Field Operations Executive in San Francisco

About the Team AI Research Lab is one of DoorDash’s frontier innovation hubs, focused on building the foundation for an AI-native future across our three core audiences: consumers, merchants, and dashers. As AI capabilities accelerate, the AI Research Lab operates at the center of technical exploration and real-world execution — connecting frontier model research, internal platform investments, operator teams, and strategic external partners. Our mission is to translate cutting-edge AI research into scalable, production-ready systems that drive measurable business impact. We combine deep technical rigor with strong operational execution to ensure that breakthrough capabilities become durable competitive advantages for DoorDash. About the Role As an Associate Manager, Strategy & Operations on our AI Research Lab, you will play a central role in converting frontier AI advancements into shipped products and scalable infrastructure. You will operate across research, product, and operations to move from early discovery and experimentation to deployment and impact. This role sits at the intersection of customer insight, technical innovation, and business execution. You will help define and scale the Lab’s most important bets while building the foundations that enable AI applications to compound over time. You’re Excited About This Opportunity Because You Will … Reimagining core experiences through AI, such as the merchant journey, by partnering directly with in-field merchants, sales, support, product, and engineering teams. You will help unify major initiatives into a coherent, AI-native interaction model. Own revenue-driving AI initiatives, operating as the accountable business owner for high-priority AI bets and ensuring clear linkage between technical progress and financial outcomes. Lead business planning cycles, developing go-to-market strategies for AI-powered products and capabilities, overseeing execution through structured project plans, resource allocation,

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Airports team is part of a mission-critical endeavor that keeps travelers moving smoothly. As an engineer on our team, your role will be essential in making sure drivers and riders enjoy a dependable experience at airports. You'll work hand in hand with various teams across Lyft, fostering collaboration and driving innovation to tackle the unique challenges of the travel and airports industry. Your responsibilities will also involve managing real-time communication with airports, ensuring our technology integrates seamlessly into their operations. Your skills will be the driving force behind enhancing the airport journey for millions. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Lead large features from idea to positive execution and launch Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Participate in our teams on call rotation. Identify, triage, debug and resolve issues/bugs across our various applications and platforms Have the ability to explain the various trade offs made in decisions Manage project priorities, deadlines, and deliverables. Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or related field or equivalent practical experience 2-5+ years of software engineering/production infrastructure industry experience Experience with Python, Go Proficiency in object-oriented programming Experience working with data structures or algorithms Ability to work with a low-ego, highly collaborative, and cross-functional team Bonus points: experience pursuing side projects or open-source project Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled M

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 the Team Marketing at Snorkel is growing rapidly and anchored by high-ownership operators who lead independently, align cross-functionally, and consistently deliver outsized results. We partner across Sales, Product, Research, and the executive team to translate complex AI and data value into differentiated positioning, integrated programs, and field-ready enablement that accelerates growth. The culture is high standards, high autonomy, and high collaboration. About the Role Reporting to the Sr. Director of Product Marketing, the Product Marketing Manager, Frontier Labs will own the GTM execution for our frontier lab business. You will partner closely with Research, FDE, and frontier-facing sales teams to translate technical work into research-credible positioning, repeatable sales plays, and high-quality GTM programs that resonate with research and procurement leaders inside frontier labs. You will keep the frontier asset library (battlecards, technical one-pagers, decks, benchmark and eval narratives) sharp against a fast-moving market, and bring competitive and customer insight into every motion. This is a hands-on role for a product marketer who wants

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 want to work on commercializing autonomy and robotics in a service used by millions of people — and on bringing the merchant partners who power that service along with us — then we want to talk to you! About the Role Come help us redefine last-mile logistics through robotics, automation, and other advanced technologies. Autonomy only works when merchants — restaurants, retailers, and other partners — can reliably interact with our robots: handing off orders, troubleshooting edge cases, and trusting the experience enough to keep using it. This role owns that side of the equation. We're looking for a Merchant Success & Growth lead to build the strategy and operational mechanisms that get merchants onboard, keep them performing, and turn their day-to-day reality into a tight feedback loop for product and engineering. You're excited about this opportunity because you will… Own merchant adoption and performance KPIs for autonomy end-to-end — defining what "successful merchant interaction with a robot" means, instrumenting it, and driving improvement against it. Build the playbooks and operational mechanisms to onboard merchants to autonomy — from first conversation through training, go-live, and steady-state ops — and scale them across markets. Partner with sales, account management, and field ops to recruit and ramp the right merchant cohorts for each stage of the product, and design experiments that test new merchant-facing features and handoff models. Define merchant performance benchmarks (handoff success rate, dwell time, dasher/robot interaction quality, merchant CSAT) and run the cadence that holds partners and internal teams accountable to them. Stand up the feedback loop from the field back to product and engineering — turning merchant complaints, edge cases, and frontline observations into prioriti

