Вакансии

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 are bringing our people systems in-house on Workday, and we are hiring our first dedicated Workday Analyst to make it excellent. You will join while the implementation is underway, ramp alongside our deployment partner, and own the tenant from go-live onward. This is a hands-on configuration role: you will build business processes, manage security, load data, and test releases yourself, and you will teach others on the People team to do the same as we grow. If you want to shape a Workday environment from its first day in production instead of inheriting years of someone else's decisions, this is that rare opening. RESPONSIBILITIES - Own day-to-day Workday configuration: business processes, security groups and roles, custom reports, calculated fields, and tenant settings - Build and run EIB loads for data changes, mass updates, and audits - Own the twice-yearly Workday release cycle: evaluate new features, regression-test, and roll out changes safely - Shadow the implementation build, then take over tenant ownership at go-live - Monitor integrations and triage issues with our IT team and vendors - Support payroll configuration in partnership with our Accounting team and payroll services provider - Field and resolve system requests from employees, managers, and the People team - Mentor teammates so Workday administration becomes a team capability, not a single point of failure REQUIREMENTS - 6+ years administering a live Workday tenant in-house (customer side, not consulting) - Deep Workday HCM core: business process configuration, security administration, and Report Writer - Fluent with EIBs and comfortable owning data loads end to end - Have shipped multiple Workday releases and know how to test them - A builder's temperament: you do the configuration yourself and like it that way - Clear written communication for documentation and change notes - Excitement about a pace that's faster than anywhere you've worked before - You'd rather improve on your old playbooks than reuse them as-is, and you're interested in AI tools that help you do it NICE TO HAVE - Workday Payroll configuration experience - Workday Benefits module configuration (plan and enrollment event setup) - Workday Absence Management configuration (time off and leave plans) - Workday Pro or similar certifications - Commutable to our San Francisco or New York office 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).

220 000 – 260 000 $

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 We are hiring at a rapid rate, and every one of our new hires deserves a great new hire experience from the moment they sign their offer letter through their entire onboarding journey. As our People Operations Coordinator, you'll own the tactical side of onboarding: collecting and tracking the completion of required documentation, greeting new hires, assisting in running sessions, and keeping the operations of onboarding on track as we grow. The role is heavily onboarding-focused today and will broaden across the employee lifecycle as our new people systems take over more of the routine work. Things change quickly here, and this role will too. This role is based in our San Francisco office. RESPONSIBILITIES - Own the full onboarding experience for every new hire, including: new hire communication from offer signature through Day 1; ensuring completion of onboarding tasks like background checks, Form I-9s, setting up HRIS profiles, etc; coordinating travel logistics; partnering with the Global Mobility Manager on immigration matters that may affect start dates - Support day one and San Francisco week one onboarding program, including coordinating with managers and buddies, room booking and coordination of start location - Partner with IT and Workplace so new hires have the right access, equipment, and desk waiting on day one - Manage the logistics behind our onboarding platform and manage the day-to-day vendor relationship - Support more moments in the employee lifecycle as the role evolves, from job changes to location moves and more - Bring ideas for making the day-to-day run smoother, from automating a task to fixing a clunky step - Handle sensitive employee information with discretion REQUIREMENTS - 2-4 years in a high-volume coordination or operations role - People function preferred - Extremely organized and detail-oriented, with a tactical, get it done approach, where tasks don't get dropped on your watch - Self-directed and comfortable with ambiguity - Extremely clear written communicator - Based in San Francisco and able to work in the office 3+ days per week NICE TO HAVE - Comfortable presenting to groups and facilitating engaging onboarding sessions for new hires as needed - Experience incorporating AI tools, such as Claude, into workflows, with a strong mindset toward automation and systems integration. - Experience working with recruiting, HRIS and onboarding platforms and related People systems. - Strong spreadsheet skills, including comfort working with formulas and organizing complex data. - Experience at a fast-growing startup 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; 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 are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on top of it, whether that is a kernel panic, a broadcast storm during boot, or getting our container runtime to run on new architectures and platforms. REQUIREMENTS: - 5+ years of experience writing high-quality production code - Experience operating fleets of physical hardware (bare metal provisioning, BMC/IPMI, PXE or network boot, firmware) or building the control planes that manage them (the more challenges you've worked through, the better) - Strong cloud skills - Strong knowledge of low-level operating system foundations (Linux kernel, drivers, networking, file systems, containers, etc.) - Effective at debugging across layers, from BGP flapping, Linux RPS, and vBIOS bugs to a Python control-plane service - Willingness to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVES: - Experience with GPUs and the NVIDIA software stack in production (drivers, health monitoring, XIDs, RDMA/NVLink) - Prior experience with Go KEY THINGS THE TEAM IS WORKING ON: - Automatic remediation of unhealthy machines (power cycling, reimaging, GPU recovery) to maximize uptime and minimize operator toil. - Automatic integration of new CPU, GPU, and storage servers into the fleet while managing hardware and network heterogeneity. - Network health monitoring and reliability across many datacenters, and standardization of bare metal network configuration. - Automatic hardware acceptance testing and benchmarking (CPU, disk, GPU, interconnect, network). - Custom network bootloader, machine image pipeline, and kernel and firmware management across the fleet.

