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Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the industry's largest AI fleets — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around Capacity. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Directly influence decisions around a significant area of company investment. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at very large scale. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Paris; London Workplace: OnSite ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE   As a Solution Operations, you will serve as a strategic business partner to our Solution team. This team, composed of AI Deployment Strategists, Infrastructure Solution Architects, and Applied AI Engineers, designs, deploys, and optimizes AI solutions that directly solve our enterprise customers’ most complex challenges.   You will drive the end-to-end staffing strategy, ensuring alignment between business priorities, operational constraints, and talent deployment. Your mission is to optimize staffing efficiency, reduce time-to-staff, and build scalable processes that enable Mistral to deliver exceptional value to our customers.   It’s a high-impact, hands-on position at the intersection of strategy, operations, and execution. You will work closely with Solutions leadership to develop data-driven staffing plans, align capacity with demand, and implement frameworks that match skills to customer needs. Your work will directly accelerate Mistral’s ability to scale its technical pre-sales and post-sales motions while maintaining operational excellence.   WHAT YOU WILL DO   Worldwide Strategic Staffing & Capacity Planning - across all geographies • Develop and execute a forward-looking staffing strategy aligned with business forecasts and needs, including resource allocation, staffing ratios across regions, and technical deployment metrics. • Build and maintain a prioritization framework for recruitment (role type, geography) to ensure the Solutions team is staffed for high-impact customer engagements. • Accelerate time-to-value by minimizing time-to-staff through efficient matching systems between skills and customer requirements. • Act as a strategy partner to the Director of Solutions, providing insights on organizational design, role evolution, and scaling plans.   Data-Driven Staffing Optimization • Identify and operationalize key metrics to measure staffing efficiency, team utilization, and impact on customer success and revenue. • Create and maintain reporting mechanisms to track staffing KPIs, including time-to-staff, skill gaps, and deployment success rates. • Synthesize and implement actionable recommendations to improve staffing processes and cross-functional alignment.   Scalable Staffing Systems & Automation • Design and implement scalable processes, automations, and tools to streamline talent deployment and reduce operational friction.  • Optimize the Mistraler lifecycle (onboarding to project allocation) by ensuring seamless transitions and maximizing team productivity.  • Identify and eliminate bottlenecks in staffing workflows, leveraging automation to enhance agility and responsiveness to customer needs.   Cross-Functional Collaboration • Partner with Sales, Product, Revenue Operations, Talent Acquisition and HR to align staffing capabilities with customer demands and business priorities. • Support the development of the Solution team offerings and technical engagement models that maximize customer success. • Collaborate with Product teams to ensure Solutions team feedback is integrated into the product roadmap. Prepare materials for executive reviews, highlighting project successes, challenges, and strategic recommendations.     WHAT WE'RE LOOKING FOR   • 3+ years of experience in strategic operations, staffing, chief of staff or resource management within technical sales, solutions engineering, or professional services environments. • Proven track record in optimizing processes, impacting business KPIs, and aligning resources with business priorities. • Experience in staffing, resource management, or talent deployment is a strong plus. • Strong analytical skills, with experience in Salesforce, data warehouses, and BI tools (e.g., Looker, Hex, BigQuery). • Exceptional negotiation and diplomacy skills: ability to navigate complex stakeholder dynamics and align competing priorities. • Hands-on, execution-focused mindset with a bias for action in ambiguous, fast-changing environments. • Technical acumen: understanding of AI implementation, use cases, and scaling challenges is a strong plus. • Bachelor’s degree required; MBA or advanced degree preferred. • Fluency in English (native level); additional European languages are a plus. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Cyprus - Remote Wrike is the most powerful work management platform. Built for teams and organizations looking to collaborate, create, and exceed every day, Wrike brings everyone and all work into a single place to remove complexity, increase productivity, and free people up to focus on their most purposeful work. Wrike is our people, not a place. As a distributed team, we own our growth, stay globally connected, and rely on the product we build to deliver impactful work alongside brilliant minds. You'll have real ownership over meaningful work, a global team that has your back, and the flexibility to do your best work your way. If that sounds like you, we'd love to hear from you. Our vision: A world where everyone is free to focus on their most purposeful work, together. About the Role: You'll help build the very AI-powered platform you use every day, with real autonomy over the features you ship. As the leading collaborative work management platform, Wrike generates an enormous amount of rich, interconnected data, including work item content, relationships between entities, complex business processes, user interactions, and direct user input. The mission of the DS/ML department is to transform this data into intelligent, AI-powered capabilities that help users gain deeper insights, automate routine work, enhance productivity, and create a more seamless work experience. As a Data Scientist in the Work Intelligence Unit, you will play a key role in product development through the application of state-of-the-art AI and machine learning technologies with a particular focus on leveraging Large Language Models and other emerging technologies. You will work on both user-facing AI features and foundational intelligence platform that power intelligent experiences across the product. Your Impact: 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 Communicating with fellow data scientists, product owners, and developers Applying best software engineering practices to build a reliable codebase Performing code reviews Working in agile environment and presenting the results of your work on regular sprint reviews Your Qualifications: 4+ years of experience in AI,  Data Science, and Machine learning Experience in LLMs, LLM-based APIs, prompting techniques, metric-driven development of prompt-based features, agentic systems, and other related topics Experience in building complex multipart and multistep LLM-based and ML systems Proficiency in Python (including pure Python, and not only jupyter notebooks) Experience in using reproducible research techniques Experience in developing AI solutions for production usage Full professional proficiency in English Standout Qualities: Experience in AI and ML solutions related to one of the areas: social networks, recommendation systems, ranking, entity matching, process mining, system personalization, risk estimation Confident statistical and machine learning skills Experience in creating core AI systems that are foundational to the product and are used in many parts of it Experience in classical software development and architecture Interpersonal skills: Excellent interpersonal, written, and verbal communication skills required with the ability to work within all levels of an organization. You are proactively pushing yourself to develop your skills and knowledge Decision making and argumentation skills Open to feedback and ready to react on it Ability to work autonomously on a project level Our Work Style: Code: Python, Jupyter, mypy, uv, black, flake8 Data: pandas, SQL, BigQuery GenAI & LLMs: Langchain, Azure OpenAI, Gemini, Vertex AI, Braintrust LLM Platform: Versioned Prompt Registry(jinja2), Declarative LLM Feature Configs (multi-step workflows, model routing) ML: scikit-learn, lightgbm, pytorch Cloud: GCP, Dagster, MLFlow Coding Agents: Claude Code, Codex, Cursor Team Dynamics: As part of Wrike’s AI center of excellence — you will help scale AI feature development across teams by collaborating closely with product, engineering, design, research, and other departments across the organization. You will explore new AI-driven opportunities, validate hypotheses through experimentation, and drive innovations from research prototypes to production-ready capabilities that deliver tangible value to millions of users. Benefits & Perks: 25 working days of paid vacation Sick Leave Compensation (5 Uncertified + 10 Certified Days) Parental Leave: Fully Paid Maternity / 4 Weeks Paid Paternity 2 Volunteer Days Medical Insurance (Employees + Dependents) Life Insurance (Employees) Provident Fund Hybrid Working Model School Allowance (Up to €600/month for school aged kids) Simcard w/ Unlimited Internet Access for active employees Office Lunch Allowance (via Wolt) on Wednesdays / Thursdays Work Permit, Blue Card & Naturalization Support What’s Next? Introduction Call with a Recruiter Technical interview Cultural interview Your recruitment buddy will be Alexandra Vorobyova , Lead Recruiter. #LI-AV1 Who Is Wrike and Our Culture We’re a team of innovators and creators who solve the complex work problems of today and tomorrow. Hybrid work mode Wrike is our people, not a place. With 1,000+ employees collaborating across nearly every time zone, we support talent through 10 global hubs — Australia, Costa Rica, Cyprus, Czechia, Estonia, France, India, Ireland, Japan, and the United States — offering flexible ways of working that include remote work, hybrid environments, and co-working spaces across many locations. While flexibility looks different across teams and regions, employees located near certain hubs — particularly in Prague (CZ), Nicosia (CY), Bangalore (IN), and Rennes (FR) — are generally expected to collaborate in person around 2–3 days per week, balancing the flexibility of distributed work with opportunities for in-person collaboration and connection. Our persona 💡  Smart: We love what we do, and we’re great at it because this is our domain. Our combined knowledge in this space is unmatched. 💚  Dedicated: We get up every day focused on helping our customers win. We’re committed to helping our teammates win, too! 🤗  Approachable: We're friendly, easy to get along with, considerate, and helpful. Our culture and Values 🤩 Customer-Focused We care about our customers. We understand the customer journey, experience, and value derived from Wrike. Decision-making and action-taking are done with the customer in mind. 🤝 Collaborative We work as one and win together, each bringing unique strengths that contribute to diversity of thought for better outcomes. Leveraging our own work management platform, we foster an environment of creative collaboration and shared achievement. 🎨 Creative We strive to succeed through continuous innovation. It’s our pursuit of novel concepts that helped us create a market category. We continue to cultivate a workplace that fosters creative thinking as a means of transcending conventional boundaries and empowers us to break new ground to deliver extraordinary work management solutions. 💪 Committed We believe in ownership at all levels of the organization, by owning workflows from start to finish. Each member of our team is an integral part of this commitment, establishing work as a platform for personal growth and transformation, as well as collective success and growth. Check out our LinkedIn Life Page , Company culture page , Instagram , Wrike Engineering Team , Medium , Meetup.com , Youtube for a feel for what life is like at Wrike.

