Вакансии

Задачи: — построение uplift-моделей по сегментам для разных групп — разработка uplift-моделей для различных номиналов промоакций с последующей оптимизацией — прогноз RFM — участие в проведении A/B тестов, расчет финансовых эффектов от внедрения моделей

Сопровождение ML-решений (мониторинг сервисов и моделей, отслеживание дрейфа данных, работа над развитием); Оценка влияния на бизнес предложенных решений;

Разработка и обучение ML/DL-моделей для задач NLP и Computer Vision. Возможен также classic ML.

Разработка и обучение ML/DL-моделей для задач NLP и Computer Vision. Возможен также classic ML;

-Разрабатывать и выводить в промышленную эксплуатацию решения на базе ИИ, в том числе AI-агентов на базе LLM. -Проектировать архитектуру AI-агентов и подходы к их построению.

Location: Berlin Office; Bosnia; Romania; Norway; Estonia; Latvia; Slovenia; Italy; Netherlands; Hungary; Portugal; France; Poland; Serbia; Germany; Austria; Finland; Albania; Lithuania; Slovakia; Ireland; Bulgaria; Denmark; Belgium; Czech Republic; United Kingdom; Croatia; Spain; Greece Workplace: Remote The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we’ve grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world’s Top 40 most popular projects - Backed by top investors, from Sequoia’s first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register http://app.n8n.cloud/register. We’re in a defining moment of an incredible journey. Come and build with us. Your main goal will be to make it simple and reliable for customers to buy, pay for, and grow their use of n8n. You'll own the foundations of how n8n's commercial system works: licensing and entitlements, customer accounts, and the metering and billing platform for both Cloud and Enterprise. Today these live across several teams and two billing stacks; you'll bring them into one stable home that the rest of the company builds on. This is a foundations role. You build the system that pricing and packaging decisions run on, rather than running price experiments yourself. To do so, here are your core responsibilities: OWN THE LICENSING & BILLING STRATEGY & ROADMAP - Define and communicate the product strategy and roadmap for Licensing & Billing in partnership with Engineering, Product leadership, Finance, and go-to-market. - Prioritize foundational investments based on revenue integrity, enterprise needs, data correctness, and engineering effort, and make trade-offs explicit. - Lead discovery with enterprise customers, Sales, Customer Success, Finance, and RevOps to understand how n8n is bought, renewed, and grown today, and where that breaks. LICENSING, ENTITLEMENTS & ACCOUNTS - Own the license server and entitlement model: issuance, renewal, and validation across Cloud, self-hosted, air-gapped, and OEM deployments, with one source of truth for which plan or deal grants which features. - Introduce "account" as a first-class product primitive (accounts, purchases, license keys, activations) and expose it as the API contract our customer-facing console and multi-instance management are built on. - Productize the deal-to-entitlement flow so a closed deal in Salesforce creates or updates entitlements without manual steps. METERING & BILLING PLATFORM - Own usage metering and billing for Cloud and Enterprise, including subscription billing: what counts as a billable execution, quota consumption, and overage charging. - Lead the migration off Paddle Classic and unify Cloud and Enterprise billing into one platform. - Build the mechanics for usage-based enterprise billing and reliable overage charging. CROSS-ORG ALIGNMENT - Make the architecture and mechanism decisions (entitlement model, billing platform, enterprise invoicing path) and align closely with Finance and go-to-market on each of them. Every decision here touches money; you bring people along rather than inform them afterwards. - Hold clear boundaries with adjacent teams: the customer console, execution limits, and access control live elsewhere; you own the data and mechanics they rely on. - Establish clear success measures and keep the squad accountable for outcomes, not only delivery. REQUIREMENTS Must-haves - Billing or licensing product experience: You have 6+ years in Product, with a substantial part spent owning a billing, licensing, entitlement, or quote-to-cash system at a B2B SaaS company. - Shipped through Finance and RevOps: You've driven a cross-functional systems change where Finance, Sales Ops, and Engineering all had a say, and you got it live. - Systems and data-model depth: You can design or critique an entity model, reason about reconciliation and idempotency in a sync, read an API contract, and explain why two systems reading the same events end up with different numbers. - Attention to detail: You know that if the billing data is wrong, everything built on it inherits the error, and you sequence work accordingly. - Prioritization under ambiguity: You make trade-offs explicit and connect foundational or data-quality work to commercial outcomes. - Ownership and autonomy: You grab problems without being asked, fix what you see broken, and drive outcomes without waiting for direction. - Exceptional communication: You're equally at home with engineers, the Finance team, and Sales, and you can make billing trade-offs legible to all of them. - Enterprise reality: You understand what self-hosted, air-gapped, and OEM deployments mean for licensing and metering. Nice-to-haves - Usage-based billing: You've owned usage-based or hybrid (subscription plus usage) billing. - Vendor billing stacks: You've worked hands-on with Paddle, Stripe, Chargebee, Zuora or similar, and know where they break at enterprise contract volume. - Migration experience: You've run a billing-provider migration. - Hands-on ability: You can read code, query data, or prototype, even if you're not shipping it. - CRM integration: You've worked on Salesforce or CRM-to-billing integrations. - Domain familiarity: You know workflow automation, agent orchestration, or open-source / developer-community products. - Writing culture: You default to writing things down to create clarity and alignment. Why join us? At n8n, you'll be in the middle of the AI revolution. The shift from deterministic automation to agent autonomy is a genuinely open design space, and n8n has a credible claim to owning it. Every plan we sell, every enterprise contract, and every agent run that gets metered and billed runs on the foundation you own: licensing, entitlements, accounts, and the billing platform across Cloud and Enterprise. Your work directly shapes how n8n makes money and how easily customers can buy, grow, and trust what they pay for, from self-serve Cloud to air-gapped and OEM deployments. You'll join one of Europe's fastest growing startups at the sweet spot: small enough to have real impact and be empowered, big enough that your work already reaches massive scale and serious enterprise customers. You'll work with experienced engineers, Finance, and go-to-market on problems where the details are the product, in an AI-native, empowered culture of humble, kind, yet driven and direct people, where you're hired to think, not just to execute. And with our fair-code model, a passionate open-source community gives you a direct feedback loop on everything you ship. Sound like a challenge you're excited to take on? Apply now, and help us build the commercial foundation of the future of reliable AI automation. n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. We can sponsor visas to Germany; for any other country, you need to have existing right to work. Our company language is English. You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n https://www.notion.so/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35?pvs=21 (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35). Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. BENEFITS - Competitive compensation 💸 – We offer fair and attractive pay. - Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity. - Work/life balance 🏖️ – We work hard but ensure you have time to recharge: - Europe: 30 days of vacation, plus public holidays wherever you are. - US: 20 vacation days, 8 sick days, plus public holidays wherever you are. - Health & wellness 🩺 – - Europe: We provide benefits according to local country norms.* - US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage. - Future planning 💰 – - Europe: We provide pension contributions according to local country norms.* - US: 401(k) retirement plan with a 4% employer match. - Financial security 🛡️ – - Europe: We provide benefits according to local country norms.* - US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones. - Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills. - A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it! - Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description. - Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about. - Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang. *Country and/or State specific details provided in your employment agreement.