Location: San Francisco; 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 are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collection over billions of objects. You'll work across the stack, from local disk and page cache to distributed blob storage and garbage collection and you'll help shape what storage becomes next as we push storage closer to workloads. REQUIREMENTS: - 5+ years of experience writing high-quality production code - Experience building high-performance distributed storage or caching systems at a large scale (the more challenges you've worked through, the better) - Strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - Strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - Willingness to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVES: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte-scale. - Prior experience with Rust KEY THINGS THE TEAM IS WORKING ON: - P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicating data across multiple blob storage providers - Automating garbage collection across hundreds of petabytes of data - Deploying colocated storage clusters to datacenters to accelerate high-throughput customer workloads

Location: United States Remote; Canada Remote ABOUT THE TEAM At Mural, we’re reimagining how teams think and create together. The Design and Research team brings clarity to complexity, shaping experiences that help people collaborate, ideate, and solve problems visually. We partner deeply with engineering, product, and research to invent the next generation of collaborative work combining craft, systems thinking, and bold exploration. YOUR MISSION As a Lead Product Designer focused on Growth, you’ll define how Mural earns user trust at the moments that matter most when someone first encounters the product's value, decides to go deeper, or chooses to stay. This is end to end growth journey ownership. It's about designing the logic of how Mural grows: the moments where clarity converts, where friction is a design failure, and where the line between growth and product quality either holds or breaks. You'll work across discovery, activation, and pricing surfaces, onboarding paths, upgrade flows, lifecycle touchpoints, and in-product nudges. Most importantly, you'll orchestrate how those surfaces work together and set the standard for how growth design is practiced at Mural. You'll succeed if you can bring full journey thinking, rigor and craft to a domain that often defaults to shortcuts and if you can help a cross-functional team understand what good growth design actually looks like. WHAT YOU'LL DO PLAYER RESPONSIBILITIES (INDIVIDUAL CONTRIBUTOR WORK): - Define high-quality, user-centered discovery, activation, and monetization experiences across problem to success flows, upgrade flows, pricing surfaces, and lifecycle touchpoints — setting patterns that scale across the platform. - Work from concept to production, delivering thoughtful UX, polished visual design, and vibe coded prototypes that help the organization understand direction, risk, and value. - Use behavioral data as a primary design input: interpret funnel metrics, experiment results, and user signals to inform design decisions, not just validate them. - Design and lead experiments across acquisition, activation, and expansion funnels — from hypothesis formation through read-out, in close partnership with product and data science. - Establish reusable growth patterns in Mural's design system that balance clarity, persuasion, and long-term user trust. - Partner with engineers to ensure accurate, high-quality implementation of flows and components. COACHING RESPONSIBILITIES (PRACTICE LEADERSHIP & MANAGEMENT): - Directly manage one to three designers on the growth surface: run regular 1:1s, set goals, give performance feedback, and support their career growth. - Balance IC output with people leadership — this is a hands-on management role, not a full-time management track. Expect the majority of your time to remain in design work. - Model how to hold craft and commercial intent simultaneously — showing peers what it looks like to design for conversion without compromising user trust. - Mentor designers working on growth-adjacent surfaces, developing their instincts around hierarchy, motivation, friction, and funnel thinking. - Contribute to how the team understands growth design as a discipline: a principled approach to earning user commitment. - Champion the relationship between growth quality and product quality, helping leadership understand when they align and when they're in tension. - Partner with research, data science, and product to elevate experimentation quality across the organization. HYBRID RESPONSIBILITIES (BOTH PLAYER & COACH): - Reframe problems at the funnel level helping teams understand where value is earned or lost and why. - Lead workshops or working sessions that bring clarity to pricing, packaging, onboarding, and upgrade moment opportunities. - Collaborate with product, research, and data science to define success metrics, shape experiment hypotheses, and interpret outcomes. - Advocate for user trust as a growth asset, not an obstacle to conversion — and model how design holds that