Environmental Control Analyst in San Francisco

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. The next frontier for AI is the physical world. We're looking for an AI Product Manager to own the Robotics vertical within our Physical AI team. In this role, you'll own both the development of the data and training environments (the teleoperated demonstrations, real-world collections, simulated tasks, and annotation products that labs use to train and evaluate robot policies) and the "data as a product" strategy that powers them. You'll understand where physical AI is headed, decide what robot tasks and embodiments are worth collecting, 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 robotics or physical AI research, and is able to pair that domain understanding with a sense for where current robot policies succeed and fail in real-world workflows. You'll translate that expertise into datasets, environments, and evaluation frameworks that teach robots to do real physical 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 Robotics AI roadmap & data strategy: Set product direction for the robotics training stack and the data strategy behind it — what data we collect, on which hardware and embodiments, and what we source internally vs. through our marketplace. Establish a vision for where physical AI is heading, driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading physical AI labs to understand where their robot p

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) 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 position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences 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 fo

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

You will: Source and acquire quality candidates for high volume positions to meet hiring and activation goals Review applications and screen candidates Support candidates throughout the recruiting process Partner with other growth recruiters, ops leads and cross-functional leaders to understand Scale’s business needs, then devise and execute on the recruiting strategy needed to deliver on them. Follow and manage processes that will evolve over time as the company grows. Represent and champion the brand, promoting its value proposition to candidates and driving engagement. Represent Scale at occasional onsite growth recruiting events. Ideally you have: 2+ years of recruiting/sourcing experience in a fast-paced, high-growth environment. Excellent written and verbal communication skills, with the ability to tailor messaging to diverse audiences Experience sourcing candidates and filling high volume roles Experience acting as the primary candidate liaison, delivering white-glove service through timely updates and personalized support throughout the interview process Nice to have: Previous experience in a start-up. Either experience managing a full-cycle recruiting experience, or a passion and ability to learn to do so. Experience with various tools such as Linkedin Recruiter, Clay, Modernloop, Gem Extreme attention to detail AI builder, AI-forward operator, or strong interest in agentic coding and experimenting with AI tooling The hourly salary range for this position is $40 to $55/hr. This is a remote position with occasional travels required for onsite growth recruiting events. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allow

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 AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

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

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

Scale AI is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments. You will: Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure. Own services or systems and define their long-term health goals, while also improving the health of surrounding components. Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product. Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings. Must have: At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance Ideally you'd have: Full Stack Development: Prof

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

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As a Software Engineer at Nextdoor, you’ll work across multiple phases of software development life cycle within a project to design, implement, and maintain the core backend systems that power the Company’s feed infrastructure. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make If you want the challenge of fast-paced growth, the satisfaction of seeing your design work come to life, and the pride in helping grow a world-class design team, this is the place for you. Your responsibilities will include: You’ll actively collaborate with product managers, frontend engineers, data scientists, and other backend engineers to understand the needs of the users and define the technical requirements for new features, improvements, and bug fixes You’ll monitor the performance of the feed infrastructure to identify bottlenecks and resolve issues in a timely manner

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We're hiring a Robotics Infrastructure Engineer in our Autonomy Software team. In this role, you'll own, build, and manage the infrastructure that makes aerial autonomy development possible. You'll work on the onboard systems that keep a drone alive (process management, health monitoring, parameterization) and the development environment that makes the team fast (build systems, CI/CD, logging, debugging, regression testing). This is not cloud infrastructure. This is real-time, fault-tolerant, onboard software for vehicles that cannot gracefully restart at 50 meters altitude. You're excited about this opportunity because you will… Play an integral role on a small and focused team Develop and own critical onboard components: process management, health monitoring, configuration management, and message passing Own the build system (C++, Python) and middleware layer (ROS2), including cross-compilation for Jetson targets Design and maintain CI/CD pipelines and regression testing infrastructure Build and manage the parameterization system, including schema definition, validation, migration, and deployment Build robotics logging, plotting, and debugging tools that make the entire team more productive Work closely with the simulation team to support SIL/HIL development workflows Define reliability standards for onboard software: watchdogs, failover, and graceful degradation We're excited about you because… You have prior experience at a robotics company in a similar infrastructure role You have experience with robotics middleware (ROS2, LCM, eCal, Apex.AI) You have experience with build systems and package managers (CMake, Bazel, Nix, Conan) You have experience with NVidia Jetson and Je

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! About the Role DashMart is looking for a motivated and experienced individual that excels in fast-paced, physical environments and is excited to roll up their sleeves and actively engage in day-to-day operations. In this role, you will work within a local fulfillment center supporting Site Management running great shifts, and delegating tasks. As a Shift Lead, you will have shift responsibility for fulfilling orders in a warehouse environment and maintaining inventory, and in some locations, this involves preparing food in a light-prep kitchen. You’re excited about this opportunity because you will… Be an Owner: Take ownership of your assigned shifts, including warehouse and kitchen processes, safety/cleanliness, quality, and training. Maintain accountability for inventory, equipment, and other company assets to ensure they are properly handled, stored, and protected from loss or theft. Delight Customers: Ensure customer orders are delivered with high quality by executing orders accurately, communicating with customers when issues arise, and making sure Dasher pickups go smoothly. Lead: Guide Operations Associates through their shift by ensuring the team works safely and productively and serving as the point of escalation for daily operations. One Team One Fight: Support operations in both the warehouse and kitchen, assist with day-to-day tasks, and lead by example. You will be expected to engage in professional and respectful interactions with team members and customers, ensuring a positive and safe

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing