Eng in San Francisco

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About the Team At DoorDash we’re building the industry’s most scalable and reliable delivery network to support our three-sided marketplace of consumers, merchants, and dashers. TPMs on our Engineering teams provide fundamental support to the underlying technology services as well as the engineers building these services. It’s no simple task, but it wouldn’t be interesting if it was! About the Role Platform Services is one of DoorDash’s organizations responsible for extending DoorDash beyond the consumer marketplace. The team owns three distinct business lines: Drive, a white-label delivery API that enables external businesses to access DoorDash’s delivery network; Parcels, which provides last-mile logistics for retailers and merchants; and Enterprise (DoorDash for Business), a b2b product suite powering corporate meal programs and large ordering for organizations of all sizes. We are looking for a Senior Technical Program Manager to help scale Platform Services. You will lead important engineering wide initiatives across Enterprise, Drive, and Parcels, working with Engineering, Product, Operations, and business leaders to deliver dependable, extensible logistics capabilities for external businesses. Programs will span backend services, partner and merchant integrations, operational tooling, and platform interfaces. They require strong technical judgment, cross organizational coordination, stakeholder management, and ownership of results. You will report into the centralized Technical Program Management team in Engineering. You're excited about this opportunity because you will… Drive Platform Services’ Most Strategic Programs - You will partner closely with Engineering and Product leadership, Strategy & Operations, and cross-functional teams to turn Platform Services’ strategy into executable technical programs. The portfolio spans Drive (DoorDash’s white-label delivery offering), Parcels (last-mile logistics for merchants and retailers), and Enterprise (DoorDa

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! About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About The Role Snorkel is hiring a Head of Security to build and lead our security function end-to-end — infrastructure security, application security, and governance, risk & compliance (GRC). You'll own the security function end-to-end — strategy, team, and execution — and operate as the primary security voice with customers, auditors, and the exec team. You'll report to the CTO. This is a builder's role: you'll take security from its current state to a mature, right-sized function as Snorkel scales, hiring and developing the team as needs grow. Key Responsibilities Security Leadership & Team Building Define Snorkel's overall security strategy,

We believe communication belongs to everyone. We exist to democratize phone service. TextNow is evolving the way the world connects, and that's because we're made up of people with curious minds who bring an optimistic yet critical lens into the work we do. We're the largest provider of free phone service in the nation. And we're just getting started. Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere. TextNow is looking for an experienced Data Developer with hands-on experience designing and developing data platforms. You will own the design, development, and maintenance of TextNow's data platform, enabling us to make effective data-informed decisions. You will be part of cross-functional efforts to build scalable and reliable frameworks that support allTextNow's business and data products. In this role, you can interact with different functional areas within the business and influence decision-making in a fast-growing mobile communications start-up. This role is about impact at scale. You’ll shape how TextNow builds and operates its systems in an AI-first environment where intelligent tooling is embedded into everyday engineering practice. Using AI is not optional, it’s expected. From design and architecture to implementation, testing, debugging, documentation, and operational analysis, you will actively leverage AI tools to increase velocity, improve code quality, and make better technical decisions. We provide a robust suite of AI-powered development tools and workflows to support you, and we expect you to continuously evolve how you use them to raise the bar for efficiency, clarity, and product excellence across the organization. What You'll Do Own TextNow's data warehouse, data pipelines, and integration points between various business systems. Design, develo

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have work

National Security Hackathon Attendees – Stay Connected with Scale AI This posting is for candidates who attended National Security Hackathon and connected with a member of the Scale AI team. It was great meeting you at the Hackathon! Whether we spoke at our booth or on the floor, we always enjoy connecting with people who are passionate about advancing AI and machine learning. At Scale AI, our mission is to develop reliable AI systems for the world's most important decisions. For the past ten years, Scale has been the leading AI data foundry, supporting some of the most exciting advancements in AI, including generative AI, defense applications, robotics, and autonomous systems. We’re continuing to grow our team across a range of technical and mission-focused roles. If you're excited about the problems we’re tackling, feel free to share your information here. A member of our team will reach out if there’s a strong fit with one of our open opportunities. And even if the timing isn’t right today, we’d love to stay connected. We look forward to continuing the conversation. In the meantime, you can learn more about our work at scale.com . 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. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: c

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

About the Team At DoorDash, design means making experiences for the people who order, the people who prepare, and the people who deliver. As a Design Manager at DoorDash, you want to build things that matter to real people. You're at your best when you can move from idea to shipped product quickly, bringing experiences to life that reach and influence users at massive scale. You'll care about whether the product you make solved a real problem for real people, or changed how someone experiences their day. You'll work shoulder-to-shoulder with Engineering and Product Management, dig into the data, and use LLM-powered tools alongside traditional design tools. If the LLM powered tools don’t exist yet, you build them. About the Role Trust is the foundation of every interaction on DoorDash. We're looking for a design leader who can define and drive a vision for designing for integrity at scale. In this role, you will join the Integrity organization. You’ll lead a team of designers working across fraud prevention, trust, safety, and compliance — protecting millions of consumers, Dashers, and merchants while keeping the platform seamless and trustworthy. You will report into the Head of Design for our Customer Experience & Integrity organization. This role is hybrid- 1–2 days per week in one of our Design Hubs. You’re excited about this opportunity because you will… Set the technical direction for Design across your product area — decide what gets built, in what order, and why; connect multiple teams around shared platforms so the work compounds instead of duplicating Work on ambiguous problems and turn them into architecture decisions and working systems that teams actually use; earn trust with leadership not through decks, but through prototypes and shipped code that make your point for you Stay close to the code and the craft across multiple projects at once — you're not just reviewing, you're building; the work you ship will move real metrics across the product area

