Quality Inspector Jobs

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

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

At Scale, we are developing the data infrastructure that powers reliable AI systems in the physical world. The Industrial Partnerships team is a critical function for scaling high-quality data collection through a global network of external partners, expanding our capacity and geographic reach. Joining this team offers a unique opportunity to build complex operations and lead cross-functional coordination to launch new partners and transform that network into a world-class operational engine. These roles are responsible for identifying and signing new partner businesses, and coordinating day-to-day operations with existing partners, including performance tracking and ongoing support. You will: Identify and engage prospective partner businesses and manage the process through to signed agreement Coordinate day-to-day operations with signed partners including onboarding and ongoing support Track partner performance and data collection targets Support hardware deployment and basic troubleshooting on partner premises Communicate regularly with internal teams (product, strategy) and partner contacts Help identify and implement process improvements based on operational feedback Ideally you'd have: Strong professional communication skills in both Spanish and English. Bachelor’s degree in Business Administration, Economics, Logistics, Industrial Engineering, or related fields (open to both technical and non-technical degrees). Industry experience (+2) in physical/on-site operations, logistics, business development, account management or analytics. Experience in the field: warehouses, factories, logistics centers. Analytical, strategic, and process improvement capability. Nice to haves: SQL Proficiency Experience working with CRM systems T his role involves both on-site presence for coordinating operations as well as visiting partner sites on a daily basis. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same

Scale's mission is to develop reliable AI systems for the world's most important decisions. We provide the high-quality data that powers the world's AI models, and we help enterprises and governments build, deploy, and oversee AI applications that create real impact. As Communications Manager, Corporate and Product, you will help shape how Scale shows up when it comes to our work building enterprise AI, spanning company narrative, product launches, partner communications, media presence, and executive visibility. This role is centered on translating complex enterprise AI deployments and partnerships into clear, compelling narratives that resonate with business and vertical industry audiences. A core focus of the role is pitching and positioning Scale's enterprise wins, product launches, and customer partnerships, including how organizations across industries are using Scale's Generative AI Platform to build, deploy, and oversee AI applications that create real impact. You will also work closely with communications counterparts at partner companies to align messaging and coordinate joint announcements. You will help tell the story of how Scale's enterprise business powers mission-critical AI programs for the world's most consequential organizations, from Fortune 500 companies to leaders across every major industry. In this role, you will partner closely with enterprise product leaders and go-to-market teams, as well as teams across communications, social, and marketing. You will play a key role in strengthening Scale's reputation with enterprise customers, industry analysts, and the broader technology ecosystem. This position reports directly to the Head of Corporate & Product Communications. You Will Support corporate and product communications initiatives with a strong emphasis on Scale's enterprise business, including customer and partnership announcements, product launches, executive visibility, and industry positioning. Help translate co

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

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

Role Summary The Support Enablement Manager builds and scales the training, onboarding, and quality-assurance programs that power a high-performing contributor-support team. The role owns the full enablement lifecycle — from designing and delivering onboarding curricula to formalizing QA frameworks that drive measurable improvement across the support organization. Enablement priorities are set in partnership with the Regional Manager; the Manager owns execution end to end within that scope and brings recommendations when scope needs to change. This is a hands-on leadership role: assess the landscape, prioritize, build the plan, lead a small team, and deliver results, working cross-functionally with Regional Managers, Team Managers, SMEs, and WFM. Key Responsibilities Own the enablement function end to end — assess gaps, prioritize initiatives, and drive them to completion within scope agreed with the Regional Manager; surface recommendations when scope should change. Onboarding & curriculum — own the end-to-end onboarding for new Support Specialists; design, build, and continuously improve structured training that reflects current workflows, tools, and contributor-experience standards, so agents ramp quickly and confidently. Coaching & development — build and maintain ongoing training across all tiers; partner with Team Managers to close skill gaps with targeted interventions that translate into performance improvement. Quality assurance — own the QA program: scorecard design, calibration, audits, and reporting; keep QA consistent, fair, and actionable, and require that quality feedback cite a current source document. Knowledge base / SSOT — own the support knowledge base and its review cadence so guides stay accurate and current, and retire stale content. Team leadership — lead, develop, and manage a small team of Enablement & QA Specialists; set priorities, coach, and keep the team unblocked and accountable to high-quality output. Cross-functional part

