Customer Support in San Francisco

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About The Role & Team Amplitude is only as useful as the data inside it. The Data Warehouse and Integrations team owns how that data gets in and out — importing behavioral and customer data from cloud data warehouses like Snowflake, Databricks, and BigQuery, from cloud object storage like S3 and Azure Blob Storage, and pushing enriched event data back out to warehouses, object storage, streaming destinations, and downstream advertising and marketing platforms. That means batch and streaming pipelines moving billions of events a day, connections that have to keep working across dozens of customer-controlled systems, credentials and configuration that have to stay correct and secure, and latency and reliability targets that customers build their own pipelines on top of. Recent work includes launching new warehouse export destinations, migrating our import

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management ro

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About The Role & Team The Senior Marketing Analyst will be a strategic analytics partner to the Marketing organization, helping leaders understand performance, identify opportunities, and make better decisions through data. Reporting to the Director of Marketing Operations, you'll bring strong B2B SaaS analytics expertise to marketing planning, performance measurement, and business insights. You'll work closely with Marketing, GTM Analytics, Sales Analytics, Customer Success Analytics, and FP&A to connect data across the funnel and translate it into actionable recommendations. This is an opportunity to have a meaningful impact on how Amplitude measures and drives efficient GTM growth. As a Senior Marketing Analyst, you will: Turn data into actionable marketing insights: Analyze marketing performance and funnel trends to identify what's w

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. Senior Software Engineer - Analytics Compute Platform Team About the Role & Team Every chart, insight, and experiment result a customer sees in Amplitude passes through the compute layer that this team owns. Our team sits between Amplitude's front-end analytics products/ rest APIs/ MCPs and Nova, our proprietary analytics database, and owns the compute API that translates a user's question into a fast, correct answer. Our mandate: enable a highly performant, reliable, and flexible way to compute insights. Those three goals are often in tension the more flexible we make the system, the harder it is to keep it fast and simple, and a lot of the interesting engineering work on this team lives in that tradeoff. Day to day, you'll work closely with engineers on data management, marketing analytics, Session Replay, Experiment, CDP, Query,

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. The Senior Enterprise Engineer opportunity Statsig is building an Enterprise Engineering team for engineers who want unusually direct ownership of high-stakes customer outcomes. Like a Forward Deployed Engineering team, Enterprise Engineering works extremely close to customers and tackles the technical problems that matter most to them. The difference is the scope of ownership. Forward Deployed Engineering is often concentrated around implementation or onboarding; Enterprise Engineering is responsible for a customer’s technical success throughout the entire customer journey. You’ll stay close as needs evolve, answering questions, investigating across the stack, identifying root causes, shipping fixes and features, and remaining accountable through resolution. This is a software engineering role with a tight customer feedback loop. It is ideal for a pragmati

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Team Marketing at Snorkel is growing rapidly and anchored by high-ownership operators who lead independently, align cross-functionally, and consistently deliver outsized results. We partner across Sales, Product, Research, and the executive team to translate complex AI and data value into differentiated positioning, integrated programs, and field-ready enablement that accelerates growth. The culture is high standards, high autonomy, and high collaboration. About the Role Reporting to the Sr. Director of Product Marketing, the Product Marketing Manager, Frontier Labs will own the GTM execution for our frontier lab business. You will partner closely with Research, FDE, and frontier-facing sales teams to translate technical work into research-credible positioning, repeatable sales plays, and high-quality GTM programs that resonate with research and procurement leaders inside frontier labs. You will keep the frontier asset library (battlecards, technical one-pagers, decks, benchmark and eval narratives) sharp against a fast-moving market, and bring competitive and customer insight into every motion. This is a hands-on role for a product marketer who wants

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! Counsel, Commercial What You’ll Do Snorkel AI is looking for a Counsel, Commercial to join our growing Legal team, reporting to Snorkel’s Associate General Counsel, Commercial. This is a key role across Snorkel’s commercial contracting function, including vendor agreements and customer agreements. You will serve as a trusted legal partner to business teams across the company, drafting, reviewing, and negotiating a wide range of commercial contracts while helping build scalable processes. You’ll work closely with cross-functional stakeholders, combining strong commercial legal skills with the hands-on, execution-oriented approach required in a fast-growing technology company. This hybrid role is based in San Francisco or New York City. Responsibilities Draft, review, and negotiate a broad range of commercial contracts, including vendor and customer agreements, NDAs, MSAs, SOWs, order forms, and other commercial arrangements. Serve as a trusted legal partner to cross-functional teams on commercial contracts. Manage a high volume of contracts and competing priorities, ensuring timely execution and alignment with business objectives. Review and negotiate commercial

About the role AI and coding agents have made building enterprise apps nearly effortless and exposed a massive gap in the infrastructure to run them. Sigma is emerging as the AI Runtime Environment that makes enterprise AI actually work, and this role will tell that story to the market, why it matters, and help define and create this new category. As Director of Product Marketing for AI, you will own the positioning and go-to-market strategy for Sigma's overall AI narrative and its specific capabilities, including: natural language exploration, agentic workflows, and AI-powered application building (both internal and using external coding agents). This is a high-visibility, high-impact role that sits at the intersection of product, sales, and the market. You'll translate a rapidly evolving AI roadmap into sharp, differentiated messaging that resonates with data teams, business leaders, and the enterprise IT buyers who evaluate and approve AI investments. You will be a key voice in helping Sigma win the category. What you'll do Define and own Sigma's AI product positioning and messaging from core value propositions to competitive differentiation and persona-specific narratives. Partner with Product and Engineering to understand and influence Sigma's AI capabilities and roadmap. Lead product launches for AI features and capabilities, coordinating across marketing, sales, customer success, and partnerships. Partner with sales leadership and frontline reps to understand AI deal dynamics, competitive objections, and messaging gaps and incorporate learnings into improved positioning, content, and enablement. Partner with the Enablement team, build and maintain sales enablement materials pitch decks, battlecards, demos, objection-handling guides that help the field win competitive AI deals. Develop thought leadership content and market education programs that shape how the industry thinks about building with AI on enterprise data. Conduct ongoing

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators and

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data