Practice Manager in San Francisco

About the Role Sigma Computing is redefining business intelligence by making complex data analysis accessible through a high-performance platform built for the modern data stack. The Compiler Team plays a foundational role in this mission by transforming user-driven spreadsheet interactions into highly optimized SQL queries, enabling seamless exploratory analytics on cloud data warehouses. As a member of the Compiler Team, you will join a group of engineers dedicated to building the core systems and abstractions that power Sigma’s intuitive spreadsheet interface, ensuring speed, reliability, and scalability for all users. What You Will Be Doing Tackle core challenges at the intersection of data modeling, query compilation, and large-scale interactive analytics—making it possible for end-users to query data warehouses efficiently without deep technical knowledge Design, build, and maintain sophisticated compiler infrastructure and intermediate representations that translate spreadsheet operations into optimized query plans Apply advanced optimization strategies to improve performance and accuracy across a wide range of query workloads and data architectures Contribute to both backend (Rust) and key frontend foundations (TypeScript), evolving critical abstractions that enable end-to-end workflow optimizations and new features Debug, analyze, and resolve complex issues, ensuring robustness and maintainability in a rapidly evolving product Collaborate with engineers and product stakeholders to review designs and code, driving technical best practices and architectural decisions throughout the team and company Qualifications We Need 5+ years experience engineering high-quality software systems Demonstrated success building and maintaining complex infrastructure or core platform services Deep understanding of Computer Science fundamentals, particularly in compilers, algorithms, SQL Optimization Passion for teamwork, technical ownership, and continually

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

Scale Labs, Research Scientist — Safety Post Training 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 Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. 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. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati

About the Team The Analytics team is looking for Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash. About the Role Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. This is a rare operational and actionable data-driven experience. We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… As a senior Individual Contributor, mentor and influence junior Data Scientists in investigating complex issues and uncovering key drivers of our business Influence the Product and Operations roadmap by making actionable recommendations based on data Interface frequently with senior leadership to showcase your team’s work and tackle complex business problems Drive measurement strategy for the area under scope, defining success metrics and implementing best practices around experiment design and statistical analysis Develop a strategic learning roadmap based on data observations, strategic questions, and hypotheses We're excited about you because you have… A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain 8+ years of experi

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 looking for an experienced technical operator to lead live testing, deployment, and operational validation of cutting-edge autonomous technologies. This role sits at the intersection of engineering and operations, helping ensure new capabilities are safely deployed, thoroughly evaluated, and translated into actionable engineering feedback. You’re excited about this opportunity because you will… Lead and oversee live testing across transport, deployment, and safety validation. Partner closely with hardware, software, and business operations teams to validate new product capabilities while providing guidance and mentorship to junior team members. Conduct and document complex tests for autonomous technologies, evaluating robot behavior, identifying issues, and validating new features and requirements. Provide actionable technical feedback to engineering teams based on test outcomes. Exercise technical judgment during live testing by evaluating robot behavior, assessing operational risk, distinguishing expected behavior from product defects, and determining when engineering escalation or additional validation is required. Develop and implement testing processes, protocols, and checklists that improve the safety, efficiency, and reliability of new products. Utilize internal tools to analyze logs, investigate issues, document findings, and track issues through resolution. Mentor junior team members in structured debugging and documentation practices. Conduct detailed analyses and generate comprehensive reports that identify trends, summarize findings, and provide strategic recommendations to engineering and operations partners. We’re excited about you because… 2+ years of exper