Location: Nicosia Wrike is the most powerful work management platform. Built for teams and organizations looking to collaborate, create, and exceed every day, Wrike brings everyone and all work into a single place to remove complexity, increase productivity, and free people up to focus on their most purposeful work. Wrike is our people, not a place. As a distributed team, we own our growth, stay globally connected, and rely on the product we build to deliver impactful work alongside brilliant minds. You'll have real ownership over meaningful work, a global team that has your back, and the flexibility to do your best work your way. If that sounds like you, we'd love to hear from you. Our vision: A world where everyone is free to focus on their most purposeful work, together. About the Role: You'll help build the very AI-powered platform you use every day, with real autonomy over the features you ship. As the leading collaborative work management platform, Wrike generates an enormous amount of rich, interconnected data, including work item content, relationships between entities, complex business processes, user interactions, and direct user input. The mission of the DS/ML department is to transform this data into intelligent, AI-powered capabilities that help users gain deeper insights, automate routine work, enhance productivity, and create a more seamless work experience. As a Data Scientist in the Work Intelligence Unit, you will play a key role in product development through the application of state-of-the-art AI and machine learning technologies with a particular focus on leveraging Large Language Models and other emerging technologies. You will work on both user-facing AI features and foundational intelligence platform that power intelligent experiences across the product. Your Impact: 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 Communicating with fellow data scientists, product owners, and developers Applying best software engineering practices to build a reliable codebase Performing code reviews Working in agile environment and presenting the results of your work on regular sprint reviews Your Qualifications: 4+ years of experience in AI,  Data Science, and Machine learning Experience in LLMs, LLM-based APIs, prompting techniques, metric-driven development of prompt-based features, agentic systems, and other related topics Experience in building complex multipart and multistep LLM-based and ML systems Proficiency in Python (including pure Python, and not only jupyter notebooks) Experience in using reproducible research techniques Experience in developing AI solutions for production usage Full professional proficiency in English Standout Qualities: Experience in AI and ML solutions related to one of the areas: social networks, recommendation systems, ranking, entity matching, process mining, system personalization, risk estimation Confident statistical and machine learning skills Experience in creating core AI systems that are foundational to the product and are used in many parts of it Experience in classical software development and architecture Interpersonal skills: Excellent interpersonal, written, and verbal communication skills required with the ability to work within all levels of an organization. You are proactively pushing yourself to develop your skills and knowledge Decision making and argumentation skills Open to feedback and ready to react on it Ability to work autonomously on a project level Our Work Style: Code: Python, Jupyter, mypy, uv, black, flake8 Data: pandas, SQL, BigQuery GenAI & LLMs: Langchain, Azure OpenAI, Gemini, Vertex AI, Braintrust LLM Platform: Versioned Prompt Registry(jinja2), Declarative LLM Feature Configs (multi-step workflows, model routing) ML: scikit-learn, lightgbm, pytorch Cloud: GCP, Dagster, MLFlow Coding Agents: Claude Code, Codex, Cursor Team Dynamics: As part of Wrike’s AI center of excellence — you will help scale AI feature development across teams by collaborating closely with product, engineering, design, research, and other departments across the organization. You will explore new AI-driven opportunities, validate hypotheses through experimentation, and drive innovations from research prototypes to production-ready capabilities that deliver tangible value to millions of users. Benefits & Perks: 25 working days of paid vacation Sick Leave Compensation (5 Uncertified + 10 Certified Days) Parental Leave: Fully Paid Maternity / 4 Weeks Paid Paternity 2 Volunteer Days Medical Insurance (Employees + Dependents) Life Insurance (Employees) Provident Fund Hybrid Working Model School Allowance (Up to €600/month for school aged kids) Simcard w/ Unlimited Internet Access for active employees Office Lunch Allowance (via Wolt) on Wednesdays / Thursdays Work Permit, Blue Card & Naturalization Support What’s Next? Introduction Call with a Recruiter Technical interview Cultural interview Your recruitment buddy will be Alexandra Vorobyova , Lead Recruiter. #LI-AV1 Who Is Wrike and Our Culture We’re a team of innovators and creators who solve the complex work problems of today and tomorrow. Hybrid work mode Wrike is our people, not a place. With 1,000+ employees collaborating across nearly every time zone, we support talent through 10 global hubs — Australia, Costa Rica, Cyprus, Czechia, Estonia, France, India, Ireland, Japan, and the United States — offering flexible ways of working that include remote work, hybrid environments, and co-working spaces across many locations. While flexibility looks different across teams and regions, employees located near certain hubs — particularly in Prague (CZ), Nicosia (CY), Bangalore (IN), and Rennes (FR) — are generally expected to collaborate in person around 2–3 days per week, balancing the flexibility of distributed work with opportunities for in-person collaboration and connection. Our persona 💡  Smart: We love what we do, and we’re great at it because this is our domain. Our combined knowledge in this space is unmatched. 💚  Dedicated: We get up every day focused on helping our customers win. We’re committed to helping our teammates win, too! 🤗  Approachable: We're friendly, easy to get along with, considerate, and helpful. Our culture and Values 🤩 Customer-Focused We care about our customers. We understand the customer journey, experience, and value derived from Wrike. Decision-making and action-taking are done with the customer in mind. 🤝 Collaborative We work as one and win together, each bringing unique strengths that contribute to diversity of thought for better outcomes. Leveraging our own work management platform, we foster an environment of creative collaboration and shared achievement. 🎨 Creative We strive to succeed through continuous innovation. It’s our pursuit of novel concepts that helped us create a market category. We continue to cultivate a workplace that fosters creative thinking as a means of transcending conventional boundaries and empowers us to break new ground to deliver extraordinary work management solutions. 💪 Committed We believe in ownership at all levels of the organization, by owning workflows from start to finish. Each member of our team is an integral part of this commitment, establishing work as a platform for personal growth and transformation, as well as collective success and growth. Check out our LinkedIn Life Page , Company culture page , Instagram , Wrike Engineering Team , Medium , Meetup.com , Youtube for a feel for what life is like at Wrike.