As a member of our Frontier Tech Consultant team, you will play a critical role in advancing cutting-edge AI innovations by conducting high-impact experiments and ensuring seamless execution at the highest quality standards. Your work will directly contribute to Scale AI’s growth, shaping the future of artificial intelligence. In this role, you will be working on various types of projects, including but not limited to: research experiments, dataset generation, data quality improvements, and in-depth technical analysis. You will tackle complex, technical and operational challenges while collaborating closely with Scale’s ML research scientists and SPM team. The ideal candidate is analytical, detail-oriented, and results-driven, with strong problem-solving abilities and excellent communication skills. We are looking for someone who thrives in a fast-paced environment, is proactive in overcoming challenges, and is committed to delivering exceptional outcomes. If you are eager to contribute to the forefront of AI innovation, we encourage you to apply. You will be responsible for: Design and execute research experiments Build and evaluate frontier LLM datasets Develop training and testing material for frontier pipelines Improve quality of existing and new products Ideally you’d have: Strong machine learning knowledge, either by being in the final years of a ML PhD career or having already graduated Strong writing and verbal communication skills An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results Analytical, planning, and process improvement capability Experience working in a fast-paced, entrepreneurial environment Technical skills including familiarity with Python, GPU, AWS, API, LLM, ML, and SQL Pay: $60-80/hr Commitment: This is a fully remote, US-based part-time (10-20 hours per week), on-going contract position staffed via HireArt. HireArt values diversity and is an Equal Opportunity E

About Scale AI Scale's rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing governments around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As these applications move from prototype to production, we're investing heavily in the infrastructure and people that keep them reliable, secure, and trusted by our government partners. At Scale, we're not just building AI solutions - we're enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you're ready to shape the future of AI in the public sector and be a founding member of our team, we'd love to hear from you. Role Overview We are looking for a technically strong and customer-oriented Engineering Manager to lead the development of AI applications for Saudi government clients. This role sits at the intersection of engineering leadership, AI/ML delivery, and direct client engagement—requiring someone who is equally comfortable presenting to a government stakeholder as they are reviewing a system architecture or shipping code. As a founding member of our regional team, you will help define how Scale AI shows up for some of the most ambitious public sector AI initiatives in the Gulf. If you thrive in fast-paced, high-impact environments and want to shape the future of AI in government, we would love to hear from you. What You'll Do Lead and manage a team of engineers delivering AI-powered applications for KSA government clients, ensuring high-quality output and on-time delivery Serve as the primary technical point of contact for KSA government stakeholders—translating complex engineering concepts into clear, accessible language for non-technical audiences Design, build, and optimize full stack AI applications end-to-end, fro

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for custom LLMs Upskilling and advisory services to spread the impact of AI As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Partner with public sector clients to scope, collect feedback and implement solutions for complex problems, including spending up to two weeks per month in client offices for feedback and delivery. Architect production-grade applications that integrate AI models with full-stack frameworks, managing everything from interactive UIs to backend APIs and systems. Deploy and manage infrastructure within cloud environments, ensuring the highest levels of system integrity, security, scalability, and long-term reliability. Contribute to core platform features designed to be reused across diverse international client use cases. Partner with design, product, and data teams to build robust applications aligned with the broader technical architecture. Ideally you’d have: Bachelor’s degree in Computer Science or a related quantitative field 5+ years of post-graduation, full-stack engineering experience with demonstrated proficiency in React (required), TypeScript, Next.js, Python, Node.js, PostgreSQL or MongoDB plus hands-on experience with Docker, Kubernetes, and Azure

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Requirements A graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Available for a Summer 2027 internship (May/June start dates) in San Franci

