Engineering Standards Manager Jobs

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 ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. 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 across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of 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 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: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/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, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

Come join our legal team to work on the most exciting legal, policy, and operational issues at the leading edge of AI. We're seeking strong product lawyers with specialized expertise in intellectual property law. As product counsel, you will advise on all legal aspects of product development, launch, and operations - including regulatory compliance, user terms, and risk management - while bringing deep expertise in your specialized legal area. The ideal candidate will have deep subject matter expertise in intellectual property law, a technology background, and a demonstrable history of providing practical product counsel to solve complex, time-sensitive problems in close partnership with cross-functional teams. This role reoprts to the Associate General Counsel, IP & Product. You will: Strategic Product Advice: Lead IP strategy for product development, embedding IP protection into the full product lifecycle from conception to commercialization, while also advising on related product and regulatory matters in collaboration with the broader legal team. Cross-Functional Collaboration: Partner with Research, Product, Engineering, Operations, Communications, and Marketing teams to mitigate IP risks in product development, data licensing, and open-source governance. IP Counsel: Support management of Scale's worldwide IP portfolio including patents and trademarks; assist with patent prosecution and trademark registration and enforcement. Risk Mitigation: Advise on third-party, synthetic, and open-source data and models, ensuring compliance with licensing requirements; design open-source governance policies. Agreements: Support drafting and negotiation of commercial agreement provisions involving intellectual property. Specialized Expertise: Provide counsel on machine learning, robotics, and other technical areas, with ability to engage effectively with technical teams on complex engineering and product issues. Training: Develop and deliver IP and data licensing trainin

Scale AI sits at the forefront of enabling machine learning for advanced robotics systems. As an Operations Program Manager focused on data creation for robotics models, you will design and execute the solutions, tools, and processes that power high-quality training data at scale. You’ll ensure precise, timely delivery of datasets that drive perception, manipulation, and autonomous decision-making in robotic platforms. With rapid growth, new customer onboarding, and continual product innovation, we face both strategic questions and hands-on operational challenges—your contributions will be key to solving them. You will be part of a highly motivated team of operators and collaborators who will ensure steady delivery and customer satisfaction. You are relentless in driving stellar results, running pilots, tests, and experiments, then handing over new designs to a team of skilled operators. The blend of operations, process improvement, and cross-functional leadership make this a unique and exciting role that will provide an opportunity to work with multiple teams (e.g., Engineering, Marketing, Operations, Analytics, and several others) across the company and around the globe. You will: Drive some of our most critical operational processes Improve existing processes and tools globally Collaborate with stakeholders to improve processes for new and existing customers Create an effective feedback loop between the frontline, product, strategy, and customers Build, maintain, and regularly communicate detailed reporting for other leaders across the company who will use your team's data to inform their own operations and strategy Ideally you'd have: Industry experience in supply chain, finance planning, in an operational role and/or in a top tier consulting firm An undergraduate degree from a top university in an analytics heavy major (e.g., Engineering or Economics) and/or a graduate degree from a top university in Engineering, Economics, or Business Experience leading day to

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

About the team: Scale is growing rapidly, and joining the Global Public Sector team is an opportunity to work on one of the most rapidly expanding teams at Scale. This team is responsible for generating, executing, and fostering Scale’s work outside of the United States. There are three core types of work involved: Building custom AI applications for government Providing high-quality training data for research institutions building LLMs from scratch Partnerships, upskilling, and advisory About the role: As the Engagement Manager, you will be responsible for establishing deep customer and prospect relationships, proactively identifying opportunities where Scale can build custom AI applications to improve lives for citizens and residents, overseeing the execution to ensure timelines are met and/or communicated effectively, interfacing with premier research institutions to discuss how Scale can best support them, and partnering with organizations who are looking to train and educate people on how to use AI, AI safety, and more. You and your team will work closely with the business development and go-to-market team, the product and engineering execution teams, and various customers and prospects to ensure success. The ideal candidate has a nose for value and opportunity, is highly personable and can build relationships with all types of stakeholders, is an excellent communicator, is highly organized, and has a demonstrated track record of high-achievement. They are naturally empathetic and excel at building long-term relationships through diligent problem-solving and thoughtful, strategic discussions. The blend of customer engagement, operations, and business development to drive our most important outcomes makes this a unique and exciting role at the heart of one of Scale's most exciting growth businesses. You will: Drive the process of identifying high-value use cases for custom LLMs that Scale can build within government entities Partner

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 the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

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 Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. 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 foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

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

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 Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. 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 foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Finance vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of financial software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Finance industry, decide what financial tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Finance industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Finance workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real financial work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do Own the Finance AI roadmap & data strategy: Set product direction for the Finance agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Finance industry (including investment banking, private equity, public markets, corporate finance, FP&A, etc), driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Finance agentic capabilities fall short and shape new product lines and competit

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. At Tenstorrent, we build open, state of the art compute for real workloads and real developers. You will own CPU core-level testbench development and verification, shaping how our out-of-order RISC-V CPUs behave in silicon. This role is hybrid, based out of Austin, TX or Santa Clara, CA. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You bring 8+ years in CPU verification, CPU testbench development, or closely related digital design. You have deep hands-on experience building and owning CPU core-level testbenches, not just using existing environments. You know high-performance out-of-order CPU microarchitecture in depth. You are comfortable developing testbench infrastructure in CVM methodology, with UVM experience as a strong plus. You work comfortably across RTL, waveforms, logs, regressions, and cross-functional debug with design, DV, emulation, and post-silicon teams. You are comfortable using AI-assisted verification workflows to improve debug, stimulus creation, and coverage analysis, while applying strong engineering judgment to validate results. What We Need Lead hands-on CPU core-level testbench development for hi

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building the next generation of AI and RISC-V compute. As a Sr. Staff NPI Global Supply Planner, you will own end-to-end demand, materials, and production planning across our AI hardware product lines, including Blackhole, Galaxy, and future platforms. You will translate engineering release schedules, BOM structures, and production forecasts into executable supply and capacity plans with our contract manufacturers, while keeping planning data accurate and reliable across ERP and PLM systems. This role is hybrid, based out of Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A strategic, detail-oriented supply chain planner who can turn engineering and program ambiguity into clear, executable plans. Experienced in NPI planning within semiconductor, AI hardware, or high-tech manufacturing environments. Comfortable working across BOM structures, engineering change processes, ERP and PLM systems, and system-of-record data. A clear, collaborative communicator who can align engineering, operations, planning teams, and contract manufacturers. What We Need Lead end-to-end materials and production planning across NPI r

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a Director, Strategy & Solutions in our GTM team, this role defines how Tenstorrent shows up in the market for AI/ML workloads—from positioning and messaging to real customer solutions. Sitting at the intersection of product, sales, engineering, and marketing, this role turns deep technical capability into clear, compelling value across industries and use cases. This role is hybrid OR remote, based out of The United States. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced at connecting complex AI/ML systems to real customer outcomes and business value. Comfortable acting as a technical storyteller for developers, architects, and executive audiences. Naturally curious and forward-looking about customer workloads, competitive dynamics, and emerging AI trends. What We Need Ownership of GTM positioning and messaging for Tenstorrent’s AI hardware, software stack, and solutions. Development of application - and vertical-specific value propositions across enterprise, cloud, and regulated markets. Value proposition & GTM strategy, including creation of technical collateral (whitepapers, sales decks, benchmarks, dem