Location: Czech Republic - Remote Wrike is the most powerful work management platform. Built for teams and organizations looking to collaborate, create, and exceed every day, Wrike brings everyone and all work into a single place to remove complexity, increase productivity, and free people up to focus on their most purposeful work. Wrike is our people, not a place. As a distributed team, we own our growth, stay globally connected, and rely on the product we build to deliver impactful work alongside brilliant minds. You'll have real ownership over meaningful work, a global team that has your back, and the flexibility to do your best work your way. If that sounds like you, we'd love to hear from you. Our vision: A world where everyone is free to focus on their most purposeful work, together. About the Role: You'll help build the very AI-powered platform you use every day, with real autonomy over the features you ship. As the leading collaborative work management platform, Wrike generates an enormous amount of rich, interconnected data, including work item content, relationships between entities, complex business processes, user interactions, and direct user input. The mission of the DS/ML department is to transform this data into intelligent, AI-powered capabilities that help users gain deeper insights, automate routine work, enhance productivity, and create a more seamless work experience. As a Data Scientist in the Work Intelligence Unit, you will play a key role in product development through the application of state-of-the-art AI and machine learning technologies with a particular focus on leveraging Large Language Models and other emerging technologies. You will work on both user-facing AI features and foundational intelligence platform that power intelligent experiences across the product. Your Impact: 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 Communicating with fellow data scientists, product owners, and developers Applying best software engineering practices to build a reliable codebase Performing code reviews Working in agile environment and presenting the results of your work on regular sprint reviews Your Qualifications: 4+ years of experience in AI,  Data Science, and Machine learning Experience in LLMs, LLM-based APIs, prompting techniques, metric-driven development of prompt-based features, agentic systems, and other related topics Experience in building complex multipart and multistep LLM-based and ML systems Proficiency in Python (including pure Python, and not only jupyter notebooks) Experience in using reproducible research techniques Experience in developing AI solutions for production usage Full professional proficiency in English Standout Qualities: Experience in AI and ML solutions related to one of the areas: social networks, recommendation systems, ranking, entity matching, process mining, system personalization, risk estimation Confident statistical and machine learning skills Experience in creating core AI systems that are foundational to the product and are used in many parts of it Experience in classical software development and architecture Interpersonal skills: Excellent interpersonal, written, and verbal communication skills required with the ability to work within all levels of an organization. You are proactively pushing yourself to develop your skills and knowledge Decision making and argumentation skills Open to feedback and ready to react on it Ability to work autonomously on a project level Our Work Style: Code: Python, Jupyter, mypy, uv, black, flake8 Data: pandas, SQL, BigQuery GenAI & LLMs: Langchain, Azure OpenAI, Gemini, Vertex AI, Braintrust LLM Platform: Versioned Prompt Registry(jinja2), Declarative LLM Feature Configs (multi-step workflows, model routing) ML: scikit-learn, lightgbm, pytorch Cloud: GCP, Dagster, MLFlow Coding Agents: Claude Code, Codex, Cursor Team Dynamics: As part of Wrike’s AI center of excellence — you will help scale AI feature development across teams by collaborating closely with product, engineering, design, research, and other departments across the organization. You will explore new AI-driven opportunities, validate hypotheses through experimentation, and drive innovations from research prototypes to production-ready capabilities that deliver tangible value to millions of users. Benefits & Perks: 5 Weeks of paid vacation Sick Leave Compensation 5 Paid Uncertified Sick Days 2 weeks fully paid w/ medical certificate, additional 4 weeks paid at 80% salary rate Parental Leave (fully paid): 18 Weeks Maternity / 4 Week Paternity 2 Volunteer Days Meal Vouchers (CZK 220 per working day) Annual Prague Travel Card (Lítačka) Hybrid Working Model Benefit budget with flexible options, including a MultiSport card, Canadian Medical membership, contributions to a pension savings plan and additional choices available through Benefit Plus What’s Next? Introduction Call with a Recruiter Technical interview Cultural interview Your recruitment buddy will be Alexandra Vorobyova , Lead Recruiter. #LI-AV1 Who Is Wrike and Our Culture We’re a team of innovators and creators who solve the complex work problems of today and tomorrow. Hybrid work mode Wrike is our people, not a place. With 1,000+ employees collaborating across nearly every time zone, we support talent through 10 global hubs — Australia, Costa Rica, Cyprus, Czechia, Estonia, France, India, Ireland, Japan, and the United States — offering flexible ways of working that include remote work, hybrid environments, and co-working spaces across many locations. While flexibility looks different across teams and regions, employees located near certain hubs — particularly in Prague (CZ), Nicosia (CY), Bangalore (IN), and Rennes (FR) — are generally expected to collaborate in person around 2–3 days per week, balancing the flexibility of distributed work with opportunities for in-person collaboration and connection. Our persona 💡  Smart: We love what we do, and we’re great at it because this is our domain. Our combined knowledge in this space is unmatched. 💚  Dedicated: We get up every day focused on helping our customers win. We’re committed to helping our teammates win, too! 🤗  Approachable: We're friendly, easy to get along with, considerate, and helpful. Our culture and Values 🤩 Customer-Focused We care about our customers. We understand the customer journey, experience, and value derived from Wrike. Decision-making and action-taking are done with the customer in mind. 🤝 Collaborative We work as one and win together, each bringing unique strengths that contribute to diversity of thought for better outcomes. Leveraging our own work management platform, we foster an environment of creative collaboration and shared achievement. 🎨 Creative We strive to succeed through continuous innovation. It’s our pursuit of novel concepts that helped us create a market category. We continue to cultivate a workplace that fosters creative thinking as a means of transcending conventional boundaries and empowers us to break new ground to deliver extraordinary work management solutions. 💪 Committed We believe in ownership at all levels of the organization, by owning workflows from start to finish. Each member of our team is an integral part of this commitment, establishing work as a platform for personal growth and transformation, as well as collective success and growth. Check out our LinkedIn Life Page , Company culture page , Instagram , Wrike Engineering Team , Medium , Meetup.com , Youtube for a feel for what life is like at Wrike.

