performant, and cost-efficient. They handle 400 million user events daily, traffic spikes of 150,000+ requests per second, and maintain a data lake for data scientists, BI, and real-time ML inference. The team runs Kubernetes with event-driven autoscaling and Karpenter, manages Kafka clusters for real-time streaming, and provisions infrastructure through Terraform. They prefer open-source alternatives over managed AWS services, using tools like Druid, Airflow, Grafana, Prometheus, Spark, Trino, MLFlow, Jupiter Hub, Elasticsearch, and Fluentbit to maintain a cloud-agnostic architecture. Cost efficiency is a key engineering constraint, including AI-based anomaly detection on infrastructure costs. Requirements: — 3+ years in DevOps, SRE, or Platform Engineering. — Experience designing and operating cloud infrastructure at scale. — Hands-on experience deploying and managing containerized applications in Kubernetes. — Experience with Kafka, Druid, Airflow, Spark, Terraform, and Gitlab on Kubernetes clusters. — Strong understanding of AWS services including EKS, DynamoDB, SNS, SQS, IAM, Lambda. — Infrastructure as code expertise with Terraform. — Knowledge of tradeoffs between managed AWS services and open-source alternatives. — Familiarity with microservice event-driven architecture, including topics, queues, and object storage. — Ability to support backend teams building high-performance Go services in distributed environments. — Experience building reliable, fast, predictable, and low-maintenance CI/CD pipelines. — Comfortable migrating workloads to self-hosted solutions and introducing new infrastructure tools. Relocation support to Hamburg, Germany is provided for candidates worldwide ready to join the team. Benefits: — Work on impactful infrastructure reaching hundreds of millions of users and powering billions of decisions daily. — Ownership of projects affecting 770 million users. — Fast-paced environment with multiple daily solution deployments. — Open problem solving and cross-team collaboration. — Diverse global team from over 40 countries. — Positive work culture celebrating wins and daily victories.

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Location: New York 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. THE ROLE: We're looking for a People Operations Generalist to join our growing People team. You'll touch the employee lifecycle end-to-end — from offer acceptance through offboarding — while helping to build the processes and documentation that let our People function scale with the business. This is a great fit for a highly organized, systems-oriented people person who thrives in a fast-paced environment and wants to build operational foundations, not just maintain them. WHAT YOU’LL DO: - Own and continuously improve the new hire onboarding experience, ensuring employees are set up for success and internal tasks are tracked and completed on time. - Serve as a first point of contact for employee questions across the full HR spectrum, triaging and routing more complex issues to the right People team member or external partner. - Maintain and improve self-service resources (FAQs, Notion pages, etc.) so employees can find what they need quickly — and always feel supported even when no one's in the room. - Support rollouts of new People programs and policies, including communication planning, manager enablement, and documentation. - Help bring employee experience programs and events to life, from team offsites to milestone recognition, that reinforce culture and make people feel valued. - Process employee changes (promotions, equity refreshes) accurately and on time, including preparing updated employment letters and maintaining compliant employee files. REQUIREMENTS: - 2+ years of People Operations experience, preferably at a high-growth startup. - Demonstrated ability to build and document HR processes from the ground up, not just execute existing ones. - Strong written communication: you write clearly, keep things simple, and know your audience. - Experience managing employee data with accuracy and discretion. - Comfortable handling competing priorities without losing track of the details.

Location: Hybrid - San Francisco 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 are hiring a Strategic Finance Manager, Product (EPD) to partner with Engineering and Product to drive unit economics, infrastructure efficiency, and margin expansion across Vercel’s consumption-based platform. This role spans cloud infrastucture & token spend, as well as emerging AI workloads (inference, gateways, and compute-intensive services). You will define how we measure and optimize the cost and profitability of every request, workload, and AI interaction on the platform. What You Will Do: Infrastructure & AI COGS Ownership Own financial visibility into compute, bandwidth, storage, and AI-related costs (e.g., inference, GPU/accelerated workloads) Translate product and infrastructure usage (requests, execution time, tokens, etc.) into clear cost drivers Partner with EPD to drive cost-efficient architecture and scaling decisions Cost Visibility & Accountability Build self-service cost tooling for Product and Engineering (cost per request, per workload, per AI query) Enable teams to own and optimize their infrastructure footprint Standardize cost attribution across products and multi-tenant systems Efficiency & Margin Expansion Lead infrastructure and AI efficiency initiatives (compute optimization, caching, vendor strategy) Define north star metrics (e.g., cost per request, cost per AI call, cost per GB) Embed cost efficiency into roadmaps and product decisions Cost Allocation & Financial Rigor Develop scalable cost allocation frameworks across products, customers, and workloads Improve gross margin visibility, including AI product margins Support auditability and IPO readiness Cross-Cutting Workstreams Unit Economics Define product-level unit economics across Vercel’s product suite Connect usage (requests, compute, tokens, etc) to revenue and COGS COGS / Gross Margin Forecasting Build driver-based models linking usage, revenue, and infrastructure costs Forecast COGS across core platform and AI products for both PLG & SLG segments Model margin impact of scale and efficiency improvements Pricing & Packaging Partner on usage-based and AI pricing models Evaluate tradeoffs between growth, adoption, and margin Ensure pricing is reflected in forecasts and unit economics About You: 5-8+ years in Strategic Finance, FP&A, IB, or Consulting Experience with consumption-based or cloud infrastructure businesses Strong modeling skills; experience with driver-based forecasting Ability to partner with technical teams and translate usage → financial insight SQL / data tooling experience strongly preferred 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 $180,000-$220,000. 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.

