Systems Integration Manager Consumer Devices in San Francisco

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,

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

About the Team The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering’s evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers. About the Role The Storage team is building and operating a high-performance, scalable, and reliable data abstraction layer that optimizes both efficiency and reliability. Our goal is to create a platform that manages itself and fades into the background—empowering engineers to focus on delivering product experiences our customers love. This role is available across two teams within Storage, each solving unique and high-impact challenges: One team is building the orchestration layer for DoorDash’s storage platform—unifying lifecycle management, operations, and self-serve APIs for databases and streaming systems, turning complex, stateful infrastructure into reliable, developer-friendly services used across the company. One team builds and operates the distributed data platform powering DoorDash's largest stateful workloads -- including Cassandra, which backs critical product surfaces across DoorDash, Wolt, and Roo. You'll design high-throughput data abstractions, smart clients, and platform services that make distributed data reliable and easy to work with at multi-petabyte, multi-million-QPS scale, with opportunities to go deep on distributed systems internals and contribute to the open-source Cassandra ecosystem. If you're passionate about distributed systems, developer experience, and building foundational infrastructure at scale, we'd love to hear from you. You must be located in San Francisco, Sunnyvale, Seattle, or the New York Metro Area for this hybrid pos

At Scale, we develop reliable AI systems for the world’s most important decisions. Scale’s product marketing team is responsible for developing and executing strategies that drive awareness and engagement for Scale’s offerings amongst our core audiences. We take a data-driven approach to understand our customers’ needs and challenges, ensuring that their voices are reflected in product development and messaging. We partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. We aim to provide valuable insights and resources that help our customers execute on their AI transformation journey. This role will focus on developing and optimizing vertical-specific messaging and content for Scale’s applications business to ensure our messaging resonates with core buyers across verticals. The ideal candidate combines strategic thinking with hands-on execution. You will: Develop clear, compelling messaging for enterprise offerings tailored to key personas within target verticals Create marketing assets, including slide decks, videos, blog posts, and one-pagers, that effectively communicate our value propositions to vertical leaders and support our sales team’s pursuits Lead positioning and sales enablement efforts to drive awareness and engagement for Scale’s offerings. Drive cross-functional marketing programs around target verticals, in conjunction with product, engineering, sales, and growth marketing to create a cohesive customer experience and contribute to pipeline targets Collaborate with field marketing and events teams to develop vertical-specific event strategies, content, and experiences that drive engagement within customer and target accounts Drive customer marketing efforts, creating both strategy and tactics to maximize the value Scale and customers get from our shared success, including case studies, testimonials, visual assets and event particip

About the Team The Storage organization builds and operates the online stateful systems and abstractions that DoorDash Engineering depends on: reliable, efficient, secure, and easy to use. Within Storage, the Distributed Caching team owns every caching offering at DoorDash end to end, including ElastiCache (Redis/Valkey), Boulder (our KVRocks-based key-value store for high-QPS feature serving), Entity Cache (read Bill Shen’s engineering blog post, “ High-Performance Proxy Cache for DoorDash Services ”), and the Distributed Lock Service, plus the smart clients (asgard-redis, valkey-go) that sit in front of them. These systems back critical product surfaces across DoorDash, Wolt, and Deliveroo: the team runs roughly 400 ElastiCache clusters serving hundreds of millions of GET requests per second in aggregate, and Boulder, our offline-to-online feature store, serves billions of feature lookups per second at peak. About the Role The team owns provisioning of clusters and the smart clients that sit in front of them, baking in sensible defaults so that other engineering teams get a turnkey caching solution instead of having to run their own. You'll help drive Boulder's evolution to scale further, improve cost efficiency, enhance performance, and support real-time updates; re-platform the Distributed Lock Service onto a strongly consistent backend; and build the self-serve tooling and recommendation engine that let customers describe a workload (QPS, TTL, payload size, latency profile) and get the right backend without talking to a human. You'll go deep on cache invalidation, replication, sharding, compaction, and failover, while shipping the guardrails, automation, and observability that keep this scale operable by a small team. You must be located in San Francisco, Seattle, or the New York Metro Area for this hybrid position. You will report to the Engineering Manager on the Distributed Caching team within the Storage organization. You’re excited about this opportunity b