Location: Madrid, Spain Workplace: hybrid Are you ready to join our digital revolution journey?    At Aleph, we’re not just part of the digital advertising landscape—we’re shaping its future. Representing the world’s leading platforms, including TikTok, Amazon, Google, and nearly 55 others, we operate in 130+ markets across new and existing geographies.   Our mission is to empower advertisers and brands to unlock the full potential of these platforms' advertising capabilities. By fostering long-lasting partnerships, we create limitless opportunities for people and businesses to advertise effectively at both local and global levels.   With a presence spanning continents, Aleph offers you the chance to be part of a fast-growing, innovative team where your work makes a direct impact. If you’re ambitious, forward-thinking, and eager to thrive in a dynamic, global environment, Aleph is the perfect place to build your career. About The Role: We're an advertising company that lives or dies by how well we connect to the outside world. We integrate with the major social and ad platforms (Meta, Google, TikTok, LinkedIn, Snap, and more) and wire them into our internal systems for billing and reporting. Data moves constantly and in both directions, at scale, and a meaningful part of our estate is legacy. You'll own the technical direction that keeps all of this coherent, resilient, and evolvable — and you'll stay close enough to the code to prove it. This is the top of our individual-contributor ladder. You won't have direct reports; your leverage comes from setting direction, building the hard parts yourself, writing the decisions down, and getting engineers and leadership to build behind them. This is not a role that only draws diagrams — you'll ship production code on the riskiest paths, cut the spike that de-risks a migration, and go deep in the incidents nobody else can crack. We work across PHP, Go, Python, TypeScript, and JavaScript; PHP and Go are both first-class and here to stay, and the right tool for a problem can land in either. You'll be the person who decides where new capability lands, how legacy gets retired, and how we absorb the constant churn of third-party APIs without breaking delivery. What You'll Own: The integration architecture for ingesting from and pushing to external ad/social platforms — versioning, rate limits, backfills, idempotency, webhooks, and graceful degradation when a partner API changes underneath us. The data architecture for information flowing between platforms and internal systems: pipelines, reconciliation, contracts between services, and the path from operational data to reporting. A pragmatic strategy for modernizing the legacy estate — strangler-fig migrations, clear service boundaries, and sound judgement about which language and pattern fit each problem — carried far enough into code that teams can follow the pattern. The engineering bar for integration and data work: the reference implementations, patterns, and standards the org builds against, ratified through the technical committee. What You'll Do: Set the technical direction for new products and major changes, and stay the technical decision-maker through build and post-launch — with the authority to course-correct when implementation drifts, and the habit of being in the codebase to catch the drift early. Build the hard parts yourself. Write production code on the riskiest, highest-leverage paths; prototype the uncertain approach to turn an argument into evidence; build the reference implementation others extend. Turn intangible trade-offs — partner API risk, team capability, long-term scalability, cost of change — into clear, written decisions (ADRs) that leadership and the technical committee can sign off on. Define service and data contracts, integration patterns, and resilience strategies that survive third-party API deprecations and outages. Go deep when it breaks: lead diagnosis on the gnarliest production incidents and performance regressions, and land the fix and the systemic follow-up. Identify the infrastructure (compute, data, messaging, observability) needed to meet current and near-future goals. Raise the bar through others: mentor engineers and tech leads, set the standard in code review, and drive cross-functional decisions across engineering, product, security, and operations — through influence, not line management. Evaluate third-party and vendor solutions against our integration and data requirements. Monitor systems against performance and business benchmarks and escalate with concrete recommendations. What We're Looking For: Substantial experience as a staff/principal engineer (or equivalent) on integration-heavy, data-heavy systems — ideally where you didn't control the external APIs. Still hands-on. You lead by building, and you're demonstrably strong in production code, not only in design. Depth in at least one of PHP, Go, or Python , and comfort across a polyglot estate (TS/JS on the front). A track record of modernising legacy systems incrementally without halting delivery. Fluency in integration and data patterns: idempotency, eventual consistency, rate limiting, queuing, backfills/reconciliation, API versioning. A history of driving technical decisions through influence rather than authority — getting senior leadership and peer engineers to commit to a direction, and backing it with working code. Nice To Have: Experience with ad/martech platform APIs (Meta Marketing, Google Ads, TikTok, etc.). Data warehouse / analytics pipeline experience (e.g. BigQuery). Multi-region, multi-currency, or high-volume billing/reconciliation backgrounds. Why Join Us?   Aleph is a place of many cultures, perspectives, and talents. We support each other, creating an environment of giving and receiving. We value partnership and communication because we believe it takes a group of people to achieve great things. We are energized by our ever-changing industry, our curiosity keeps us learning and seeking out new opportunities.     We stay flexible and adaptable, and believe in moving with the speed of change. We encourage everyone to strive for more, providing our internal talent with growth opportunities and the ability to learn together.    #ALEPH

Location: Tokyo, Japan WHAT IS BOX? Box(NYSE: BOX)はインテリジェントコンテンツ管理（ICM）プラットフォームのリーディングカンパニーです。Boxのプラットフォームは、企業のコラボレーション促進や、コンテンツのライフサイクル全体の管理、重要なコンテンツの保護、そしてエンタープライズAIによるビジネスワークフローの変革を実現することを目指しています。2005年に米国で設立され、JLL、モルガン・スタンレーなどを含む大手グローバル企業や、日本では22,000社超および日経225の85%の企業の業務効率化を支援しています。 Boxは、カリフォルニア州レッドウッドシティーに本社を置き、米国、ヨーロッパ、アジアに拠点を持っています。株式会社Box Japanは2013年に設立された日本法人です。 Boxでは、重要なコンテンツを扱うプラットフォームをさらに推進し、お客様の働き方に大きな変革を提供する、またとない機会があります。コンテンツは私達の業務の中心にあります。契約書、請求書、社員情報、財務情報、製品仕様、マーケティング資産などの部署間に跨る重要なビジネス・プロセスに含まれる数十億ものファイルや情報が日々流れています。私達のミッションは、コンテンツ管理にインテリジェンスをもたらし、お客様がデジタル・トランスフォーメーションを実現するお手伝いをさせていただくことです。このAIと膨大な業務コンテンツの融合による、大規模な働き方の変革期に、そのビジネスの最前線に貢献することが、Boxではできます。 WHY BOX NEEDS YOU テクニカルサポートの世界は、今まさに大きな転換点を迎えています。Boxのプロダクトサポートチームは、単に問い合わせに答えるチームではありません。私たちが目指しているのは、テクノロジーとエンジニアの知恵を融合させ、従来のサポートの枠を超えた新しい顧客体験と価値を生み出すことです。 Box AIをはじめとする新機能の登場により、向き合う技術領域が急速に拡大するなか、AIエージェントをパートナーとして自らの能力を拡張し、ソースコード解析をはじめとする高難度な技術調査や根本原因の究明へ挑む——これまでの時間やリソースの限界を超え、より本質的な顧客課題の解決に集中できる環境を自らの手で作り上げています。それが、今のBoxのテクニカルサポートエンジニアです。 新しいテクノロジーに好奇心を持ち、変化を楽しみながら、チームとお客様の双方にインパクトを与えたいエンジニアを求めています。最先端のAIと共に自らも進化し続けられる環境で、テクニカルサポートの未来を一緒に切り拓きませんか？ WHAT YOU'LL DO Boxを利用するエンタープライズ顧客に対し、高い共感力と強い当事者意識を持ち、期待を超えるテクニカルサポートを提供します チケット管理システムを通じたテキストベースのサポートを主軸としつつ、必要に応じてリモート接続やオンラインミーティングでの詳細な技術説明を実施します Box製品に加え、ネットワーク構成、デスクトップ環境、API/SDKなど多岐にわたる技術領域の問題を調査・解決します 検証環境での事象再現、各種ログ解析（BigQuery、Google Cloud Logging等）、データ調査を通じて、複雑な技術課題の根本原因を特定・解決します AIエージェントを活用した調査・問題解決の自動化に取り組み、その精度向上に貢献します ——パターン化された問題はAIに任せ、あなたはより高度な課題に集中できます ナレッジベースの新規作成・更新を通じて、顧客が自己解決できる仕組みを構築します ——1件の問題を解決するだけでなく、同じ問題が二度と起きないような仕組みづくりを担います 複雑な問題であっても、文章・口頭でお客様にわかりやすく伝えます 製品開発チームへ問題を報告し、製品品質の向上に貢献します 営業・カスタマーサクセス・コンサルティングと密に連携し、顧客ビジネスの成功を支えます Box AIをはじめとする新機能のサポートを通じて、AI領域の知識を実務で磨き続けます チームの業務効率化・スケール化に向けたプロジェクトの立案・実行を担います 他のチームメンバーへの技術的なサポートやナレッジ共有を積極的に行います 社内コミュニティ活動に参加し、チーム文化の醸成に寄与します Boxではコミュニティと対面でのコラボレーションを重要視しています。Boxの社員（Boxers）は、少なくとも毎週3日間以上はオフィスで勤務することが求められます。選考プロセスの中で、リクルーターが働き方や企業文化についてさらに詳しくご説明します。 WHO YOU ARE 私たちは「AIファースト」の企業です。 すなわち、常に成長マインドセットを持ちながら仕事に取り組み、AIを活用し、より迅速かつ適切な意思決定を行い、インパクトを高める方法を見つけていくことが求められます。 複雑な問題を解き明かす、テクニカルサポート業務が好きな方 主体的に責任感を持って物事に取り組める チームメンバーが困っている時には進んで手を差し伸べられる方 2年以上のエンタープライズ顧客向けのL2/Tier2以上のテクニカルサポート経験 新しい製品、技術への熱意がある 高い成長率と速いペースで進む環境で成長し、変化する要求に素早く適応する能力 業務遂行能力とプロジェクト管理能力を有し、部門横断的なコラボレーションを推進し、成果を上げることができる方 前例がない難しい問題に対しても、前向きに取り組み機転をきかせ突破できる人 情報資産の重要性を深く理解し、高い倫理観とコンプライアンス意識を持って業務に取り組める方 REQUIRED SKILLS API、サードパーティ製品連携、およびネットワークトラブル（HAR、Fiddler、Wireshark等を用いた解析）の調査能力 BigQuery や Google Cloud Logging を活用し、自力でクエリ（SQLやログ検索・フィルタクエリ）を記述して、必要なログやデータを的確に抽出・分析し、問題の根本原因を特定できること 日本語： 極めて円滑なビジネスコミュニケーション能力（読み書き、および顧客や社内向けに口頭での高度な技術説明ができるネイティブ同等レベル） NICE-TO-HAVE SKILLS AIツール（LLMツールや、プロダクト内のAI機能）の業務利用経験、またはそれらを用いた業務効率化への関心 SaaS製品のサポート経験 Box の利用経験 MDM ソリューション(Microsoft Intune 等)に関する実務経験 コーディング経験 サポート/CRMツール（Zendesk、Salesforce、Jira等）の実務での利用経験 英語： ビジネスレベルのコミュニケーション能力（読み書きによるグローバルチームとの意思疎通、および社内会議への参加ができるレベル） 業務上使用するツール一例 Zendesk, Salesforce, Slack, Zoom, Google Workspace, Cursor, Google Cloud (BigQuery, Cloud Logging), Fiddler / Charles Proxy, Process Monitor, Wireshark EQUAL OPPORTUNITY We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability, and any other protected ground of discrimination under applicable human rights legislation. For details on how we protect your information when you apply, please see our Personnel Privacy Notice. NOTICE OF USE OF AI At Box, we believe in the power of AI to improve the recruiting process while keeping people at the heart of every decision. For more information on the use of AI in our hiring process, please visit our webpage here .