Location: Hybrid - San Francisco, New York City About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role We are looking for a Machine Learning Engineer on our Trust & Safety Engineering team to build and operate the production systems that detect and stop abuse on the platform at internet scale. This is an engineering-first role, roughly 80% writing and shipping production code (services, pipelines, and infrastructure) and 20% modeling, taking detection and classification approaches from prototype to hardened systems. This is a hybrid role based in San Francisco or New York City, with three days a week in the office. What you’ll do Design, build, and operate production systems that detect and disrupt abusive behavior across the platform, with an emphasis on reliability, scalability, and observability Build and maintain machine learning (ML) infrastructure, including training pipelines, feature pipelines, serving infrastructure, and evaluation frameworks Ship large language model (LLM) and classical ML approaches for abuse detection and classification, turning prototypes into maintainable code Own systems end to end, from integrating a model into the platform through deployment, monitoring, and iteration Work with security, product, and infrastructure teams to turn abuse patterns and detection logic into production systems What you need 5+ years of software engineering experience building and operating production systems at scale Wrote production code in Python, plus JavaScript/TypeScript or Go Built and maintained ML infrastructure, such as training and serving pipelines, feature stores, or evaluation tooling Integrated LLMs into production systems, including prompt engineering and evaluation Bonus if you Built an open source ML tool Worked in the trust and safety, fraud, or abuse prevention domain 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 $208,000.00 - $312,000.00. 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.

What you will be doing Take high-uncertainty questions from product teams (Old Players, New Players, Quality of Life, Platform) from a vague question to a decision the team acts on. Design and analyze experiments in non-standard setups: delayed treatment for veteran players, kingdom-level (cluster) tests, small samples, heavy-tailed revenue.