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). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. 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. 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 role. 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 du

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

About the Role As the Fleet Coordinator, you will be the single source of truth for the fleet: tracking what configuration each aircraft is flying and where it is, with no aircraft cleared to fly outside its approved configuration.You'll oversee all aircraft configuration that supports engineering and Part 135 operations, while keeping aircraft audit-ready. You will play a key role in supporting safe, compliant, and reliable operations by dispatching aircraft, tracking configuration and compliance records, and acting as the connective tissue between engineering, operations, maintenance control, and the FAA. You're excited about this opportunity because... Fleet Configuration & Testing: Maintain and verify compliance across the Part 107 test and Part 135 Commercial aircraft inventory: registration, airworthiness status, maintenance logs, and battery/component life-cycling." Maintain accurate software, hardware, and firmware configuration records for every aircraft, including designated testing candidates, so results are always traceable to a known config. Track aircraft location across the fleet ensuring one hundred percent accountability. Initiate and track parts requests tied to configuration changes, testing, and scheduled maintenance. Operations & Compliance: Maintain OpSpecs and the general maintenance manual, ensuring maintenance procedures and standards align with Part 135 requirements. Maintain the maintenance, training, and flight-log records the FAA expects an air carrier to produce on demand. Act as point of contact during FAA audits, representing the accuracy of aircraft configuration records and documentation against the maintenance program's compliance requirements. Fleet Dispatch & Availability: Decide which aircraft flies which mission (dispatch-style), verifying maintenance status before an aircraft is released. Track each aircraft's real-time location and availability, including movements between bases, hangars, and maintenance fac

TextNow is on a mission to make communications affordable and accessible for everyone. As a full MVNO operating our own mobile core network over LTE and 5G NSA, we have the unique advantage of controlling our network infrastructure end-to-end. We operate the HSS, PGW, and other critical network functions, giving us the flexibility to innovate and deliver exceptional service to millions of users. About the Role Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere. T extNow is looking for a new SecOps team member to secure, monitor , and enable automated response within our infrastructure. What You’ll Do Ensure Secure & Reliable Systems: Design, implement, and maintain security-focused infrastructure to protect TextNow’s services while ensuring reliability and scalability. Security Automation & Infrastructure as Code: Develop and enforce best practices using Terraform, Ansible, Crowdstrike , and AWS security tools , ensuring secure configurations, automated compliance checks, and infrastructure as code. Threat Detection & Incident Response: Participate in an on-call rotation to respond to security incidents, investigate vulnerabilities, and implement proactive measures to prevent future threats. Work closely with engineering teams to remediate security risks. Monitoring & Logging for Security: Improve observability by implementing security monitoring solutions, logging best practices, and alerting mechanisms to detect anomalies and suspicious activity. Access Control & Identity Management: Manage IAM roles, permissions, and policies to ensure least privilege access and enforce security controls across cloud and internal systems. Collaboration & Security Advocacy: Wo

As Sigma scales its global footprint, the Sales Engineering (SE) organization is the technical engine driving our GTM motion. We are looking for a Strategy and Operations Lead, SE to partner directly with our VP of SE and serve as the operational bedrock for this critical organization. Operating within our broader GTM Strategy & Operations team, you will own the global operating rhythm, operational infrastructure, and capacity planning for the entire SE organization. You will drive strategy across a highly matrixed, global environment. You are part strategist, part builder, and part operator - responsible for ensuring our pre-sales motion scales seamlessly. What You Will Do Drive Business Reporting & the SE Operating Rhythm: Own the cadence of the SE organization. Design and execute regular business reviews and leverage Sigma to build robust, real-time reporting that gives the VP of SE crystal-clear visibility into technical pipeline health, team utilization, and conversion metrics. Optimize Funnel Mechanics & Deal Acceleration: Deep dive into the pre-sales funnel to identify where deals stall during technical validation. Partner with SE leadership to optimize the Proof of Concept (POC) lifecycle, remove friction, and accelerate the technical win. Lead Global Headcount & Capacity Planning: Serve as the SE representative in cross-functional GTM planning cycles. Own end-to-end global SE capacity requirements, design territory allocation frameworks, and manage annual headcount planning seamlessly across AMER, EMEA, and APAC. Build Solutions in Sigma: Leverage Sigma itself to build robust operational solutions, designing the dashboards, data models, and workflows needed for POC tracking, capacity management, and performance visibility. Act as the Cross-Functional Hub: Represent the SE organization in all major GTM Strategy & Operations initiatives. Serve as the connective tissue between SE, Sales, Product, and RevOps, ensuring SE requir