Ai And Cloud Service Provider Account Executive in San Francisco

You will: Manage the growth program from end to end, including top-of-the-funnel growth / recruiting campaigns, applications processing, and hiring and onboarding Represent and champion the brand, promoting its value proposition to candidates and stakeholders, driving engagement, and taking ownership of process improvements that streamline growth pipelines and support program success Optimize full growth funnel for conversion and experience Build and lead new growth recruiting campaigns and channels to meet business goals Be the subject matter expert for all recruiting systems (ATS: Greenhouse), tools, and processes, and provide training/onboarding as needed Own internal reporting and analytics, and keeping all the internal hiring data clean and up-to-date in our systems Be the strategic driver behind on impactful initiatives to improve the workflow, data infrastructure and reporting Proactively flag discrepancies in hiring plans, interview process, JDs, offer details, etc. and maintain data integrity and operational excellence within the team Work from the San Francisco office, with occasional travel for onsite growth events. Ideally you’d have: Minimum of 3-7 years of experience working in Growth, Recruiting or RecOps at a rapidly growing company Extensive experience using Greenhouse as a Site Admin (user permissions, approvals, custom options) and pulling ad hoc reports using our internal TA tools (report connector, reporting capabilities, and limitations) Strong knowledge of Gsuite (VLOOKUP, pivot tables, data validation, conditional statements and formatting, filters, etc.) Excellent written and verbal communication skills, with the ability to tailor messaging to diverse audiences Must have a deep understanding of Growth / Recruiting Pipelines, Funnels and Conversion metrics Demonstrated excellent project management skills, ability to pull and manipulate data sets, critically analyze existing processes, and identify opportunities for process improvement Able to

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead , you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. You will: Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order. Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced. Close. Own it from cold outreach to signature. Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable. Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline. Ideally, you’d have: 5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there A strong track record of managing important external relationships Strong business judgment and the ability to evaluate partnership value quickly Clear communication skills and comfort working with senior stakeholders Ability to operate independently while staying closely connected to cross-functional teams A practical, hands-on approach to building new functions from the ground up Comfort working in fast-moving, ambiguous environments Experience in

Owns day-to-day deal pricing execution for Enterprise, including pricing calculations, staffing inputs, and dashboard reporting that gives Sales and Deal Desk leadership visibility into deal status, pricing, and margin. Partners with the Deal Desk Manager on customer deal structuring and on identifying ways to accelerate the deal approval process. What You’ll Do Deal Pricing Execution Manages day-to-day deal pricing calculations for Enterprise deals, including ROI modeling and EPD staffing inputs Applies existing pricing frameworks consistently across Land, Expansion, and Framework deals Partners with the Deal Desk Manager to design customer-specific deal structures for non-standard or complex deals Pricing & Deal Status Reporting Builds and maintains a pricing dashboard tracking deal status, pricing, margin, and overall deal health across the Enterprise pipeline Updates pricing and trend reporting to keep leadership current on where deals stand and how pricing is trending against targets Process Optimization Identifies bottlenecks in the deal review & approval process and proposes ways to accelerate cycle time Helps standardize and streamline recurring pricing/approval steps into repeatable, lower-friction workflows Tracks deal approval cycle time and surfaces trends to inform process improvements Cross-Functional Deal Coordination Owns deal crafting end-to-end from initial pricing/modeling through contract review, coordinating with sales management, reps, and internal stakeholders Ensures the relevant stakeholders (Accounting, Finance, EPD, Legal) review and approve deals at the appropriate stage before they progress Routes deal packages to the correct reviewers and tracks open items so deals aren't stalled waiting on sign-off Strategic & GTM Support Tackles ambiguous, open-ended questions around Scale's go-to-market motion and iterates quickly on solutions that deliver measurable results Supports Sales and Finance leadership in quarterly strategy and

About Scale 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 both 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 are producing is some of the most important work for how humanity will interact with AI. Our Approach As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale. Responsibilities: Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your use

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! The Role We're looking for our founding AI Data Product Manager to own Snorkel's Agentic Data and RL Environments roadmap. In this role, you'll lead the product strategy for a variety of data types (e.g. Agentic Coding, Computer Use). You will shape the roadmap for the datasets Snorkel invests in by understanding the market, incorporating frontier lab needs and collaborating with researchers at Snorkel and our academic partners. This role is highly cross-functional, sitting between Research, GTM and Operations. As a founding member for this role, you will be in charge of setting up the frameworks to build the roadmap, gather data from relevant sources, and share the roadmap with both internal and external stakeholders. What You'll Do Own the "data as a product" roadmap for Snorkel's Agentic and RL Environment focus areas, working x-functionally with research, academic partners, and GTM to define the skills and capabilities for our datasets Shape new "data" product areas and work with academic partners and research leaders to build Snorkel's competitive edge in the market Collaborate cross-functionally to help shape the roadmap and data strategy and influence bu