About the Team DashMart is a local-fulfillment center owned and operated by DoorDash, offering customers household essentials and other items to their doorsteps with speed, reliability, and quality. Customers order their convenience, grocery, retail, and prepared foods in the DoorDash app, and our team members fulfill orders in a real, brick-and-mortar store, for Dashers to deliver. We’re open early and close late - some sites even run 24/7! Shifts: Morning, Day, Evening, Weekend, Part-Time About Part-Time Variable Schedule Roles at DashMart As a Variable Schedule Operations Associate , instead of a fixed weekly schedule, you largely pick up open shifts through our scheduling app. Shifts may open ahead of time or pop up at the last minute based on business needs. Schedules with available openings are posted weekly, and additional shifts may appear through shift swaps or peaks in demand. You will be expected to work at least one shift every four weeks for a minimum of four hours each shift. Variable Schedule Operations Associates will be scheduled for one shift a month to help meet this requirement. This will also be a key time to review any relevant changes in processes and company-provided tooling, and stay connected with the Site Leadership Team, including your supervisor. Reliability and communication are key — when you pick up a shift, we count on you to show up on time and complete each shift, while meeting performance expectations. You’ll start with DashMart onboarding and initial training ( one shift ) and complete one 4-hour on-the-job training shift (must be completed within 14 days) to set you up for success, then you can begin choosing shifts based on business needs and your schedule. About the Role Picking and Packing orders. Pick orders that come through the app, pack the order and hand it off to Dashers. Inventory and Spoilage Management. Stock receivables and manage inventory, including shelf life. Warehouse Organization. Clean and o

Opportunity Overview: We’re looking for a Manager, Platform Engineering that can lead and grow a high-performing engineering team focused on Developer Experience, DevOps, SRE, and Quality. You will own the systems and processes that enable teams to build, test, release, and operate software with high velocity and reliability, driving engineering efficiency and operational excellence across the organization. What you’ll do: Lead a fast-paced, autonomous team of engineers focused on platform engineering, developer experience, DevOps, SRE, and quality engineering Own and drive the internal developer platform strategy and roadmap, improving how engineering teams build, test, deploy, and operate services Create transparency into engineering efficiency and system health through meaningful metrics across delivery, reliability, and quality Enable teams to move faster by improving CI CD pipelines, environments, tooling, and overall developer workflows Provide technical leadership across platform, infrastructure, and reliability, helping teams build scalable and resilient systems Ensure strong engineering practices across release processes, testing, quality, reliability, and security Define and enforce release guardrails, validation standards, and rollback mechanisms to improve production safety Improve environment stability and consistency across development, QA, and pre production environments Drive test strategy and automation maturity to improve overall product quality and confidence in releases Define and implement observability, monitoring, and alerting standards across systems Improve incident detection, response, and RCA practices, ensuring learnings translate into platform and system improvements Drive cloud infrastructure best practices across AWS, containers, and infrastructure as code Foster a culture of ownership, reliability, and continuous improvement within the team Provide innovative solutions for attracting, developing, and retaining top engineering talent I

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew

Opportunity Overview: We are seeking a Technical, Hands-on Manager to lead a team responsible for building and maintaining high-quality healthcare market datasets and analytics that power internal insights, benchmarking, and external thought leadership . In this role, you will lead a team of data analysts responsible for the development, quality assurance, and ongoing refresh of market data assets. You will combine strong people leadership with technical expertise in analytics and data science to ensure reliable, scalable data pipelines and actionable insights. The ideal candidate is both a strong people manager and a hands-on analytics leader who can guide analysts in rigorous data methodology, translate data outputs into meaningful business insights, and partner closely with commercial strategy, product, clinical, and analytics stakeholders. What you’ll do: Lead and develop a team of data analysts responsible for the creation, validation, and ongoing refresh of healthcare market datasets. Mentor analysts in data methodology, statistical reasoning, and reproducible analytics practices to ensure consistent and rigorous analysis across the team. Establish analytic standards, coding practices, and documentation expectations to ensure all datasets and insights produced by the team are reproducible and scalable. Establish and maintain governance processes for market data including versioning, documentation, auditability, and traceability of data sources and methodologies. Oversee change-detection logic, ensuring the team systematically identifies and documents additions, removals, and shifts in the market dataset. Define and enforce data quality standards across ingestion, transformation, and analysis workflows. Collaborate with Data Engineering and Platform teams to ensure the underlying data infrastructure supports scalable ingestion, transformation, and analytics workflows used by the analyst team. Translate analytic outputs into business insights, benchmarks, and st