Engineering Lead Analyst Jobs

As a member of our operations team, you will be accountable for driving revenue by ensuring that Scale AI meets customer commitments in a timely manner while maintaining the highest quality standards. You will manage our supply operation funnel by building and running solutions, tools, and processes by working with a cross-functional team including Customer Operations, Product Operations, Product Managers, and many others. You will be solving problems no one has solved before, and you will need to be relentless in driving stellar results, running pilots, tests, and experiments. You’ll come up with creative solutions to bottlenecks. The blend of operations and ownership of our most important outcomes make this a unique and exciting role at the heart of Scale’s daily operations.The ideal candidate is scrappy, analytical, empathetic, outcome focused, and above all someone who drives and inspires results. You will: Build and drive some of our most critical operational processes Own the day-to-day delivery of customer commitments Create an effective feedback loop between the front line, product, strategy, and customers Collaborate with stakeholders to improve processes for new and existing customers Ideally you'd have: Advanced English skills Industry experience (+2) in an operational role and/or a top-tier consulting firm An undergraduate degree with an analytics heavy major (e.g., Engineering or Economics) and/or a graduate degree in Engineering, Economics, or Business An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results Analytical, planning, and process improvement capability Experience with reading SQL, or have demonstrated analytical skills PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems

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. 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

About Eudia Eudia is a high-growth AI startup on a mission to transform legal work through Augmented Intelligence—pairing advanced AI with human expertise to supercharge legal teams. Our platform helps Fortune 500 corporate legal departments move faster, manage risk, and transform the legal function from a cost center into a strategic advantage. Eudia is trusted by some of the world’s most demanding organizations, including Cargill, ServiceNow, DHL, Bayer, Duracell, Dolby, Indeed, OpenAI, the U.S. Air Force, Best Buy, Asana, Dropbox, LinkedIn, Citi, Etsy, Novelis, Pure Storage, Del Monte, Cox, PetSmart, Udemy, and many more across regulated and high-stakes industries. Backed by General Catalyst (Hemant Taneja, Marc Bhargava), Floodgate (Mike Maples), Sierra Ventures (Tim Guleri), and leading individual investors including Gokul Rajaram and Prof. Chris Ré (Stanford), Eudia is building deeply technical AI platforms for risk-sensitive environments where accuracy, security, and trust are non-negotiable. We believe the future of legal work lies in AI augmenting human expertise, not replacing it, and we are assembling a world-class team to make that future a reality. About the Role We are looking for a Product Manager to own the end-to-end user experience of Eudia’s core application. This role defines how corporate legal teams interact with AI across workflows such as contract review, diligence, compliance analysis, and advisory research. You will translate powerful AI capabilities into intuitive, trustworthy, and scalable application experiences that align with how legal professionals work. This is a senior role with full ownership of application-layer strategy, workflow design, and enterprise adoption, working closely with AI, platform, design, engineering, and customer teams. What You’ll Own End-to-end product strate

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 Manager, 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, demo

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. Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API. This role is hybrid , based in Cyprus. 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 Bring up, run, and debug modern ML models (e.g., transformers) using PyTorch or TensorFlow. Analyze model behavior and performance, and identify bottlenecks across the stack. Improve efficiency, correctness, and scalability of model execution in real systems. Work closely with compiler, kernel, and hardware teams to drive performance and system-level improvements. Help translate state-of-the-art model architectures into production-grade, high-performance deployments. What We Need Strong experience building and working with ML models in PyTorch or TensorFlow. Strong understanding of mod

About Graphcore At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence. Job Summary As a research engineer at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this exciting field. We are therefore looking for individuals who combine strong machine learning experience with practical engineering skills to deliver impactful AI research. We are seeking AI researchers with strong software engineering experience, particularly in lower-level programming and performance optimisation for hardware efficiency. Our research spans a broad range of topics, including efficient training and inference, world models, life sciences, reinforcement learning, and beyond. You will work closely with researchers to generate ideas and translate them into scalable implementations, contributing to publications and projects that help to steer the future of AI hardware. The Team Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence a

About Graphcore At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence . Job Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems The Team The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible. Responsibilities and Duties Develop, own, and maintain tools and services to support AI research and engineering teams Deploy and maintain services with Kubernetes and Docker Manage our Cloud Infrastructure using tools such as Terraform Candidate Profile Essential:

About Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Summary Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed system The Team The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible. Responsibilities and Duties Develop, own, and maintain tools and services to support the software org