Location: Argentina; Uruguay; Colombia AI Senior Support Engineer Hours: Aligned to Chicago time (CT) · Engagement: 80 hrs/month, full-stack + data stack remit About the Role Altoros is staffing a Senior Support Engineer for a client engagement supporting an analytics platform. This is a full-stack and data-stack role: the engineer owns the platform shell, the ingestion and semantic layer, and a bounded amount of embedded analytics component upkeep. The role is commercial-model first: month one is an observe and define phase (baseline setting, onboarding), with the engagement shifting toward outcome-based delivery from month two (issue resolution time, defect reduction against baseline, availability targets). AI-augmented delivery is central to this role and one of its most important elements. Working AI-first with Claude Code is how a single engineer credibly covers this full remit. Altoros builds its delivery on Anthropic's professional courses and certification, and the engineer uses Claude Code across the full range of work — maintenance, bug-fixing, and data work, not just new development — operating inside the client's own Claude Code / AI-tooling accounts. Scope & Responsibilities Platform Shell Maintain and extend authentication and SSO integration Own navigation and application shell components (modern front-end framework, e.g., React / TypeScript) Manage tenant and user management, including multi-tenancy considerations Data & Semantic Stack Build and maintain data ingestion pipelines Operate and extend orchestration workflows in Dagster Develop and maintain transformation logic in dbt and SQL Work with the data warehouse on Google Cloud Platform (GCP), primarily BigQuery Maintain the semantic layer in Cube, including metric definitions and data modeling Embedded Analytics (light, bounded) Customize and update Embeddable component files pulled into the client's repo Maintain theming and keep the Embeddable SDK current Note: Embeddable itself handles the builder, embed serving/rendering, security tokens, and multi-tenancy: this is a maintenance layer, not a build-from-scratch effort Delivery & Documentation Maintain centralized documentation in Confluence, including DBML/database diagrams Capture ongoing knowledge for handover and continuity purposes Work to defined outcome targets from month two: P1 issue resolution/mitigation within one business day, defect reduction against an agreed baseline, and business-hours availability once the client is live Use spare capacity (when live issues don't consume the monthly band) on preventative maintenance, hardening, and onboarding new data sources/integrations Required Skills & Experience AI-first delivery (core requirement): hands-on with Claude Code (or similar) / AI-assisted engineering across the full development lifecycle; Anthropic's professional courses and certification are a strong plus (or readiness to complete them) Full-stack development experience, including a modern front-end framework (e.g. React / TypeScript), authentication/SSO implementation, and multi-tenant application architecture Hands-on experience with Dagster for orchestration (or similar tools) Strong DBT and SQL experience for data transformation Experience with BigQuery and the Google Cloud Platform (GCP) data stack Experience with Cube or a comparable semantic-layer / metrics-layer tool Familiarity with embedded analytics tooling (Embeddable or similar), component customization, theming, SDK integration Comfortable working independently and engaging directly with client stakeholders Strong documentation discipline: Confluence, DBML/ER diagrams Available to work core hours aligned to Chicago time (CT) Nice to Have Background supporting analytics/BI platforms for enterprise or sports/media clients Experience setting SLA style targets (resolution time, availability) and reporting against them Engagement Details 80 hours/month, full remit across platform shell, data/semantic stack, and Embeddable upkeep Backup coverage required for continuity during absences: candidate should be able to hand off context cleanly

Location: Mexico City Workplace: Remote THE ROLE We're looking for a Solutions Architect to serve as the primary technical partner for our prospects and customers. You'll work hand-in-hand with Sales throughout the full lifecycle: qualifying technical requirements, designing and proving out architectures, running proofs of concept, and guiding customers from first evaluation through to production at scale. You'll be the trusted technical voice in the room, translating ClickHouse's architecture and capabilities into solutions that solve real business problems. WHAT YOU'LL DO - Act as the technical advisor for prospects and customers evaluating or scaling ClickHouse, from discovery through production deployment. - Design reference architectures, data models, and ingestion/query patterns tailored to each customer's use case, scale, and existing data stack. - Own and run technical proofs of concept and benchmarks, demonstrating ClickHouse's performance, scalability, and cost advantages against incumbent solutions. - Partner closely with Account Executives to build technical account strategy, navigate procurement/security reviews, and close complex deals. - Deliver compelling technical presentations, demos, and workshops to audiences ranging from individual engineers to VP/C-level stakeholders. - Advise customers on schema design, query optimization, cluster sizing, replication, and migration strategy from other databases (e.g., Postgres, Elasticsearch, Snowflake, Druid, Spark). - Serve as the voice of the customer internally, feeding product and engineering teams structured feedback on gaps, feature requests, and competitive positioning. - Build reusable assets, demos, and technical content (blog posts, reference architectures, sample apps) that scale your impact across the field team. - Contribute to team best practices, tooling, and onboarding materials. WHAT WE'RE LOOKING FOR - Experience in a customer-facing technical role such as Solutions Architect, Sales Engineer, Data Engineer, or Technical Consultant, ideally at an infrastructure, database, or analytics company. - Deep hands-on experience with SQL and analytical/OLAP databases (ClickHouse, Snowflake, BigQuery, Druid, Vertica, Redshift, or similar); ClickHouse experience is a strong plus. - Strong understanding of distributed systems fundamentals: partitioning, replication, consistency trade-offs, and query execution at scale. - Comfort working across the modern data stack, including streaming systems (Kafka), orchestration tools, BI tools, and cloud infrastructure (AWS, GCP, or Azure). - Ability to run and win technical evaluations against competitive alternatives, with a track record of influencing buying decisions. - Excellent communication skills, able to flex between whiteboarding with engineers and presenting business value to executives. - Self-starter who thrives with ambiguity and enjoys being both hands-on with technology and directly responsible for revenue outcomes. - Willingness to travel periodically for customer visits, conferences, and team events. NICE TO HAVE - Direct experience deploying or administering ClickHouse in production. - Experience with real-time analytics, observability, or large-scale event/log data use cases. - Contributions to open-source data infrastructure projects. - Prior experience at an early-stage or hypergrowth startup. WHY CLICKHOUSE - Work with one of the fastest-growing open-source projects and databases in the industry, at the center of the real-time analytics category. - Join a technically excellent, customer-obsessed team that ships fast and takes ownership. - Competitive compensation, equity, and benefits, with a remote-friendly, distributed culture. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Netherlands; Romania; Bulgaria; Canada; Serbia; Kazakhstan; United States; Spain; Portugal; Moldova; Philippines; Poland Workplace: Remote About the company Turning marketing into a market-domination weapon, we created a new category - the marketplace for future customers. Businesses shop for leads as they shop for products in e-commerce: you see everything about a lead before you buy - full transparency, control, and predictable outcomes. We're the #1 lead marketplace in the USA, and we're accelerating. Role overview We are looking for a Product Manager to ensure we always build the most valuable things for our marketplace — measured in money, not opinion. You will own the outward half of the product: users, market, and the "what and why." Working closely with a Product Owner who owns delivery ("how and when"), your job is to make sure not a single sprint is spent on something that does not move LTV, margin, or retention. Requirements 3+ years in B2B SaaS or marketplaces, with clear examples of metrics you moved and can prove. Strong understanding of unit economics, including LTV, CAC, payback, and contribution margin. Hands-on user research experience with real synthesis work behind it. Ability to tie product ideas to measurable upside before development starts. Experience pulling and working with your own data using