line. DESIGN & RESEARCH TEAM CONTRIBUTION: - Share growth approaches for designing discovery, onboarding, and identity flows with peers through critique and collaboration. - Partner with research, data, and product teams to elevate experimentation quality and improve how Mural understands user value signals. - Contribute to a culture of design excellence, especially in areas where growth and monetization intersect with core product experiences. WHAT YOU’LL BRING - 8+ years of product design experience, ideally in SaaS, productivity tools, collaboration software, or product-led growth environments. - 2+ years of managing other designers - A track record of leading growth, monetization, or conversion-focused design work — not just contributing to it. - Deep fluency in funnel thinking: you understand acquisition, activation, retention, and expansion as a connected system, not isolated moments. - Strong data instincts: you can read behavioral data, interpret experiment results, and use both to sharpen design decisions. - Exceptional craft: visual clarity, spacing, motion, and interaction polish are second nature. - Systems thinking: you understand how decisions cascade across surfaces, journeys, and user relationships over time. - Experience mentoring or leading other designers, even informally — you know how to raise the quality of work around you. - Strong communication skills that help cross-functional partners make smart, user-centered decisions. - Comfort operating in spaces where patterns don’t yet exist and playbooks need to be written. ALSO GREAT IF YOU BRING - Experience with pricing architecture, packaging strategy, or monetization model design. - Deep experience mapping and designing activation journeys — the full arc from first action to genuine value realization. - Hands-on experience using AI-assisted tools and vibe coding to prototype growth flows, simulate behavioral nudges, and stress-test funnel logic in motion — treating code as a design material for rapid exploration. - Background in organic acquisition or activation funnels at scale. - Familiarity with AI-assisted experiences or contextual intelligence in growth flows. - Experience working with data science teams on experimentation frameworks or causal inference. - History of shaping 0→1 growth systems or redesigning broken acquisition or retention loops. WHY YOU’LL LOVE MURAL You’ll help shape how millions of people discover value in Mural, understand what the product can do for them, and make confident choices about their journey. You’ll design experiences that balance business goals with user trust, clarity, and delight. You’ll collaborate with thoughtful partners who care about evidence, craft, and outcomes. At Mural, we “drink our own champagne” and use our product daily to collaborate, ideate, and prototype together. This role is Canada Remote. Your design work will shape how millions of people around the world collaborate. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. EQUAL OPPORTUNITY  We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Компания "Урал Логистика" приглашает ML-инженера для участия в создании системы обработки документов и данных для грузовых железнодорожных перевозок. Задачи: — Строить конвейеры подготовки данных: сбор, очистку, нормализацию, дедупликацию и разметку — Формировать обучающие, валидационные и независимые оценочные выборки, контролировать утечки и пересечения — Создавать baseline для задач извлечения, классификации, определения сущностей и связей — Дообучать модели, готовить инструктивные наборы, обучать адаптеры и сравнивать результаты с базовыми моделями — Определять метрики, стратифицировать выборки и анализировать ошибки по типам документов, сценариям и полям — Работать с извлечением сущностей и связей для построения и обновления графового представления данных — Разворачивать локальный inference и оптимизировать его под доступную инфраструктуру — Работать с tensor parallelism, batching, длиной контекста, GPU-памятью и квантованием — Измерять задержку, пропускную способность, утилизацию и стоимость обработки документа — Версионировать данные, модели, конфигурации обучения и результаты экспериментов — Участвовать в интеграции моделей с прикладными AI-сервисами и production-конвейерами Требования: — Уровень middle+ и выше — Практический опыт построения ML-конвейеров, используемых в production — Уверенное владение Python, PyTorch и Hugging Face Transformers — Опыт fine-tuning языковых моделей, подготовки данных и работы с PEFT — Умение строить корректную оценку качества и контролировать утечки между обучающими и тестовыми данными — Опыт локального inference LLM и понимание устройства GPU-памяти — Знание компромиссов между качеством, скоростью, длиной контекста, batching и квантованием — Знание Linux, CUDA, SQL, Docker и Kubernetes — Способность довести модельное решение до устойчивой эксплуатации Условия: — Полная занятость — Возможность трудоустройства через российское юридическое лицо в штат или через согласованную аутстафф-модель — Основной формат — офис или гибрид — Для самостоятельных специалистов возможна распределённая работа из России — Итоговый грейд и масштаб ответственности определяются по результатам собеседования