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! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other

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. Public Sector engineers build the core product including the systems required to ingest and process federal datasets that support real-time decision-making in contested environments. As a New Grad Software Engineer on this team, you will own meaningful, mission-facing work from day one: shipping features, sitting with the government stakeholders who use them, and iterating fast. Example Projects Build multi-layered guardrails that keep agents safe and predictable in high-stakes federal environments Optimize data retrieval for agents, including RAG pipelines over large, heterogeneous federal datasets Build orchestration for fleets of asynchronous agents running long-horizon tasks Develop systems that automatically alert users to deviations and anomalies in incoming data Create interfaces that illustrate how an agent reached a decision, so operators can audit and trust its output Develop data pipelines and ML infrastructure that make previously siloed government data sources accessible to agents Build evaluation infrastructure that measures model reliability against mission requirements Ship full-stack tooling that lets analysts query, visualize, and explore mission data Deploy and harden applications into secure, air-gapped, and cloud-native government environments Requirements A graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Product engineering expe

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About the Role We are seeking an experienced IT Engineer to own and enhance the technology experience within HP IQ. This role combines traditional IT operations, SaaS administration, endpoint management, and infrastructure support with a strong focus on automation, scalability, and employee experience. The ideal candidate is a hands-on problem solver who thrives in fast-paced startup environments, takes ownership of systems and processes, and proactively identifies opportunities to improve tooling, security, and operational efficiency. You will serve as a technical escalation point for the IT Support team while helping shape the future of our internal technology stack. What you might do Manage and administer core business platforms including Google Workspace, Microsoft 365, Okta, Slack, and other SaaS applications. Ensure employees have a seamless and productive technology experience across all systems and devices. Evaluate, implement, and optimize tools and workflows that improve employee productivity and reduce operational friction. Develop and maintain IT documentation, standards, processes, and

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, 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 The Code Quality team sits within the Developer Platform organization and owns the systems that keep DoorDash's codebase healthy and secure as it scales: static analysis, quality gates, test frameworks, regression infrastructure, and tooling. Our job is to make sure the signals engineers rely on before shipping — test results, coverage, performance feedback etc — are fast and trustworthy. The decisions we make about tooling and standards directly shape how confidently and quickly engineering teams at DoorDash can ship to production. About the Role We're looking for Software Engineers to help build and maintain the systems that validate code quality across DoorDash's engineering org, treating our tooling as a critical product for the engineers who rely on it every day: static analysis and quality gates, test frameworks and regression infrastructure. You’ll design the tooling and automation that will help derive trustworthy quality signals, integrate them into the development lifecycle, and make it easy for engineers to execute reliable, repeatable workflows. You will collaborate across the engineering org, partnering directly with the teams who use what you build to understand the accuracy, reliability and performance of their functionality. You will report into the Engineering Manager on our Code Quality team in our Developer Platform organization. You must be located in either San Francisco, CA, Sunnyvale, CA, Los Angeles, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Build and maintain quality tooling — static analysis, quality gates, coverage reporting, test frameworks, regression infrastructure — and integrate it directly into our developer workflows and CI/CD pipelines Define and derive quality signals - flakiness, pass rate, coverage, performance, scale readiness etc - Build tooling that improves everyday engineering workflows, including local development, CI/CD, debugging, and rollou