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 Product at Baseten is a nascent function. Our company today has a strong engineering culture, is heavily customer obsessed, and moves fast. We're building the product function now, and you'd be one of the first people who will help define it. You'll work directly with our founders and with some of the best systems and infrastructure engineers in the world, and you'll set the standard for building great AI infrastructure. PMs at Baseten don't sit above engineers. You earn ownership by being technical, finding the truth in front of customers, building great cross-functional relationships, and shipping great product experiences. Getting a model into production still takes real expertise: choosing a serving engine, sizing hardware, tuning it, wiring it into an app. We want a developer to go from "it runs on my laptop" to "it's serving production traffic" in minutes, on their own. You'll own the entire experience a developer touches to deploy and iterate: the CLI and SDKs, the console, onboarding, model discovery, deployment configuration, Truss, and the increasingly agent-driven ways developers build. Your job is to make Baseten synonymous with great DevEx and make it effortless for far more developers to self-serve deploy models on Baseten than can today. This role fits someone who gets technical by instinct and does whatever it takes to ship for customers, not only strategy, UX, or docs. You'll define the design system and the patterns from scratch rather than work inside ones someone else built, and you're obsessed with improving your product craft with AI. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Product and Engineering teams: - Building multi-component AI workflows at scale with Chains https://www.baseten.co/blog/baseten-chains-explained/ - Announcing Baseten for Model Labs https://www.baseten.co/blog/announcing-baseten-for-model-labs/ - Introducing canary deployments on Baseten https://www.baseten.co/blog/canary-deployments-on-baseten/ RESPONSIBILITIES - Collapse time to production, taking a developer from first sign-up to a running, maintained production deployment and driving down the time it takes to get there. - Make the CLI and SDKs the primary way developers and their AI agents build on Baseten, converging the authoring surfaces (CLI, console, Truss, config.yml, model.py, chains.py) into one coherent path. - Make a developer's first run effortless across onboarding, model discovery and deploy via the Model Library, and a first deploy where errors surface clearly and builds show progress. - Own the deployment lifecycle that lets teams ship safely, including environment promotion from dev to staging to prod, version history, an artifact and model registry, reproducible deployments, and the progressive delivery controls developers set and read: canary, shadow, A/B, scheduled promotion, and one-gesture rollback. - Define how developers compose multi-model apps through Chains and the DevEx for developers building multi-modal agents and applications. - Grow self-serve deployment across FDEs and customers by living in customer conversations and turning deploy-and-operate friction into roadmap, so work that needs an FDE today becomes something a developer does alone. REQUIREMENTS - 5+ years building developer-facing or technical products, as a product manager or as a product-minded engineer. - Built dev tools as an engineer before becoming a PM, shipping SDKs, CLIs, APIs, or platform surfaces with your own hands. - Proof of dev tooling and dev products you've shipped and take pride in. - Genuine taste for developer experience across both local (CLI) and UI, with a specific example of where you made something complex feel simple. - Strong opinions on CLI, API-first, and agent-first design, treating the coding agent as a first-class user rather than a feature. - Technical enough to earn engineers' trust and reason about what's under the hood, because you've been under it. - A rigorous researcher who lets customer reality drive the call, and a relentless shipper NICE TO HAVE - Experience with ML infrastructure, developer tools, or API products. - You've deployed and served models yourself. 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).