Зарплата не указана

Задачи: — разработка, обучение и оптимизация ML/AI-моделей на PyTorch и/или TensorFlow — проектирование end-to-end ML-пайплайнов — работа с LLM, NLP, Computer Vision и Generative AI — подготовка моделей к production и масштабированию — интеграция моделей с backend — оптимизация inference и производительности — построение MLOps-процессов — работа с Docker и cloud-инфраструктурой — принятие архитектурных решений и техническое руководство AI-командой Требования: — от 4 лет коммерческого опыта в Machine Learning / AI Engineering — практический опыт разработки и внедрения ML-моделей в production — уверенный Python — PyTorch и/или TensorFlow — понимание Machine Learning и Deep Learning — знание ML-метрик и методов оптимизации моделей — Docker, Git — AWS или аналогичные cloud-платформы — практический опыт с MLflow, Kubeflow, AWS SageMaker или аналогичными MLOps-инструментами — свободный английский язык Условия: — full-time — офис в Ташкенте — официальное трудоустройство по ТК Узбекистана — вилка от $3,500

от 3 500 $

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 social media manager to own how Baseten shows up on social. Our audience is ML engineers, infrastructure teams, and technical founders, and most of them meet us first on X or LinkedIn, around a model launch, a benchmark, an open source release, or a customer result. This role decides what that first impression is. This is a senior individual contributor role. You set the strategy and you write the posts. Day to day you'll work with product marketing, comms, design, our engineers, and our founders. This role relies on technical credibility. You don't need an engineering background, but you do need to understand what we're claiming and why it matters. We post about latency, throughput, and GPU cost, and we hold ourselves to getting those details right. RESPONSIBILITIES - This role is the face of the Baseten brand on our social channels and builds our direct line of communication with the community across X, LinkedIn, YouTube, and the communities where our audience already spends time. - Track the conversation across AI and open source, and move quickly when we have something useful to add. - Set the social strategy: what we post where, how each account grows, and how we measure it, with a clear point of view on which channels deserve investment and which don't. - Translate technical work into posts worth sharing: model launches, benchmark results, open source projects, engineering deep dives, and customer outcomes. - Lead the social side of launches alongside product marketing, product, and engineering. - Produce content. Shoot and edit short-form video at events, in the office, and around launches, and brief a freelancer or design partner when that's faster. - Scale the voices of our team. Help engineers, GTM, and leadership post in a way that still sounds like them, and ghostwrite where it helps. - Report on follower growth, engagement, reach, and share of voice against goals, and change the plan when the numbers say to. - Manage the contractors and creators who extend our output beyond one person. REQUIREMENTS - 5+ years running social for a technical, developer-facing, or B2B technology brand, most of it as the person writing and shipping the posts. - A track record of growing an account. We'll ask you to walk us through posts you wrote and what made them land. - Technical fluency to write accurately about inference, GPUs, and model performance, and to ask our engineers the right follow-up questions. - Native fluency on X and LinkedIn, and comfort producing short-form video. - Experience being trusted with a brand account, including the judgment calls about what not to post. - Comfort in a fast launch cycle where the plan changes and the window to react is short. - A point of view on how AI companies show up online, with specifics on who does it well. 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 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: Modal considers high-quality documentation to be essential for developer experience, and we see docs becoming even more important as agents increasingly deploy and operate Modal Apps. We are looking for a content-minded engineer who will partner with our product teams to curate Modal’s technical documentation and maintain a high quality bar across multiple dimensions. RESPONSIBILITIES: - Thinking holistically about content architecture and how the docs should evolve as Modal introduces new products and features - Innovating on novel documentation formats and delivery channels to optimize agent productivity, in collaboration with our Agent DX research team - Developing content standards, style guides, and automated enforcement mechanisms to ensure consistent style and high quality - Building and maintaining automated pipelines that will enforce the correctness of code examples and prose descriptions - Collaborating with engineers across the company to author documentation that is clear, consistent, and correct REQUIREMENTS: - 3+ years of experience in an engineering, product, or developer relations role, ideally in the devtools or infrastructure space - Experience authoring and/or editing high-quality technical content for developers - Knowledge of agentic engineering workflows and best practices - Comfort with modern software development practices (version control, CI/CD, testing)

Location: San Francisco, CA • New York, NY Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Data Science team partners across product, engineering, design, marketing, sales, and operations to help Figma make better decisions with data. As a PhD Data Science Intern, you’ll bring rigorous research training to some of Figma’s most important and open-ended questions, from researching emerging product and user behaviors and Figma’s broader ecosystem to developing new measurement methodologies, applying causal inference or machine learning, and building analytical systems. You’ll own a data science project end-to-end: from framing the question and methodology to translating findings into insights that influence Figma’s products, strategy, or data science practices; with the potential to continue toward publication after the internship. This internship will be based out of our San Francisco or New York hub. What you’ll do at Figma: Partner with cross-functional teams to turn ambiguous product, platform, or business questions into well-defined data science problems Analyze user, product, or business data to uncover insights and recommend actions Design and evaluate experiments, metrics, statistical or machine learning models, and analytical frameworks Communicate assumptions, tradeoffs, limitations, and recommendations clearly to technical and non-technical partners Own a focused internship project end-to-end, from problem framing and technical execution through final recommendations, with potential to continue toward publication after the internship We’d love to hear from you if you have: Currently pursuing a PhD in Data Science, Statistics, Computer Science, Human-Computer Interaction (HCI), Economics, Operations Research, Physics, Applied Mathematics, or a related quantitative field; with demonstrated experience conducting independent research (e.g. thesis or equivalent research milestone) Demonstrated fluency in one or more research methodologies or technical areas, such as statistics, experimentation, machine learning, causal inference, econometrics, optimization, user research methods, or AI/LLMs Experience using a scripting language such as Python or R, as well as proficiency with SQL, for analysis, modeling, or work with complex or large-scale datasets through research, internships, or applied projects Ability to explain technical concepts clearly and connect analysis to decisions, recommendations, or product/business impact A curious, rigorous, and self-starting mindset, with the ability to thrive in ambiguous, fast-moving environments and translate research into real-world impact While it's not required, it's an added plus if you also have: Prior industry or applied research experience with experimental design, causal inference, forecasting, product measurement, user research, or applied machine learning to influence product, business, platform, or stakeholder decisions Publications or research relevant to applied data science Experience or interest in AI product measurement, LLM analytics/evaluation, recommendation systems, search, personalization, or evaluating AI-powered features At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure This internship role is based in either Figma’s San Francisco or New York hub offices, and has the hourly base pay rate stated below.  Figma also offers interns a housing stipend and travel reimbursement. Figma’s compensation and benefits are subject to change and may be modified in the future. Internship $68 — $68 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Задачи: - Развивать и усиливать команду аналитиков, выращивать будущих тимлидов - Быть ключевым партнером для Product, Growth, Marketing и бизнеса - Развивать культуру принятия решений через эксперименты, а не интуицию - Улучшать подходы к A/B-тестированию, causal inference и оценке бизнес-эффекта - Влиять на развитие продукта, персонализации и пользовательского опыта Требования: - Опыт управления командой аналитиков - Хорошее понимание продуктовой аналитики и A/B-тестирования - Опыт работы в e-commerce, marketplace или других digital-продуктах - Умение выстраивать отношения со стейкхолдерами и влиять на решения - Знания в персонализации, рекомендательных системах, ранжировании (будет плюсом) - Опыт в FoodTech, Retail, E-grocery или Marketplace (будет плюсом) - Опыт с causal inference и продвинутой экспериментальной аналитикой (будет плюсом)