SQL, Amplitude, BigQuery, or similar tools. English C1+; your users are American real estate investors, and communication needs to be sharp and clear. AI-first by default — if you are not using AI to 3x your output already, you will be behind our engineers. High ownership and strong decision-making in ambiguous, fast-moving environments. What You'll Be Doing Talk to users constantly: buyers, power accounts, and churned users — and turn conversations into decisions, not decks. Own platform improvement broadly across onboarding, buying experience, lead quality, retention, and monetization. Find the weakest link, fix it, then move to the next. Own the unit economics of every bet by tying each brief to LTV, CAC payback, margin per lead, or revenue per active user. If you cannot put a number on the upside, it is not a brief yet. Model value before anything is built, using rough sizing of expected impact so engineering time goes to things that move money, not things that only feel nice. Write one-page briefs built around problem, evidence, and expected impact, then hand them off and trust the execution. Ship experiments weekly, kill failures fast, and scale winners. Pull your own data directly; there should be no analyst between you and the truth. Track competitor changes closely and know what they shipped before users tell you. This is not for you if You measure success in features shipped. You cannot tie a feature to a number. You want to manage the sprint and own the delivery. That is a different role. What we expect from you (first 3 months) We do not do long onboarding. Access on day one, context in days, a real problem in week one. We hire people who create value with incomplete information, because that is the job every day after probation too. End of month 1: you know the platform as a real user does because you have used it like one; you have mapped the weakest points in the funnel, ranked with evidence and value; and you have handed off your first accepted brief. End of month 3 (the bar): multiple shipped changes with measurable results you can defend, with at least one of them moving a core metric such as activation, churn, LQS, or revenue per user. A live experiment pipeline exists so something is always being tested. Your validated brief backlog is deep enough that the team never waits on you for direction. We trust your "this is worth building" without re-checking it. How We Work With You: We use honest checkpoints at 2 weeks, 1 month, and 2 months. We judge trajectory, not perfection. Wrong fast and corrected beats slow and safe. If the fit is wrong, both sides should know by month 2 and say it out loud. Nice to Have Experience in startup or fast-scaling tech environments. Experience in marketplace, SaaS, real estate, lead generation, or other performance-driven digital businesses. Familiarity with experimentation systems, product analytics, and growth-focused product work. What We Offer Impact: Work at the core of a product-led, AI-powered startup where your decisions directly affect business performance. Autonomy: High ownership, low bureaucracy, and real authority over product direction. Flexibility: Remote-first culture with flexible hours and async-friendly communication. Compensation: Competitive salary above the market average. Team: Join a smart, passionate team that moves fast, supports each other, and builds cool stuff. Time Off: Three weeks paid vacation plus 5 paid sick days annually. Growth: Unlimited learning policy — paid courses, books, and growth resources. AI-Heavy Environment: AI is deeply embedded across prospecting, research, and workflows. Ownership: Real decision-making power and direct ownership of your outcomes.

Location: Ukraine; Moldova; Latvia; Slovakia; Czech Republic; Slovenia; Romania; Turkey; Kazakhstan; Brazil; Poland; Hungary; Montenegro; Estonia; European Union; Cyprus; Lithuania; Serbia; Georgia Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE We are seeking a Billing Data Analyst to join our Billing and Data team. You will play a key role in analyzing financial performance, billing behavior, risk trends, and support operations. Your work will help drive better decision-making, reduce financial risks, and improve billing efficiency across all products. This role combines analytical rigor, statistical thinking, and cross-functional collaboration. KEY RESPONSIBILITIES - Monitor, analyze, and report on key billing and support performance indicators and emerging trends. - Build and maintain data pipelines to ensure accurate, timely, and reliable data delivery. - Apply statistical methods to project scenarios, assess “what-if” outcomes, and anticipate financial risks. - Run A/B tests and experiments to evaluate billing and support strategies. - Collaborate with cross-functional teams (Billing, Support, Finance, Product, Marketing) to align processes with risk-mitigation goals. - Analyze the impact of marketing and product changes on billing outcomes, risk behavior, and customer support metrics. - Provide actionable recommendations to improve billing performance and reduce disputes, churn, and operational inefficiencies. - Document analyses, workflows, and data logic to ensure clarity and consistency. QUALIFICATIONS - Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or a related field. - Experience as a Data Analyst, ideally within fintech, subscription products, billing, or customer support. - Strong SQL skills. - Experience with popular BI tools such as Tableau, Looker, or similar - Experience with Python or R - Solid understanding of statistical analysis, forecasting, and scenario modeling. - Experience running A/B tests and interpreting experiment results. - Excellent problem-solving skills, attention to detail, and ability to work in a fast-paced environment. - Strong communication skills, with the ability to explain findings to both technical and non-technical stakeholders. - Curiosity, ownership mindset, and the discipline to maintain high-quality data work. NICE TO HAVE - Experience with BigQuery, ClickHouse, or any cloud data warehouse. - Basic Python knowledge for data cleaning or simple analysis. - Exposure to subscription businesses or payment systems. - Understanding of disputes, chargebacks, declines, or fraud signals. - Familiarity with DBT or data quality frameworks. LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0 Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! INTERVIEW PROCESS After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps: - Recruiter Screening (40 minutes) - Technical Interview (60 minutes) - Final Interview (30 minutes) LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

Задачи: — Анализировать поведение игроков для выявления закономерностей и возможностей. — Проектировать и анализировать A/B тесты: от постановки гипотез и расчёта размера выборки до интерпретации результатов и предоставления рекомендаций. — Поддерживать запуск новых функций, предоставляя аналитику для оценки и принятия решений на основе данных. — Самостоятельно выявлять тренды и аномалии, а не только реагировать на запросы. — Тесно сотрудничать с продюсерами и гейм-дизайнерами. — Создавать и поддерживать качественные дашборды в Tableau. — Проектировать и внедрять новые аналитические события в продукт. — Вносить вклад в разработку и развитие внутренних аналитических инструментов. Требования: — Опыт работы от 1 года в роли Product или Data Analyst в игровой индустрии. — Продвинутый уровень SQL, опыт работы с BigQuery. — Мастерство в A/B тестировании, понимание статистики и ограничений. — Знание метрик F2P и их взаимосвязей. — Умение создавать профессиональные дашборды в Tableau. — Навыки коммуникации для простого изложения сложных данных руководству. — Базовый опыт работы с Git для управления запросами и аналитическим кодом. — Использование современных AI-инструментов (Claude, Cursor и др.) для повышения эффективности. Преимущества: — Знание dbt и понимание моделей данных. — Владение Python для аналитики (Pandas, визуализация, автоматизация). — Опыт работы с платформами для экспериментов (GrowthBook). — Интерес к AI и его практическому применению. Условия: — Баланс работы и личной жизни. — Возможность работать в офисе и удалённо по согласованию. — Подарки от компании по важным событиям (100 USD). — Личный депозит на благополучие 250 USD. — 30 больничных дней в году с 100% оплатой при превышении лимита. — 19 оплачиваемых отпускных дней в году. — 12 дней отпуска по уходу, по одному в месяц.