What you will do Build new strategic partnerships with travel companies, agency networks, airlines, OTAs, travel platforms, loyalty programs, fintech companies, travel-tech players, and other distribution channels. Build a specific partnership hypothesis for each account rather than sending a generic company presentation.

Creating new and improving existing AI solutions Involvement in the whole process of data-driven development from analyzing product requirements to launching the feature or system to production (with the help of MLOps specialists) and improving it based on results of monitoring and feedback.

2D Artist. to help shape the visual world of a mobile poker game set in a.

разработка классических LLM агентов. разработка tools для агентов, а также skills-инструкций для LLM.

Location: Canada (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. This is a remote opportunity, and we would be interested in applicants located in the US or Canada. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Senior Software (Database) Engineer to help build the underlying storage system for our general purpose data platform. The database layer has both OLAP and OTLP capabilities to support classic analytics queries while also serving up freshly stored data. It embraces the separation of compute and storage and is designed to run on multiple cloud providers. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Take ownership over and build one or multiple parts of the database: Design, implement, test, and operate ingestion, query planning, distributed query execution, data formats, storage formats. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant database service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and database interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve data quickly. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument database services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the database solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with distributed systems, catalogs and table formats, query engines. Mastery of a programming language like golang, C++, or Rust Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building distributed query engines. Experience building data warehouses and/or data lakes. Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In Canada, the Base compensation range for this role is $ 164,490 - $197,389. 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 .

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. This is a remote opportunity, and we would be interested in applicants located in the US or Canada. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Senior Software (Database) Engineer to help build the underlying storage system for our general purpose data platform. The database layer has both OLAP and OTLP capabilities to support classic analytics queries while also serving up freshly stored data. It embraces the separation of compute and storage and is designed to run on multiple cloud providers. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Take ownership over and build one or multiple parts of the database: Design, implement, test, and operate ingestion, query planning, distributed query execution, data formats, storage formats. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant database service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and database interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve data quickly. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument database services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the database solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with distributed systems, catalogs and table formats, query engines. Mastery of a programming language like golang, C++, or Rust Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building distributed query engines. Experience building data warehouses and/or data lakes. Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In the US, the Base compensation range for this role is $ 154,445 - $185,334. 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 .

Сопровождение ML-решений (мониторинг сервисов и моделей, отслеживание дрейфа данных, работа над развитием); Оценка влияния на бизнес предложенных решений;

Требования: 1) Коммерческий опыт работы от 3-х лет. 2) Опыт реализации и вывода в промышленную эксплуатацию решений на базе ИИ (обязательно в том числе AI агентов на базе LLM) в роли Data Scientist/AI Engineer. 3) Знание основ Classic Machine Learning, хорошее знание Deep Learning (NLP). 4) Глубокое понимание архитектуры Transformer. 5) Глубокое понимание подходов и методов проектирования AI-агентов. 6) Практический опыт fine-tuning языковых моделей (GPT-like, BERT-like и др.). 7) Работа со стеком Python - Torch, Transformers. 8) Опыт разработки интеграций с ИТ-системами. 9) Опыт промышленной работы с k8s. Обязанности: - Артефакты тестирования гипотез/экспериментов: описание подхода/модели, соответствующие значения метрик (выбранных для данного решения), тестовый сет/бенчмарк. - Артефакты продукта в целом: описание проекта, архитектура (утвержденная и согласованная с архитекторами и информационной безопасностью (ИБ)), согласование от ИБ что решение может быть использовано в продакшн, код продукта и документация к нему, инструкция по разворачиванию решения в контуре компании. - Все вышеперечисленные артефакты размещены в контуре заказчика (Gitlab, Confluence).