Зарплата не указана

Задачи: — Проводить security review AI/LLM-решений: LLM-приложений, AI-агентов, RAG, векторных БД, интеграций с внешними API и облачными LLM; — Участвовать в threat modeling AI-решений: prompt injection, jailbreak, утечки данных, небезопасные tool calls, избыточные привилегии AI-агента, RAG/data poisoning; — Проверять наличие и корректность защитных механизмов: guardrails, фильтры персональных данных, ограничения длины prompt/response, rate limiting, валидация ответов, контроль вызовов tools; — Оценивать безопасность работы с данными: персональные данные, конфиденциальная информация, источники данных для RAG, embeddings, индексы векторных БД; — Проверять, что AI-агенты работают по принципу минимально необходимых привилегий и не выполняют чувствительные операции без ручного подтверждения; — Проверять изоляцию пользовательских сессий, контекстов и памяти AI-решений; — Участвовать в проверке безопасности локального запуска LLM в Kubernetes: контейнеры, RBAC, secrets, network policies, ingress, resource limits; — Формировать требования к логированию, аудиту и трассировке AI-решений: trace ID, логи prompt/response, вызовы модели, вызовы tools, действия AI-агента; — Разрабатывать тестовые сценарии для проверки AI-решений на prompt injection, утечки данных, обход ограничений и небезопасное поведение агента; — Помогать командам разработки и эксплуатации безопасно использовать локальные и облачные LLM. Требования: — Опыт в кибербезопасности от 2–3 лет в одной или нескольких областях: Application Security, DevSecOps, Cloud Security, Kubernetes Security, API Security, Product Security; — Понимание принципов security review, threat modeling и безопасной разработки; — Понимание web/API-безопасности: аутентификация, авторизация, OAuth2/OIDC, SAML, JWT, RBAC, service-to-service-взаимодействие; — Базовое понимание AI/LLM-стека: LLM, prompt, system prompt, context window, embeddings, RAG, vector database, AI-agent, agent memory, tools/function calling; — Понимание основных рисков LLM-приложений: prompt injection, indirect prompt injection, jailbreak, утечка чувствительных данных, раскрытие system prompt, небезопасная обработка ответа модели, excessive agency; — Понимание особенностей безопасности RAG и векторных БД: например, Milvus, Qdrant, Weaviate, pgvector, Chroma, Elasticsearch/OpenSearch vector search; — Понимание рисков работы с персональными и конфиденциальными данными при использовании локальных и облачных LLM; — Базовое понимание Kubernetes и контейнерной безопасности: secrets, service account, RBAC, network policy, resource limits; — Умение формулировать понятные и проверяемые требования безопасности для продуктовых команд. Что мы ищем в кандидатах: — Опыт security review AI/LLM, RAG, чат-ботов, AI-ассистентов или агентских решений; — Знакомство с OWASP Top 10 for LLM Applications, OWASP Agentic AI Threats, MITRE ATLAS, NIST AI RMF; — Понимание безопасности agent tools/function calling: allowlist tools, схемы входных параметров, контроль прав, human-in-the-loop; — Опыт работы с SIEM/security logging: проектирование событий безопасности, аудит действий, расследование инцидентов; — Понимание подходов к безопасному исполнению кода, сгенерированного моделью: sandbox, изоляция контейнеров, запрет доступа к secrets, ограничения сети и ресурсов; — Базовые навыки Python, работы с JSON/YAML, API-тестирования или автоматизации security checks. Будет плюсом: — Опыт с OpenAI/Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic или другими LLM-провайдерами; — Опыт с локальными open-source LLM и inference-сервисами; — Опыт настройки или проверки guardrails, фильтров персональных данных, DLP-подходов, content moderation; — Опыт участия в AI red teaming или разработке тестов на prompt injection и data leakage. Условия: — Формат: Гибридный (от 2-х дней в неделю, м. Технопарк); — Бесплатный доступ к телемедицине и очным приемам в частных клиниках (включая стоматологию и сессии с психологами); — Условия ипотечного кредитования от Сбербанка; — Индивидуальный план развития; — Английский язык с корпоративным преподавателем и скидки на курсы в Skyeng, компенсация обучения от ведущих платформ; — Официальное оформление, стабильные выплаты, оплата больничного и отпуска, современная техника; — Частичная компенсация спортивного абонемента, бесплатные занятия сквошем и футболом.