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's researchers generate and depend on enormous amounts of data — training runs, evaluations, RL transcripts, annotations etc... The Research Data Platform team builds the systems that make that data easy to produce, find, query, and trust. We work in two modes: we build platform components that other systems plug into (for example, a metrics library that training frameworks integrate to record and retrieve run data), and we own core datasets end to end (for example, the data pipeline behind RL transcripts). As the team's tech lead, your job starts with our users. You'll work directly with researchers — and with the engineers who support them — to understand how they actually work, where managing data slows them down, and where a well-built platform component or a well-curated dataset would change what's possible. You'll turn what you learn into technical direction for the team, in partnership with the team's manager, who owns priorities and people. A central ambition you'll drive: a small set of canonical, well-documented datasets — starting with the core data model for RL — that researchers trust and standardize on, rather than every team managing its own copies. You'll spend your first few months close to the code and close to users: shipping improvements in our core systems, embedding with research teams, and building your own map of their workflows. As the team grows, this role has a natural path into formal people leadership for someone who wants it. Responsibilities Work directly with researchers and the engineers supporting them to understand their workflows, identify the highest-leverage opportunities, and shape what the team builds next Set the technical direction for the team across our platform and our datasets Design and build platform components that other teams plug into — libraries, services, and interfaces such as the metrics library used by training frameworks Own core datasets end to end: the pipelines that produce them, the schemas that define them, and the documentation and guarantees that make researchers trust them Drive convergence toward canonical datasets — including the core data model for RL transcripts — that research teams standardize on Lead complex, multi-quarter projects that span several systems and teams, staying hands-on in the code Raise the team's technical bar through design reviews, mentorship, and the quality of your own work You may be a good fit if you: Have built and operated data-intensive systems at scale — pipelines, storage layers, query systems — with strong instincts for data modeling and schema design that hold up as usage grows Have set technical direction for a team, or owned the architecture of a data platform that other teams build on Treat internal users as customers: you do the discovery work, iterate with users, and measure success by adoption rather than by shipping Understand that researchers aren’t typical internal customers — the work is exploratory by nature, workflows differ from team to team, and requirements are discovered through experiments rather than specified up front Can build for that motion — keeping interfaces stable and data trustworthy while use cases change underneath you, and judging when a quick, disposable solution serves research better than a durable one Lead through influence — aligning engineers and stakeholders without relying on formal authority Are results-oriented and pragmatic, willing to do unglamorous work when it's the highest-leverage thing Are excited about learning the fundamentals of machine learning research (deep ML expertise is not required) Care about the societal impacts of your work Strong candidates may also have Experience with large-scale ETL and columnar or analytical storage (e.g., Spark, BigQuery, ClickHouse, DuckDB, Parquet) Experience with metrics or experiment-tracking systems, or high-volume time-series data Experience with dataset management, cataloging, or lineage tooling Built developer tooling or internal data platforms for demanding technical users — including in domains like quantitative trading, where fast-moving, exploratory data work looks a lot like research A working knowledge of machine learning Worked in, or closely with, an ML research lab Interest in — or experience with — people management and growing engineers The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York City, New York, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. About Tavily We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent — but also informed. We work with some of the most innovative teams in AI — from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world. The Role We are looking for a Senior Software Engineer to design and build the billing platform behind a novel search engine tailored for agentic AI consumption. This role is based in our New York office, hybrid with the NYC team. Our APIs are used by millions of developers and the AI agents acting on their behalf, all paying based on what they consume. You will own the systems that turn product usage into accurate, trustworthy revenue, supporting flexible billing models—usage-based pricing, subscriptions, prepaid balances with auto top-up, and enterprise contracts. Correctness is non-negotiable: every event must be measured precisely and every invoice must be right to the cent. ‌ In this position, your responsibility will be to: Design and operate the billing platform end to end, from usage events to invoices Build metering and usage-aggregation pipelines that turn high-volume events into billable amounts Design and operate prepaid credit/wallet systems with auto top-up and balance management Support enterprise/contract billing with custom pricing, negotiated terms, and scheduled invoicing Build reconciliation, idempotency, and invoice-accuracy safeguards to ensure revenue data is always correct Lead the migration to the next generation of our billing system with no revenue loss or downtime Define observability and quality metrics for billing correctness, freshness, and throughput Ensure billing systems meet audit and compliance requirements ( SOX , financial audit) ‌ What we're looking for : 6+ years building production backend systems, of which 3+ years actively building and operating billing or metering systems in production Hands-on experience with usage-based / metered billing: rating, aggregation, and proration logic Hands-on experience with subscription / recurring billing alongside usage-based models Hands-on experience with prepaid credits / wallet systems and auto top-up mechanics Hands-on experience with enterprise / contract billing: custom pricing and negotiated terms End-to-end integration of a third-party billing platform (Stripe Billing, Metronome, Orb, or Zuora) Strong expertise in Python and TypeScript/Node (Go a plus) Production experience with transactional databases (Postgres or equivalent) for financial-grade data Built high-volume event / usage pipelines into a data warehouse (Kafka or Kinesis → Snowflake or BigQuery) Owned billing correctness in production: reconciliation, idempotency, invoice accuracy Product-Led Growth (PLG) experience: worked on billing for high-volume, self-serve users Hands-on with Auth0, Okta, or similar identity systems in production Shipped revenue systems under SOX or financial audit constraints Nice to have: Led a billing system migration or re-platform with zero revenue loss or downtime Built hybrid billing combining usage, subscriptions, and prepaid in one system Worked across both a payments layer (Stripe) and a metering / rating layer (Metronome / Orb) Billed a developer-facing / API product with pay-as-you-go and API-key metering Used Snowflake for usage aggregation and revenue analytics Why Tavily ? Full ownership — small team, you own the entire infrastructure, not a slice of it Real scaling challenges — bursty scraping workloads, cache invalidation, multi-region, millions of daily requests AI-native company — your infra directly powers AI agents used by leading companies in the space. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $147,200 — $224,300 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

RELOCATION TO LONDON OR BARCELONA | PERK Company Perk is an intelligent platform for travel and spend management, automating manual processes to help businesses reclaim lost productivity. What you will do Design and maintain efficient ELT pipelines using dbt to transform raw data into clean models. Implement best-practice data modeling and software engineering techniques, including CI/CD and testing. Develop comprehensive data quality checks and monitoring scripts to ensure reliability. Collaborate with analysts and business users to optimize data models for specific analytical use cases. Tune SQL queries and data models to improve warehouse performance and reduce latency. Build scalable, compelling data visualizations in Looker for large teams. Requirements 3+ years of experience in a data-focused role such as Analytics Engineer, Data Analyst, or BI Developer. Expert-level proficiency in SQL. Hands-on experience with dbt or similar transformation frameworks. Experience with cloud data warehouses like Snowflake, BigQuery, or Redshift. Solid understanding of dimensional modeling and ETL/ELT principles. Proficiency with Git for version control. Must be based within commuting distance of London or Barcelona. Nice to have Python expertise for automation and orchestration. Experience with semantic layers and orchestration tools like Airflow. Knowledge of modern software engineering practices applied to data. Culture & Benefits IRL-first culture emphasizing connectivity and collaboration. Opportunity to work in a global, diverse environment with teams across 12 offices. Focus on professional growth and impact within a fast-growing SaaS company. Equal opportunity employer committed to diversity and inclusion.