Дивизион "Моделирование и исследование данных" отвечает за компетенцию Data Science в Блоке Сеть Продаж. Мы разрабатываем и внедряем end-to-end решения на основе AI в бизнес-процессы Сети Продаж Банка. Ищем человека, вместе с которым мы будем строить топовые AI решения, на основе архитектуры Claw-like & Ouroboros, которые будут в действительности приводить к Disrupt в реальных процессах. Задачи: • разрабатывать с нуля AI-агентов и микросервисы для AI-продуктов • исследовать и внедрять новейшие технологические решения в ИИ - Claw-like & Ouroboros • разрабатывать и дообучать модели машинного обучения (Classic ML, Deep Learning) • разрабатывать алгоритмы взаимодействия ML-моделей и сервисных модулей • принимать участие в разработке архитектуры и дизайна агентов и AI-сервисов • проектировать и разрабатывать backend-части AI-сервиса • принимать участие в оптимизации скорости работы AI-агентов и ML-моделей. Мы ожидаем: • законченное высшее образование • компетенции: Python, Classic ML, Deep Learning, LLM/Agents, MLOps • понимание принципов разработки, внедрения и сопровождения AI-решений • уметь писать хороший и понятный production-ready код на Python, хорошее знание алгоритмов, структур данных • опыт работы с реляционными и нереляционными базами данных • навыки работы с генеративными AI-моделями, опыт создания AI-агентов и использование их в работе будет преимуществом • опыт использования GigaChat, Kandinsky и аналогов в продуктах • инструментальное владение Ai для анализа, генерации и автоматизации • опыт построения отказоустойчивых высоконагруженных распределенных ML систем. Мы готовы предлагать: • график 5/2, офис на м. Кутузовская; • режим работы на выбор - офис или гибрид • достойный уровень вознаграждения (оклад + годовая премия) • возможность стать частью команды, реализующей программы цифровой трансформации банка - на основе передового опыта и инновационных идей • широкие возможности для профессионального развития: корпоративный университет и множество онлайн-программ обучения. Корпоративное обучение за счет компании • бесплатная подписка СберПрайм+, многочисленные скидки и бонусы от партнеров: СберМаркет, МегаМаркет, Самокат, Еаптека и др.

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 Baseten's GTM org is in hyper growth. As it grows and matures, the needs of the GTM stack get more sophisticated with scale — and this team exists to stay ahead of those needs. This role owns a core set of the platforms the field runs on. You'll administer, configure, and continuously improve them, build AI and automation on top of the CRM to keep it clean and current, and run the adoption programs that make sure the field actually uses what we put in front of them. We're an AI-native company scaling fast, and we want to add sophistication without adding drag — you'll be the person deciding how much system is enough. This isn't a classic Salesforce admin role. You know the ecosystem, but you come at it as a builder and an orchestrator, not a ticket-taker. Central RevOps is the systems and operations center of excellence for Baseten's GTM org. The stack includes Salesforce, Pylon, Outreach, Sales Navigator, Clay, and a growing set of AI-native GTM tools. The field is scaling fast, and the systems need to mature with it without slowing anyone down. You'll co-own Salesforce with our other GTM Systems Manager and work alongside a GTM Engineering team who builds internal AI products for GTM productivity — plus partner closely with sales leadership and the field. RESPONSIBILITIES - Own adminship, configuration, and enablement for Pylon, Gong, Sales Navigator, Outreach, and Prospect. These platforms are yours end-to-end — configured well, enabled with the field, and continuously improved as needs grow. - Run adoption, license forecasting, and vendor management for each of those systems. Own the adoption programs that get the field using them, forecast license needs ahead of growth, and manage the vendor relationships and renewals. - Co-own Salesforce. Partner with our other GTM Systems Manager to keep the CRM configured for how sales actually runs, and act as backup for Deal Operations processes. - Build AI and automation on top of the CRM. Stand up agents and automations that update and maintain the CRM — keeping data clean, current, and trustworthy without adding manual work. - Drive adoption, not just deployment. Document what you build, enable the field, and measure success by whether people actually use it. - Right-size the process. Add just enough structure to scale the company without slowing the field down. Have a point of view on where process helps and where it just gets in the way. REQUIREMENTS - 4+ years in GTM systems, RevOps, or sales/business systems — owning platforms and process end-to-end - Experience building AI and automation on top of a CRM — you've built agents or automations that update and maintain CRM data, not just configured fields - Hands-on adminship and configuration experience across a multi-tool GTM stack (support ops, engagement, prospecting, and enrichment tools) - Working knowledge of the Salesforce ecosystem and data model — enough to co-own the CRM — without wanting to be a career admin - A real appetite for enablement — you care whether the field uses what you build, and you'll run the adoption programs to make sure it does - Experience owning vendor relationships, renewals, and license planning - Judgment on process — you can tell structure that helps the field from structure that slows it down, and you right-size accordingly - Experience in high-growth B2B technology companies, ideally scaling systems as the field grows fast NICE TO HAVE - Fluency with AI and automation tooling (Claude, Clay, n8n, or similar) as a builder, not just a user - Familiarity with a data warehouse and BI environment (Sigma, Hex, BigQuery, Snowflake) on the data layer - Hands-on experience with Pylon - Exposure to Deal Operations, CPQ, or quote-to-cash processes as a backup or contributor - You've inherited a sprawling, redundant stack and made it more intentional without breaking what works 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).