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

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

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

#Team Nextdoor Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on. Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 350,000 neighborhoods across 11 countries. Meet your Future Neighbors As an Analytics Engineer 4 with Nextdoor, Inc. (San Francisco, CA) (May telecommute from any U.S. location) you’ll: Apply mathematical or statistical theory and methods to design, create, and select the appropriate samples of data that will allow the data science team to conduct probabilistic experiments and statistical analyses Design software systems and processes to gather data in the most efficient way and determine key data points needed in order to interpret experiment results and ensure results are properly tracked Interpret data and report conclusions drawn from their analyses Work with cross-functional teams, including product, design, engineering, marketing, operations, and sales, to determine which data analyses will lead to the most actionable insights Build data pipelines to create and transform data for analysis of different product features Clean and summarize data to make it accessible for reporting and for data science Combine data from multiple sources to make and distribute client reports in order to see how particular ad products are performing Analyze expected vs actual delivery of ad products in order to find and improve gaps in our delivery pipeline What You’ll Bring to The House Master’s degree or foreign equivalent in Mathematics, Statistics, Business Analytics, or closely related quantitative field. Three (3) years of years of experience in the role or in a related position. Full term of experience m

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 are hiring a Software Integration Engineer for our Platform Integration team. This is a critical role with impact across the robot lifecycle, from manufacturing to daily operation. The Platform Integration team owns making sure the robot works as one cohesive system. The focus is on the interfaces between subsystems; this role in particular is focused on the software side handling interaction between: OS & software stack; firmware; networking; timing; and calibration. In this role, you will work cross functionally with our electrical, hardware, firmware, and autonomy engineers to support new functionality both in both hardware and software. This includes creating provisioning tools, functional tests, and supporting integration into the autonomy software stack. You will report to the Autonomy Platform Lead on our Autonomy Platform Team at DoorDash Labs. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Play an integral role on a small and focused team. Lead system-level debug when an issue crosses subsystem boundaries or no single team can isolate it. Support early integration of new sensor and software component designs by identifying interface requirements, risks, dependencies and required checks. Design and maintain integration tests, test setups, and procedures to ensure subsystems, once combined, satisfy requirements and design intent. Build and maintain the mission-readiness checks used before manufacturing signoff, validation, field testing, or mission use for different robot platforms. Create the tools, checks, and debug guidance that Manufacturing Integration, Validation,

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 ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. 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 across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of 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 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: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/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, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

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 HP IQ is seeking a Senior Power Systems Engineer to drive end to end system architecture, modeling, and optimization for wearable platforms. The candidate will build power models, define system use cases and operating modes, partner with product and engineering teams to meet aggressive power targets, and define manufacturing tests and field telemetry for NPI. The ideal candidate brings strong systems thinking, hands-on experience with low power architectures, and the ability to build models and telemetry to drive tradeoffs from SOC level to board level to maximize user runtime. What You Might Do: Power architecture responsibility for a wearable device covering SoC states, sensor, audio, and memory architecture tradeoffs at board level. Battery, PCM, and charging profile definition and validation Design power experiments, test plans, and measurement & telemetry mechanisms across firmware and hardware to optimize power and performance. Build and maintain system-level power models to model expected power consumption for user profiles. Map power models by subsystem, correlating

About Prophecy Prophecy is building the next generation AI-powered data prep and analysis platform. Our platform enables business analysts and data teams to transform raw data into reliable, production-ready datasets and insights faster, using modern data infrastructure and AI-driven capabilities. We work with leading enterprises to simplify how organizations prepare, analyze, and operationalize data, while maintaining strong governance, security, and operational control. Our mission is to make it dramatically easier for organizations to turn complex data into trusted insights that drive decisions. About the Roles We are looking for a Director of Strategic Partnerships who can do both: drive revenue through Prophecy's partner ecosystem, and build an effective partner program. This is an early-stage, high-ownership motion, the playbook is still being written, and you'll have real influence over how we engage partners, what good looks like for partner-sourced pipeline, and how we build durable co-sell relationships with Snowflake, Databricks, GCP field and partner teams. You will sit at the intersection of sales, partnerships, and strategy, owning partner performance while building the programs and processes that scale it. You'll work directly with our AEs and SEs to bring partners into deals at the right moments, and you'll serve as the primary point of contact for our strategic cloud and ecosystem partners. What You’ll Own Partner Revenue & Pipeline Own and exceed partner-sourced and partner-influenced revenue targets on a quarterly basis Proactively generate pipeline through Snowflake, Databricks, and GCP field AEs and PDMs — building the relationships that produce qualified, sourced opportunities Drive joint account mapping and target account activation against Prophecy's ICP: enterprises running Alteryx on Snowflake or Databricks Activate co-sell motions through marketplace programs (GCP Marketplace, Snowflake Partner Network, Databricks

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