Location: SF or Remote (US/Canada) At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. ABOUT THE ROLE We're looking for a Senior/Staff Data Scientist to join our growing Data team and serve as a strategic analytics partner across Render. As we scale, we're tackling increasingly complex questions across our product, customers, and business, from how developers discover and adopt Render, to what drives engagement and retention, to how we prioritize investments and identify new opportunities for growth. You'll partner with leaders and teams across Product, Growth, Go-to-Market, Finance, and other functions, focusing on some combination of data analytics, analytics engineering, machine learning, and experimentation based on your strengths, interests, and Render's highest-priority needs. You'll turn ambiguous questions into rigorous analysis, define how we measure success, and translate complex data into decisions and action. As a Senior/Staff-level individual contributor, you'll also help set the standard for analytics at Render, shaping our measurement frameworks, analytical practices, and how teams across the company use data to make better decisions. WHAT YOU’LL DO - Serve as a strategic analytics partner. Work closely with leaders and cross-functional partners across Product, Engineering, Growth, Go-to-Market, Finance, and other teams to identify high-impact questions, frame decisions, and determine how success should be measured. - Define meaningful metrics and measurement frameworks. Develop the KPIs and frameworks teams use to understand performance across areas such as acquisition, activation, adoption, engagement, retention, conversion, expansion, and customer outcomes. - Turn data into strategy. Surface patterns across our users, customers, products, and business. Identify opportunities, diagnose friction, and help teams determine where to invest and what to prioritize. - Shape our approach to experimentation and evaluation. Design and analyze experiments where appropriate, develop guardrail metrics and other methods for evaluating initiatives, and help teams choose the right analytical approach for the decision at hand. - Build measurement into how we work. Partner with teams to define instrumentation and measurement plans early, ensuring new products, programs, and initiatives can be evaluated reliably after launch. - Build trusted analytical foundations. Build and maintain dbt models, semantic and context layers in partnership with Analytics Engineering, transforming behavioral and business data into reliable datasets that support decision-making across Render. - Raise the bar for analytics. Establish analytical best practices, improve how teams use data in decision-making, and mentor scientists and cross-functional partners on measurement, experimentation, and data literacy. - Help shape the future of analytics at Render. Explore how AI-assisted tools can make analytics faster and more accessible while maintaining a high bar for accuracy, context, and analytical judgment. WHAT WE’RE LOOKING FOR - 7+ years of analytics experience, with a track record of shaping strategy and influencing decisions across complex or ambiguous problem spaces. - Strong business and product judgment. You can take an ambiguous question, identify what really needs to be understood, and determine the right analytical approach to inform a decision. - Experience defining and using metrics across some combination of Product, Growth, Go-to-Market, Finance, or other business domains, for example acquisition, activation, adoption, engagement, retention, conversion, expansion, or revenue. - Strong SQL skills. Writing complex, efficient SQL and independently exploring large datasets is a core part of how you work. - Experience using experimentation, statistical analysis, or other rigorous evaluation methods to understand impact, along with judgment about when each approach is appropriate. - Experience with modern analytics tooling such as Metabase, Mixpanel, dbt, BigQuery, Segment, and Git. - A track record of influencing cross-functional teams and senior leaders without direct authority. You're comfortable challenging assumptions, creating clarity from ambiguity, and driving alignment around what the data says. - Excellent communication skills. You can turn complex analysis into a clear narrative, explain technical concepts to non-technical audiences, and build the relationships necessary to drive action. - Experience using AI-assisted coding or analytics tools such as Codex, Cursor, or Claude Code to accelerate analysis, data modeling, instrumentation, or visualization. NICE-TO-HAVES - Expertise in statistical methods beyond traditional A/B testing, such as causal inference, cohort and survival analysis, or time-series analysis. - Experience with developer-focused, product-led, sales-led, or usage-based businesses. - Knowledge of cloud infrastructure, PaaS, developer tooling, or other technically complex products. - Experience analyzing multi-product or multi-segment businesses and understanding behavior across interconnected customer journeys. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. We encourage all who are interested to apply. We can't wait to hear from you! Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Задачи: — Руководить командой Computer Vision Engineers — Проектировать архитектуру production AI-систем — Менторить инженеров и проводить code review — Декомпозировать задачи и контролировать качество реализации — Разрабатывать пайплайны обработки десятков и сотен RTSP-потоков — Оптимизировать инференс на GPU и CPU — Принимать ключевые технические решения — Участвовать в найме и развитии AI-команды Основной стек: Python, PyTorch, OpenCV, YOLO, RTSP, GStreamer, NVIDIA DeepStream, TensorRT, Triton Inference Server, ONNX, OpenVINO, CUDA, FastAPI/gRPC, Docker и Kubernetes. Что важно: ✅ Сильный коммерческий опыт в Computer Vision и Video Analytics ✅ Опыт технического лидерства или менторства ✅ Запуск production AI-систем ✅ Уверенное знание Python, PyTorch, OpenCV и YOLO ✅ Практический опыт с RTSP, GStreamer, DeepStream и TensorRT ✅ Оптимизация моделей через ONNX, TensorRT, OpenVINO, CUDA или Quantization ✅ Понимание высоконагруженной обработки видеопотоков ✅ Умение принимать и аргументировать архитектурные решения Будет плюсом: ➕ Triton Inference Server ➕ C++ и CUDA ➕ Kafka и потоковая обработка данных ➕ MLflow и MLOps ➕ ViT, DETR, Swin и Video Transformers ➕ VLM, RAG, LangGraph, vLLM и Function Calling ➕ Опыт найма и формирования AI-команд Предлагаем влияние на архитектуру и технологический стек, сильную инженерную команду и работу над высоконагруженной системой промышленного уровня.