About the Team DoorDash Labs, established in 2018, serves as the innovation hub for DoorDash, focusing on developing automation and robotics solutions to enhance last-mile logistics. The team's mission is to create technologies that support and augment human networks, aiming to improve efficiency for Dashers, merchants, and consumers alike. We’re ruthlessly focused on business impact. We are a highly senior team composed of former pioneers from a variety of different robotics industries. As of 2025, DoorDash has completed 10B lifetime deliveries. We’re focused on how to do the next 10B even better. About the Role We are seeking a highly motivated Senior Reliability & Test Engineer to join our team. This individual will play a key role in the development and validation of our unmanned platforms at the system and component levels. You will partner closely with EE, ME, and Autonomy teams to translate mission needs into robust, reliable hardware. The ideal candidate thrives in a fast-moving, cross-functional environment where reliability and test rigor determine program success. You will be hands-on in developing test methods and equipment to uncover failures before they happen in the field. You will partner closely with EE, ME, and Autonomy teams to translate mission needs into robust, reliable hardware. The ideal candidate thrives in a fast-moving, cross-functional environment where reliability and test rigor determine program success. You’re excited about this opportunity because you will… Architect and implement rigorous validation strategies, utilizing Python scripts for automation while leveraging CAD and shop tools to engineer bespoke test fixtures and hardware rigs. Oversee experimental execution across internal facilities and external laboratories, maintaining technical mastery over vibration tables, environmental chambers, DAQ systems, and ingress protection testing. Translate high-level vehicle reliability requirements into granula

Technical Support Manager About the role: We are looking for a technically skilled, self-motivated, customer-focused manager to lead a team of high energy Support Engineers. In this role you will be responsible for hiring, developing and mentoring team members as well as delivering against key performance metrics. You'll lead process improvements for customer and partner growth, retention, and excellence, while fostering individual contributions and driving cross-functional projects that spark innovation and collaboration. You need to be comfortable working in a fast paced environment and continuously challenge the team to step outside their comfort zone. Minimum Education Requirement This position requires a U.S. Bachelor's degree (or foreign equivalent) in Computer Science, Software Engineering, Information Systems, Data Science, or a closely related technical field. This requirement is a minimum and cannot be substituted by work experience alone. What You Will Be Doing Become a product expert and stay technically close to complex and critical customer escalations. Lead a team of exceptional product experts providing the Sigma user base with an excellent customer experience. Hire, develop and train a strong team of Support Engineers on an ongoing basis. Own strategic areas of the Support organization end to end, from strategy through measurable outcomes. Partner across Engineering, Product, Customer Success, Sales, and Marketing to solve customer challenges and drive cross-functional outcomes. Drive performance against key Support metrics, including CSAT, Initial Response, SLA, and Time to Resolution. Continuously refine processes to optimize efficiency, elevating customer support operations. Uncover golden insights within Support data, translating them into actionable strategies that improve customer experience, operational efficiency, and business outcomes. Develop a reputation for excellence, high credibility and integrity with

Sigma is growing rapidly, and our Technical Support Engineering team is scaling alongside it to meet the needs of an expanding global user base. As a Technical Support Engineer at Sigma, you will be part of an award-winning team recognized with the 2024 Stevie Gold Award for Customer Service, helping customers solve technical, business, and data challenges using the Sigma platform. You'll work closely with Product, Engineering, and Go-to-Market teams to diagnose complex issues, drive solutions, and contribute to the continuous improvement of our product and support operations. Minimum Education Requirement This position requires a U.S. Bachelor's degree (or foreign equivalent) in Computer Science, Software Engineering, Information Systems, Data Science, or a closely related technical field. This requirement is a minimum and cannot be substituted by work experience alone. What You Will Be Doing You will work with Sigma's customers and the pre-sales team to assist with the diagnosis and resolution of complex technical issues. Working closely with the development team, you will develop best practices and tools for diagnosing issues and optimizing the service for performance. Collaborate with cross-functional groups — backend, frontend, DevOps, design, product, and the go-to-market teams to create a first-class experience for users of our product. Participate in quarterly projects and perform periodic on-call duties to improve automation and processes. Qualifications We Are Looking For 2+ years of experience in a customer-facing technical role (Technical Support, Solutions Engineering, or Software Engineering) at a cloud or SaaS provider. SQL proficiency — strong grasp of JOINs, Partitions, Window Functions, Aggregations, CTEs, and sub-queries. SQL query performance troubleshooting and query plan analysis. Proficient in data modeling concepts. Ability to chart data into logical visualizations. A proven track record of building trust with customers and brin

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an