R And D Dry Etch Process Development Engineer in San Francisco

At Qualia, we've built the leading B2B real estate technology that transforms the home buying and selling experience into a simple, secure, and enjoyable process. Our SMB and Enterprise products bring together users from across the real estate ecosystem---homebuyers and sellers, lenders, title and escrow agents, and real estate agents---onto a single shared digital closing platform, providing greater clarity and transparency to real estate transactions. Today, through our business customers across the country, millions of consumers use Qualia to close on homes every year. WHAT YOU'LL WORK ON The FP&A team at Qualia is the analytical engine of the Finance organization. We own the company’s planning and forecasting processes, serve as trusted business partners to functional leaders, and produce the financial insights that inform our most important strategic decisions—all in an environment where AI is actively reshaping how we work. As a Senior FP&A Analyst, you will be a driving force across the organization for forecasts, annual planning, long-range planning, and critical financial analysis — partnering closely with leaders across Sales & Marketing, Customer Success, R&D and G&A to manage spend, track performance, and surface insights that shape how Qualia operates as we scale. RESPONSIBILITIES Elevate Qualia's financial rigor — drive deeper Budget vs. Actuals analysis and forecast precision via smarter, more data-driven modeling and tighter cross-functional collaboration, particularly in uncharted, high-impact areas Support monthly forecasting and reporting processes — analyze financial results, distill key trends, and communicate risks and opportunities to influence business outcomes; assist in preparation of monthly and quarterly management reporting including variance analysis, dashboards, and Board materials Build and own our growing playbook of financial models and reports, ensuring quality, timeliness, and accuracy across in-depth analyses

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Metronome, now part of Stripe, is the leading usage-based billing platform built for modern software companies. With Metronome, companies can launch products faster, offer any pricing model, and streamline finance workflows without writing code. Our platform computes millions of invoices per billing period and is scaling rapidly to accommodate new customers, saving them hours of development time and manual invoicing and enabling them to use consumption data to better serve their customers. Our customers love our product and approach, and we’re humbled to work with amazing companies like OpenAI, NVIDIA, Confluent, and Anthropic. What you’ll do As a member of our technical support engineering team, you will be on the front lines providing world-class customer service. As part of our engineering organization, you will become an expert on our product and partner closely with Metronome's engineers, customer success, solutions architecture, and growth teams, as well as our customers' developers. Your primary responsibilities will include handling customer escalations through our ticketing system, using internal observability tools to diagnose and scope customer-facing issues, collaborating directly with customers via Slack and other channels, and developing internal tools and documentation to improve the support experience. Since we view every support escalation as an opportunity to learn, both as individuals and as a company, you will play a

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

At Scale, we believe that the next frontier of artificial intelligence is embodied. The Physical AI team is focused on building general AI that can reason and act in the physical world. By leveraging Scale’s massive, industry-leading data infrastructure, we are partnering with frontier labs to build Foundation Models for Physical AI that will redefine the future of automation. To support our rapid hardware-software iteration cycles and ensure a world-class R&D environment, we are looking for a Safety Coordinator / Lab Lead to anchor our physical testing operations. Role Overview As the Safety Coordinator / Lab Lead , you will play a mission-critical role in scaling our physical testing infrastructure safely and efficiently. This is a high-impact position where your highest-priority responsibility will be owning the end-to-end execution of safety audits and incident documentation . Operating at the intersection of cutting-edge AI foundation models and complex robotics hardware, you will ensure our researchers, engineers, and autonomous systems interact in a secure, compliant, and highly organized environment. Core Responsibilities Priority Focus: Safety Audits & Incident Documentation Rigorous Safety Audits: Design, schedule, and execute routine safety audits across all physical testing environments, robot cells, and hardware workspaces to ensure continuous compliance with internal benchmarks and industrial safety standards. Incident & Near-Miss Documentation: Own the end-to-end incident management pipeline. Act as the primary point of contact for documenting, archiving, and analyzing any lab incidents, mechanical anomalies, or near-misses. Root-Cause Analysis (RCA): Lead structured post-incident investigations to identify systematic risks, authoring comprehensive RCA reports and implementing Corrective and Preventive Actions (CAPA). Data-Driven Risk Mitigation: Treat safety data as a core operational asset—tracking safety metrics and audit trends to proa

About the Team The Analytics team is looking for experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decision-making across the company across a variety of teams and levels. Data Scientists at DoorDash work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. Analytics is integral to all operational areas at DoorDash. Please apply here for all non-managerial levels within the following analytics teams: Consumer & Growth Business Operations Dasher & Logistics Customer Experience & Integrity Merchant, Ads & Sales New Verticals International Data Science About the Role As a Data Scientist at DoorDash, you'll use your quantitative background to mentor other scientists and dive into large datasets to guide decision-making. We solve a multitude of exciting challenges including customer acquisition, fraud and support, marketing, balancing supply and demand, new city launches, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, 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… Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, R, Python, or other scripting and statistical tools Work with and mentor junior analysts on how to use more advanced methods and solve challenges Produce recommendations and use statistical techniques and hypothesis testing to validate your findings Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends Identify and measure levers to help move essential metrics and make recommendations Work backwards from understanding and sizing problems to ideating solutions Report aga

About the Team The Sales Analytics team at DoorDash is responsible for getting the right information and insights out to drive our business goals. As DoorDash grows both in scale and breadth of offering, the strength of our sales engine and organizational structure must grow with it. About the Role You will be focused on partnering with our sales & strategy teams, who help solve pain points for small business (SMB) merchants on the Doordash platform through various methods such as new product adoption. You will lead analyses to guide our sales team with data-driven insights to unlock growth opportunities within their accounts. This cross-functional role will partner with sales, operations, product, and strategy teams. You will report into a Senior Manager on our Sales Analytics team, which is part of our Sales Operations organization. You’re excited about this opportunity because you will… Strategize – Devise and execute initiatives against the overall sales org strategy for “winning the merchant” while managing stakeholders across multiple lines of business Experiment – Use data-driven decision-making and sound business judgment to run sales tests and lead market intelligence efforts Optimize – Build the best merchant acquisition engine so DoorDash continues to offer the highest quality selection for its customers Analyze – Build models to evaluate the economics, value, and opportunity costs of strategic initiatives to improve sales performance Influence – Manage cross-functional projects with our sales, partner management, operations, product, engineering, business operations and BD teams to improve the merchant experience and achieve targets We’re excited about you because… You have 2+ years of experience in Analytics, Consulting, or Strategy You have a bachelors degree or higher You are highly technical with advanced SQL, basic Python/R, AI, and data modeling experience. You are an excellent analytical thinker who can deliver actionable recommendations