700 000 – 1 700 000 ₸

Location: San Francisco; New York Workplace: Remote 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 ROLE: We're hiring the first Account Managers at Modal. You'll report to the Regional Director of Account Management and be a founding member of the team. This function does not exist yet. There is no playbook, no territory map, no established motion. You'll own a book of business from day one and build the motion at the same time — from fast-moving AI startups to large enterprise teams running critical infrastructure on Modal. This is a commercial role with a revenue target. You'll be measured on retention and expansion across your accounts. While you won't be delivering the technical recommendations and implementation, the work is technical by nature. Our customers are engineers running GPU workloads, inference, and batch jobs in production, and you need to hold your own in those conversations. The profile we're hiring is a technical account manager. You've worked at companies that are deeply technical and consumption in nature. You bring the commercial instincts to grow revenue from an existing base and enough technical depth to know which conversation actually matters. And you can credibly work with a CxO all the way down to a Developer. WHAT THE ROLE IS: - A founding seat. You're helping build the AM function with us, not joining one that already runs. The account plans, expansion motions, and customer cadence you and the rest of the founding team figure out are what we scale to every AM we hire after you. - A technical customer-facing role. You'll work directly with Developers and ML teams on what they're building and how Modal fits. You translate and triage the deeper technical work to FDEs and Product when it's needed. - A book of business. You’ll own a set of accounts and be responsible for the revenue that comes from them. Expect to be meeting with customers in your first few days because the best playbooks are built from real experiences. WHAT THE ROLE IS NOT: - A traditional post-sales role. You're measured on revenue, not health scores. - An on-call support function. You're not fixing bugs or triaging tickets. You're driving growth. - A technical delivery role. You're not implementing for the customer. You know where the technical work goes and you pull in the right people. - An inherited motion. Nothing is handed to you. If you identify gaps in process, tooling, or a playbook — you help build it. - A single-lane job. Our priorities go customer → company → team → me. We focus on delivering maximum impact vs. "this is my job". WHAT YOU'LL ACHIEVE: - Build Modal's account management function and iterate on it as we scale the business - Own and deliver on a revenue target across your book of accounts - Grow an account's first use case, expand into a second, and drive standardization across the Modal platform - Get fluent enough in Modal to hold your own with engineering teams on their workloads, and know when to pull in FDEs, Support, or Product - Work with Sales, Solutions Architects, FDEs, Support, and Product to grow accounts and feed customer signal back into the roadmap - Travel to customers as needed to support key accounts and drive expansion opportunities WHAT YOU'LL NEED TO BRING: - Customer-facing experience. You've owned a revenue target or supported a revenue target in a highly technical, consumption business. - Technical depth. You work autonomously with Developers through CxOs and understand the core parts of the developer tech stack. - AI builder. You're hands on building with AI tools — not just consuming workflows that were built for you. - Ownership. You run your book of business and projects like you're the CEO of it. You're highly organized bringing stability, predictability, and pace to your work. You take action vs. waiting for direction. - Learning velocity. You operate with the mindset of what I can do today vs. let me pick this up tomorrow. You move fast, take the learnings, and iterate on it. - Cross-functional partner. Low ego, easy to work with, and highly accountable. You ask for feedback, you act on it, and you'd rather be corrected early than right late. Internal teams love working with you. NICE-TO-HAVE: - Experience as a Technical Account Manager, Solutions Engineer, Solutions Consultant, or similar type role - Certification as an engineer (ex. Computer Science Degree, Professional Bootcamps) - Early GTM hire experience at a fast-growing startup - You've sat close to GPU spend, model training, or inference workloads

