Software Engineer Database Engineering Manager Manager in San Francisco

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE The largest, most demanding enterprises run on Baseten, and they bring exacting requirements for how people, services, and agents access the platform. This is the founding role for our identity and authorization team within enterprise engineering. You'll own the identity and access layer of the Baseten platform: the authorization model, credential systems, and admin experiences that enterprise IT teams use to govern access for organizations like Harvey, HubSpot, and Notion. You'll design and build Baseten's fine-grained authorization system from the ground up to support the workflows customers depend on today while giving them cleaner, more precise ways to manage access as the platform grows. Authorization at Baseten requires low-latency permission checks at high request volume, consistent contracts and behaviors across the product suite, and strong security guarantees for mission-critical, highly regulated workloads. EXAMPLE INITIATIVES Recent and upcoming work in this area: Fine-grained authorization for users, service accounts, and agentic workloads: per-resource permissions at the organization, team, and workload scope to support both common workflows and complex enterprise access policies Programmatic authentication allowing high-compliance customers to connect service principles securely via short-lived, workload-based credentials Agent credentials that grant an agent exactly the access it needs for the gi

About the Team The Safety Systems org is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Engineering team builds the platforms and tools that make OpenAI’s models safe to use in the real world. We partner closely with researchers, product teams, and policy to turn safety ideas into reliable, scalable systems: measuring risk, enforcing safeguards, and continuously improving how models behave in production. Our work sits at the intersection of product engineering, data, and AI, and directly shapes how millions of people experience OpenAI’s technology. About the Role We’re looking for a self-starter engineer who loves building products in an iterative, fast-moving environment—especially internal tools that unlock real-world impact. In this role, you’ll build full-stack tooling for our Safety Systems teams that directly improves the safety and reliability of OpenAI’s models, including in sensitive areas like mental health and other vulnerable-user protections. Your work will increase the team’s velocity in identifying and fixing safety issues and help tighten the feedback loop between policy, data, and the model training cycle. In this role, you will: Own the end-to-end development of internal tools that help improve the safety of OpenAI’s models (with a focus on areas like mental health and other vulnerable-user protections) Partner closely with Safety Systems researchers, engineers, and model policy creators to understand workflows, pain points, and requirements—and translate them into durable product solutions Build full-stack experiences to support core model policy workflows, such as labeling and inspecting data, analyzing and reviewing failure cases, and surfacing insights for iteration Optimize internal applications f

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About Mixpanel Mixpanel turns data clarity into innovation. Trusted by more than 29,000 companies, including Workday, Pinterest, LG, and Rakuten Viber, Mixpanel’s AI-first digital analytics help teams accelerate adoption, improve retention, and ship with confidence. Powering this is an industry-leading platform that combines product and web analytics, session replay, experimentation, feature flags, and metric trees. Mixpanel delivers insights that customers trust. Visit mixpanel.com to learn more. About The Team Mixpanel Engineering is a small, fast-moving team focused on delivering real value to customers. We build powerful AI-powered product analytics while obsessing over clarity, simplicity, and delight. Engineers here own problems end to end. You can move across the stack to ship impact without being blocked by silos or heavy process. Product innovation drives our business, and product engineering teams own that responsibility. Our OLAP engine queries over 500 trillion events; a typical blob storage system we interact with processes 300 PiB/month at 1.2 Tbps sustained, and we run many of them across the world. The Data Runtime team owns the data execution layer that powers every Mixpanel product. We ensure that every customer query runs fast, cheap, and reliably, at any scale. This is an exciting time to join. Mixpanel's agentic and AI-first products are driving rapid growth in query volume, and Data Runtime is making the big bets that power it. We’re investing in elastic query compute and a distributed file cache that will let us scale query workloads dramatically without scaling cost with them. We