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

Scale’s Generative AI business unit is experiencing historic growth. As the Community Manager, you will spearhead initiatives connecting hundreds of thousands of expert contributors on our platform. This is a strategic operational role requiring the execution of an operator, program manager, and creative writer. You’ll need an entrepreneurial mindset, operational rigor, and the ability to communicate effectively with diverse stakeholders across internal and external community channels. Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Our Generative AI unit partners with the world's most advanced research teams to improve their models with human data. You will ensure that our global network of contributors stay engaged and informed so that they can do their best work. You will manage communications, execute virtual campaigns and events, and develop strategies to grow and retain our contributor base. This pivotal role shapes community culture, facilitates a thoughtful contributor experience, and harnesses the energy of our community in order to achieve high-level business goals. You must employ creative problem-solving to resolve complex operational challenges and manage the communications cadence across diverse stakeholders. In this role you will: Create strategies to increase participation and satisfaction, overseeing external platforms like Reddit and managing our internal Outlier Community Develop systems to efficiently channel questions, feedback, and disputes across our platforms and social channels Lead with vision: Set direction for multi-team areas and inspire clarity and alignment Organize virtual events to foster connection and monitor community sentiment in order to proactively mitigate risk and address concerns Leverage user feedback, insights, and quantitative metrics to drive improvement in product and operational strategies Enable the team: Instill ownership, drive cross-team collaboration, and remove structur

Head of Enterprise GTM Strategy & Operations Reports to VP, Enterprise Sales · SF or NY Reporting to the VP of Enterprise Sales, this role owns both halves of Scale AI’s enterprise revenue engine: the strategy that determines where we play and how we win, and the operating system - people, process, and systems - that makes that strategy executable, measurable, and repeatable. On the strategy side, you set the analytical foundation for enterprise growth: segment and account prioritization, coverage and territory design, pricing and packaging inputs, and the diagnostic work that explains why the funnel behaves the way it does. On the operations side, you own the RevOps stack, forecasting, compensation design, sales enablement, and the operating cadences that convert strategy into predictable quarterly execution. The ideal candidate is equally comfortable building a segmentation model from a blank page and running a Monday morning pipeline review. You will lead an established team, with the Head of Sales Enablement and the RevOps Manager as direct reports. Your first job is to raise the ceiling on what that team delivers: sharper analysis, tighter operating rhythm, and enablement that measurably shortens ramp and lifts win rates. This is a senior, highly visible role partnering with Enterprise Sales leadership, Finance, Marketing, Product, and Solutions Engineering, with regular exposure to the executive team and board materials. STRATEGY Define which segments, industries, and accounts Scale prioritizes, and build the analytical case behind those choices Build and maintain the market sizing, segmentation, and account-tiering models that drive coverage decisions and investment trade-offs Lead hypothesis-driven analyses of the enterprise funnel - win/loss patterns, conversion drivers, deal economics, coverage gaps - and translate findings into specific changes to how we sell Partner with Finance and Product on pricing, packaging, and deal-structure strateg

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Location: San Francisco, CA (hybrid) What is Verse? The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI. At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy. The Role We're looking for a highly analytical Senior Business Operations Analyst to support the growth and execution of our Dispatch Intelligence product. This role sits at the intersection of business operations, customer, product, engineering, and data science and has two core areas of responsibility. First, you will help drive overall program execution for Dispatch Intelligence: bringing structure to complex cross-functional initiatives, improving processes, tracking progress, and ensuring teams stay aligned on priorities and timelines. Second, you will help build and operate the processes through which flexible energy assets are onboarded onto the Verse platform and continuously improve their operational performance. The ideal candidate combines strong analytical problem-solving with exceptional project management and is comfortable working across both technical and commercial teams. You will play a critical role in helping Verse scale Dispatch Intelligence from individual projects and assets

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 Developer Experience (DX) team at Amplitude builds and maintains the foundations that power how developers integrate, extend, and trust Amplitude across platforms. Our mission is to make Amplitude’s SDKs reliable, easy to adopt, and a joy to build on, so customers can confidently instrument their products and unlock insights at scale. We’re looking for a Staff Software Engineer, iOS to play a key technical leadership role on our DevEx team. In this role, you will lead the design and development of Amplitude’s core iOS SDKs, including Analytics and Session Replay , and serve as the iOS platform expert that other SDK teams, such as Statsig, Guides, and Surveys rely on. As a Staff Engineer, you’ll operate with a wide scope and high impact: setting technical direction for the iOS platform, driving cross-SDK architecture, improving performance and reliabilit

(Sr.) Revenue Accounting Manager Sigma Computing is seeking a Senior Revenue Manager to join our Revenue team and play a key role in managing revenue accounting and revenue operations in a fast-growing SaaS environment. Reporting to the Senior Director of Revenue, this role will own key aspects of the revenue close, revenue recognition, contract review, and related processes. The Senior Revenue Manager will serve as a subject-matter expert on revenue accounting, partnering closely with Sales, Deal Desk, Legal, FP&A, and Finance to assess complex customer arrangements, ensure appropriate revenue treatment, and build scalable processes and controls. Key Responsibilities Own key components of the monthly, quarterly, and annual revenue close, including revenue recognition, deferred revenue, unbilled revenue, and related reconciliations. Ensure compliance with ASC 606 and applicable accounting standards. Review customer contracts and non-standard arrangements to determine appropriate revenue recognition. Partner with Sales, Deal Desk, Legal, FP&A, and Finance to assess the accounting implications of new products, pricing structures, and complex deals. Review and approve revenue-related journal entries, reconciliations, and supporting schedules. Develop, maintain, and improve revenue accounting policies, procedures, and internal controls. Own accurate and timely billing operations, including review and validation of sales tax applied to customer invoices. Own sales tax compliance processes, including periodic reviews of nexus, taxability, and potential exposure across applicable jurisdictions. Support internal and external audits, including preparation of revenue-related schedules and documentation. Identify opportunities to streamline, automate, and scale revenue processes. Partner with Finance Systems and other stakeholders on revenue system enhancements and process improvements. Support the implementation and optimization of revenue-related