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 At Baseten, we’re looking for a Technical Program Manager to drive our most complex, cross-cutting infrastructure programs. This role will operate across all domains of AI infrastructure, from the GPUs up to the multi-cluster orchestration layer. This is an execution-first role. The work is less about owning a single system and more about imposing order on ambiguity: standing up the right structures, driving decisions to closure, and making sure nothing falls through the cracks across dozens of stakeholders. If you take satisfaction in turning a chaotic, half-defined initiative into a predictable, well-governed program, this role is for you. RESPONSIBILITIES - Own complex migrations end to end. Lead large-scale infrastructure migrations across teams and domains. This will involve scoping the work, sequencing dependencies, managing risk, and driving them to completion without surprises. - Drive process across infrastructure. Establish and run the operating rhythms that keep programs healthy: planning cadences, status reporting, decision logs, risk reviews, and escalation paths. Make the process light enough that teams adopt it and rigorous enough that it actually works. - Help managers build the right structures. Partner with engineering managers and leads to design the team structures, ownership boundaries, and working models a program needs to succeed. Spot gaps in accountability before they become problems. - Own follow-ups relentlessly. Be the person who tracks every open item, owns the action register, and closes loops. Drive decisions and unblockers to resolution rather than letting them drift. - Create clarity from ambiguity. Take loosely defined goals and turn them into scoped, sequenced, resourced plans with clear owners and measurable milestones. - Manage risk and dependencies. Maintain a clear-eyed view of cross-team dependencies and risks; surface them early, drive mitigation, and keep leadership informed with honest, signal-rich updates. - Communicate up, down, and across. Translate between deeply technical teams and senior leadership. Run effective program reviews and write the kind of crisp status that lets busy people make fast decisions. REQUIREMENTS - 3+ years of technical program management experience, with a track record of delivering large, cross-team infrastructure or platform programs. - Demonstrated ownership of complex migrations or comparable multi-domain initiatives from inception through completion. - Strong execution discipline: you build the structures, cadences, and tracking that keep programs on the rails, and you hold the line on follow-through. - Comfort operating across multiple infrastructure domains. You don't need to be the deepest expert in any one, but you can engage credibly with engineers on compute, storage, networking, and data. - Proven ability to influence without authority, aligning teams and managers who don't report to you around shared plans and commitments. - Excellent written and verbal communication; you can make complex, technical programs legible to any audience. - A bias toward closure: you're uncomfortable with open loops and you drive things to done. NICE TO HAVE - Experience designing team structures or operating models alongside engineering leadership. - Experience with AI models, their use, and how they operate at the infrastructure level. - Background in or exposure to software engineering, SRE, or infrastructure operations. - Familiarity with the tooling that supports program execution at scale (e.g., issue tracking, planning, and reporting systems). WHAT SUCCESS LOOKS LIKE - In your first few months, you'll have taken ownership of one or more in-flight programs, established the operating rhythm they were missing, and built the trust that makes teams want you in the room. - Within a year, the programs you run are the ones leadership doesn't worry about, because the structure is clear, the risks are visible early, and the follow-ups always close. 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).

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 the Engineering Manager for Baseten's Cloud Platform team, you will directly manage a team of cloud platform engineers responsible for building the systems and processes that keep our infrastructure scalable, reliable, and efficient — from automated deployments and monitoring to performance optimization and incident response. You are a people-first leader with a strong cloud infrastructure background. You set a high bar for reliability and operational excellence, engage credibly in technical discussions and code reviews, and know how to build a culture of ownership and accountability. You'll spend most of your time close to the work: unblocking your team, shaping technical direction on day-to-day decisions, and developing your engineers. At Baseten, we work closely with our users to understand their struggles operationalizing ML — you'll keep your team connected to that mission and translate user learnings into better infrastructure.   RESPONSIBILITIES - Recruit, hire, and grow a high-performing team of cloud platform engineers; provide ongoing coaching, feedback, and career development through regular 1:1s. - Set clear performance expectations, hold a high bar, and create an environment where engineers do their best work. - Foster a culture of ownership, accountability, and continuous improvement. - Drive day-to-day technical decisions through design reviews, code reviews, and architectural discussions; translate the infrastructure roadmap into clear team priorities and milestones, and hold execution against them. - Establish standards and best practices for reliability, performance, and operational excellence; ensure the team owns projects end-to-end, from specification through production. - Exercise and encourage good judgment on tooling and architectural tradeoffs, with a bias against unnecessary complexity. - Partner with product and engineering teams to align infrastructure work with business priorities; represent your team's progress, capacity, and technical tradeoffs clearly to leadership. - Serve as the escalation point for major incidents; drive resolution with urgency, ensure the team learns systematically, and stay connected to users so those learnings feed back into infrastructure improvements.   REQUIREMENTS - Proven experience directly managing engineers in a cloud infrastructure, platform engineering, or SRE context (not managing managers). - Extensive hands-on experience with Kubernetes, with the ability to engage credibly in architectural discussions and code reviews. - Strong background building and maintaining scalable, production infrastructure. - Familiarity with infrastructure-as-code tools (e.g., Terraform, CloudFormation, Pulumi) and CI/CD tooling (e.g., GitHub Actions, GitLab CI, CircleCI, Jenkins). - Demonstrated ability to drive projects end-to-end — from specification to execution — and coach your team to do the same. - Strong written and verbal communication skills; able to influence across teams without direct authority. - Track record of recruiting and growing engineering talent. - Openness to learning about ML infrastructure; prior machine learning experience is not required.   NICE TO HAVE - Experience with OSS observability tooling (Prometheus, ELK stack, Grafana, OpenTelemetry). - Background in multi-cloud environments or GPU infrastructure. - Experience building and managing on-call rotations and incident response processes. 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).