Location: Remote - United States 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: AI Gateway gives developers one place to connect applications and agents to hundreds of models with one API key. It handles provider routing and fallbacks, unifies billing and observability, and lets teams manage spend and security controls across production AI workloads. Designing this well is a systems problem. A developer should be able to choose the right model, make and verify a first request, diagnose a failed request, and configure routing, budgets, credentials, and security controls without losing sight of the application they are trying to build. The right interface might be in the dashboard, on the public model catalog, in the CLI, in an API response, or in code. You will be the Design Engineer for AI Gateway, owning product design and frontend implementation across those surfaces. You will work with customers, a Product Manager, and engineers to understand the problem, explore solutions, build the production experience, ship it, and learn from what happens after launch. AI Gateway is live, the model ecosystem changes every week, and the team can move from an observed problem to production quickly. This is a rare chance to use your product judgment, design craft, and code to shape a developer product and ship the experience yourself. You will be the design owner embedded with a Product Manager and a dedicated engineering team. You will also have the Product Design team around you for critique, collaboration, and support. AI Gateway will be your main product area, with room to pursue design-led improvements across Vercel. You will report to the Design Team. If you’re based within a pre-determined commuting distance of one of our offices (SF, NY, London, or Berlin), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote. For location-specific details, please connect with our recruiting team. What You Will Do: Own product design and frontend implementation for meaningful parts of the journey from discovering a model to making a first successful request and operating AI in production. Design and build production experiences across the website, dashboard, CLI, and APIs, choosing the right medium for each problem. Make models, providers, credentials, routing, budgets, logs, performance, privacy, and governance understandable, then create patterns that extend across new providers, modalities, and workloads. Talk directly with customers and use product data to understand problems, define success, make tradeoffs, and improve what ships. Own quality after launch, including visual and interaction craft, accessibility, performance, resilience, instrumentation, and edge cases. Use coding agents to explore and implement ideas quickly, while testing, debugging, and taking responsibility for what ships. About You: Your work shows what you personally identified, designed, built, shipped, and learned after launch. You build production-quality web applications with React and TypeScript and can contribute confidently in a large, existing codebase. You bring strong visual and interaction craft and have made technical or data-rich products understandable without removing the control advanced users need. You can move between graphical interfaces, CLI workflows, API behavior, and implementation details, treating accessibility, performance, failure recovery, and instrumentation as part of the design. You use customer research and product data to make decisions, communicate your reasoning clearly, challenge ideas constructively, and change direction when the evidence changes. You use coding agents in your daily work, but you can explain, test, debug, and take responsibility for the code they help produce. There is no required path into this role. You may come from product design, frontend engineering, creative development, or a career that does not fit a standard title. We care about the quality of what you have shipped and the judgment behind it. Bonus If You: Have experience with developer tools, infrastructure products, model marketplaces, or observability experiences. Have worked with AI models, providers, inference platforms, guardrails, or AI application tooling. Have experience with APIs, command-line tools, structured product content, or agent-facing interfaces. Have built an application or agent with Vercel’s AI SDK or AI Gateway. See the work: AI Gateway AI Gateway documentation Browse AI models AI model leaderboards Design Engineering at Vercel 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 $208,000 - $312,000. 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: 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. About Talent at Modal Modal is growing fast, and the programs that bring people in and set them up to succeed are still being built. You'll join the Talent team as one of its first hires focused purely on programs; working closely with recruiting and leadership to build the events, internship, and campus presence that shape how the best people discover and experience Modal for the first time. The Role As Talent Programs Manager, you will own Modal's talent events, our intern program, and our presence at career fairs, end-to-end. This is a build-from-the-ground-up role for someone who wants full ownership rather than an existing playbook to execute. You'll work directly with recruiters, hiring managers, and marketing to make sure every program ladders up to real hiring outcomes, and you'll be the person who makes candidates' and interns' first experience of Modal a great one. What You'll Do: - Own Modal's talent events strategy; meetups, recruiting mixers, tech talks, and community events, from concept through post-event follow-up - Design and run the intern program end to end: recruiting timeline, project scoping with hiring managers, mentorship matching, and conversion - Represent Modal at career fairs and campus events, and recruit and prep employee brand ambassadors to join you - Build and maintain relationships with university programs, bootcamps, and community organizations that feed our pipeline - Manage program budgets and vendor relationships; venues, swag, catering, event platforms - Track and report on program metrics: event pipeline conversion, intern conversion rate, cost per hire from programs - Move quickly without sacrificing the candidate or intern experience Requirements: - 3+ years running recruiting/talent programs, events, or university relations, with a track record of owning a program end-to-end including budget and vendors - High influence, low ego: you build relationships easily across recruiting, hiring managers, and marketing, and share credit freely - Strong project management skills; comfortable juggling multiple concurrent events and timelines without dropping details - Excellent written and verbal communication; comfortable representing Modal externally - Someone who takes ownership seriously: you drive programs to completion and build structures that let them scale - Based in or willing to relocate to NYC, in-office

Задачи: — Разработка сервисов ИИ платформы для создания функциональных агентов и ИИ ассистентов. — Подготовка бэк части для функциональных агентов, включая среду разработки агентов: тестирование фреймворков, opensource агенты. — Разработка сервиса управления реестром и скиллами агентов. — Создание отдельного единого сервиса для всех баз знаний, интеграция крупных корпоративных источников. Требования: — Понимание архитектуры, возможностей и ограничений современных языковых моделей. — Опыт работы с embeddings, vector search, RAG, structured output и tool calling. — Понимание принципов проектирования AI-агентов: управление состоянием и контекстом, выбор инструментов, контроль уровня автономности и human-in-the-loop. — Опыт построения evals для LLM-систем, оценки качества ответов, контроля галлюцинаций и мониторинга поведения системы. — Понимание рисков prompt injection, некорректного tool calling, утечки данных и чрезмерных прав доступа агента. — Опыт работы с API языковых моделей, Hugging Face и одним из orchestration-фреймворков. — Умение оценивать стоимость, latency и масштабируемость LLM-решений. — Опыт работы в e-commerce, retail или других продуктовых highload-системах. — Опыт работы с Airflow, MLflow, Kafka, Redis, Kubernetes, Prometheus и Grafana. — Опыт эксплуатации GPU-инфраструктуры и оптимизации inference. — Опыт fine-tuning или адаптации LLM, включая LoRA / PEFT. — Опыт проектирования agentic workflows или multi-agent-систем. — Понимание принципов информационной безопасности, privacy и работы с персональными данными. Условия: — full-time

174 000 – 215 000 ₽