Location: Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations: Austin, TX - Hybrid About the team The Data Intelligence & Analytics organization builds the core data platform and internal products that power decision-making across the company. We design and operate large-scale data systems, own the company’s data lake, ingestion infrastructure, and platform tooling, and develop end-to-end applications that transform complex datasets into fast, reliable, business-critical products used daily by go-to-market, product, and engineering teams. Our work sits at the intersection of data platforms, distributed systems, and product development, giving engineers the opportunity to own meaningful problems across the stack and build systems that truly run the business. About the role We are looking for a visionary and hands-on Lead Machine Learning Engineer to join our Austin team. In this role, you will be the principal architect behind the next generation of our unified AI/ML platform, designing and building the infrastructure that powers everything from traditional predictive models to generative AI, large language models (LLMs), and autonomous agent frameworks. You will own the end-to-end technical strategy, blueprint, and execution of scalable backend services and data pipelines that support AI-driven applications across go-to-market, engineering, and product teams. Because our products are initiated and owned entirely within the team, you will drive the vision from initial requirements and system design to global deployment, optimization, and long-term evolutionary ownership. What you'll do Architect and evolve a highly scalable, multi-tenant AI/ML platform that seamlessly unifies traditional ML (classification, regression, forecasting) and Generative AI/LLM orchestration. Design and implement robust production-grade AI Agents and Advanced Chatbots. Build reliable execution environments for Multi-Agent Systems, including state management, long-term memory architectures, and Model Context Protocol (MCP) server integrations. Build high-throughput, low-latency application backends and orchestration layers. Partner closely with data, platform, and full-stack engineers to ensure seamless feature delivery and reliable production operations. Act as a technical anchor for the Data Science team – enforcing rigorous engineering standards, leading design and security reviews, evaluating build-vs-buy decisions, and mapping business requirements to robust technical designs. Evaluate trade-offs and drive adoption of modern AI infrastructure tools, optimized embedding pipelines, vector databases, and serverless compute paradigms (such as Workers AI).\ Must-Have Skills Extensive experience as a Senior or Lead ML Engineer, with a proven track record of architecting and operating production-grade ML platforms, services  and distributed backends. Strong competency in Traditional ML lifecycles (feature stores, training pipelines, model monitoring) alongside deep experience in Generative AI patterns (RAG pipelines, context engineering, fine-tuning, guardrailing, and agentic AI systems). Mastery of Python and robust experience with modern backend ecosystems. Familiarity with (or willingness to collaborate on) full-stack technologies like React and TypeScript is highly valued. A builder's mindset. You are comfortable navigating ambiguity, shaping your own technical roadmap, adapt as needed and taking extreme ownership of system reliability, costs, and model performance. Nice-to-Have Skills Technical Leadership & Systems Architecture 3+ years of dedicated ML Engineering experience within a large-scale, enterprise environment (handling petabyte-scale data and working across globally distributed teams). Proven ability to architect, scale, and secure reliable, highly observable distributed systems, with a track record of leveling up platform foundations. Experience mentoring engineers, leading by example through high-quality code and rigorous design reviews, and fostering a culture of technical excellence. Strong problem-solving skills with a demonstrated ability to independently drive complex projects through ambiguous spaces and collaborate cross-functionally with data engineers, full-stack teams, and analysts. AI, LLMOps & Agentic Engineering Hands-on proficiency in building production-grade GenAI applications and multi-agent systems using advanced LLM frameworks like LangGraph, LangChain, or Autogen. Deep understanding of agent harness primitives, state management, memory architectures, and tool-calling loop mechanics. Experience establishing LLMOps foundations, including automated prompt tracking, LLM evaluation pipelines (e.g., Ragas, TruLens), vector database optimization, context/token management, and real-time guardrailing/moderation layers. Deep experience in scientific computing using Python (Scikit-Learn, PyTorch, or TensorFlow) and deploying traditional systems for end-to-end training, batch/real-time inference, and model observability. Infrastructure, Cloud & Data Platforms Strong experience with Docker and Kubernetes for containerization and orchestration, alongside Infrastructure-as-Code tools like Terraform and public cloud ecosystems (GCP, AWS, or Azure). Hands-on experience with modern MLOps platform tools (e.g., Airflow, Argo Workflows, ArgoCD) and data systems including BigQuery, Postgres, and robust ETL/ELT practices. Experience with full-stack web technologies and serverless/edge environments (FastAPI, TypeScript/JavaScript, Cloudflare Workers), with the agility to contribute across a multi-language stack. Strong foundation in continuous integration/continuous deployment (CI/CD), testing frameworks (Pytest), and robust version control practices. Education & Communication M.S. or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field. Exceptional written and verbal communication skills, with the ability to translate complex technical architectures into clear concepts for both engineering peers and business stakeholders. Equity This role is eligible to participate in Cloudflare's equity plan. Benefits Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun! The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S. Health & Welfare Benefits Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Financial Benefits Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Time Off Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

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

Location: Gibraltar; Malta; Georgia; Isle of Man; Poland; Romania; Ukraine Workplace: Remote About Patrianna Patrianna is a fast-scaling product development company headquartered in Gibraltar, with a dynamic, global team powering our growth. We operate at the intersection of technology and entertainment, building innovative solutions that shape the future of social gaming and deliver outstanding experiences to millions of players worldwide. We're driven by speed, ambition, and bold ideas. At our core, we're product creators and problem-solvers who thrive in a high-performance environment. We're looking for exceptional talent—smart, adaptable, and motivated individuals eager to make an impact, scale business functions at pace, and continuously improve. The Role Design, build, and manage advanced data systems that turn raw player data into actionable insights, powering personalized gaming experiences for millions. What you will be doing • Develop batch and real-time data pipelines on our GCP platform • Build APIs to share data with other teams and develop CI/CD pipelines for automated deployments • Develop Terraform IAC for deploying core infrastructure and use Datastream to ingest CDC data • Use Dataform and dbt to build medallion data architecture while optimizing BigQuery and ClickHouse models • Build Airflow DAG pipelines for data imports/exports with monitoring and alerting for data integrity • Uphold GDPR/CCPA compliance and maintain data governance standards across platforms What we are looking for • Strong proficiency in Bash, Git, SQL and Python (essential skills) • Hands-on experience with Terraform IAC, Docker and Kubernetes • Solid GCP expertise including BigQuery, Dataform, Airflow, and Datastream • Real-time processing experience with Kafka, PySpark, or Flink • Proven ETL/CI-CD development skills and API development capabilities • Bachelor's in Computer Science, Data Science, Information Systems, or equivalent experience Why you will love it Your pipelines will personalize gaming experiences for millions while detecting fraud and driving monetization. You'll work with cutting-edge GCP technology, enjoy autonomy in your role, and learn from a collaborative global team. We offer flexible remote options, professional development opportunities, and a culture that celebrates diverse ideas and breakthrough thinking. Equal Opportunities We hire based on skills, drive, and ideas—nothing else. Your background, gender, age, race, ethnicity, disability, sexual orientation, religion, neurodiversity, or educational path will never be a barrier to joining us. We also welcome candidates from non-traditional career journeys and value diverse perspectives that challenge conventional thinking. Diversity fuels our innovation, collaboration, and growth, and we're committed to creating an environment where everyone can contribute their best work and thrive.