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will build the model runtime within the inference engine that executes complex, frontier models at scale on OpenAI’s custom silicon. The runtime will sit between models running on the hardware and the upper layers of the cluster serving software stack, translating demanding inference workloads into efficient execution while optimizing for throughput, latency, utilization, and reliability. You will work across model architecture, distributed systems, compilers, kernels, and silicon to design a production-grade runtime comparable in ambition to systems such as vLLM and SGLang, but customized and optimized for OpenAI’s AI accelerator. Your work will shape how new model capabilities map onto the platform and how quickly custom silicon can deliver meaningful performance in production. In this role, you will: Design and implement the LLM inference runtime for frontier models running on custom silicon. Build scheduling, continuous batching, memory management, KV-cache management, and execution orchestration for high-performance inference. Develop distributed execution strategies across chips, hosts, and racks, including model partitioning, communication, and synchronization. Optimize end-to-end latency, throughput, memory efficiency, and hardware utilization across diverse model architectures and serving workloads. Partner with kernel, compiler, architecture, and silicon teams to co-design interfaces and remove performance bottlenecks across the stack. Enable new

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will build the low-level device runtime that turns compiled programs into efficient, functional and performant execution on OpenAI’s custom AI accelerator. This software will schedule kernel launches, manage device memory and address spaces, coordinate synchronization, and expose reliable abstractions to higher-level runtimes and frameworks. You will work at the boundary of software and hardware, partnering with compiler, kernel, architecture, verification, and silicon teams to define interfaces and validate behavior. You will also use and improve event-based, cycle-accurate simulation to develop runtime capabilities before silicon is available, diagnose performance and correctness issues, and guide hardware-software co-design. In this role, you will: Design and implement the low-level device runtime for OpenAI custom silicon. Build kernel-launch scheduling, command submission, queueing, dependency tracking, and completion handling. Manage device memory spaces, allocation, virtual-to-physical mappings, data movement, and lifetime across concurrent workloads. Implement synchronization primitives, events, barriers, streams, and ordering guarantees that are correct and efficient. Define clean interfaces between the runtime, drivers, firmware, compiler-generated code, kernels, and higher-level execution systems. Use event-based, cycle-accurate simulators to develop, validate, debug, and performance-tune runtime behavior before and after silicon availability. Di

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: As a Developer Platform engineer, you will directly contribute to the foundational pieces that make Notion extensible and connected. You will build tools, APIs, and platform experiences that help customers connect Notion to the world — bringing their apps, data, and workflows into one workspace. Your work will make it easier for developers, admins, and builders to create reliable integrations and automations on top of Notion. You will be a key player in building the robust technical foundation that allows Notion to achieve the connected workspace vision. Your work will include both internal platform contributions that accelerate other Notion engineering teams and end-user-facing functionality that enables toolmaking ubiquity. You will be presented with challenging technical problems, as Notion’s product needs are complex. You’ll play a key role in identifying and executing against technical investments that ensure the long-term quality, reliability, and performance of Notion’s platform as we scale. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursd

Join the engineering teams that bring OpenAI’s ideas safely to the world! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. Build and maintain the load, chaos and synthetic-testing software leveraged by development teams to make the systems they design and operate more reliable. Build and maintain automation tools to streamline repetitive tasks and improve system reliability. Build and maintain the platform for CPU, storage, GPU, and network lifecycle management to drive efficiency, accountability and dynamic optimization of our resources. Implement fault-tolerant and resilient design

About the Team Our mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large-scale optimization, active learning, and other areas. The team builds the performance-critical systems that allow OpenAI's models to run efficiently across a diverse set of AI accelerators. We work across the inference stack, from low-level kernels and compilers through model execution, to unlock the full capabilities of the underlying hardware. About the Role As a Software Engineer, Trainium, you will help bring OpenAI's inference workloads to AWS Trainium and build the software stack required to run cutting-edge frontier models efficiently on the platform. This is a deeply technical, cross-stack role spanning kernels, compilers, and model execution. You will work on the systems needed to support OpenAI's inference stack on Trainium, including developing and optimizing high-performance kernels, improving compiler support, and enabling efficient execution of the model forward pass. You'll work closely with engineers across inference, compilers, kernels, and ML systems to identify performance bottlenecks and build the software needed to take full advantage of Trainium. The work may range from low-level hardware-specific optimization to compiler and runtime improvements to integrating new model architectures into the inference stack. If you enjoy working at the intersection of ML systems, compilers, kernels, and accelerator hardware, this role is for you. We're looking for engineers who are self-directed, comfortable operating across abstraction layers, and excited to solve challenging performance problems for frontier-scale AI systems. In This Role, You Will Build and optimize OpenAI's inference stack for AWS Trainium. Develop high-performance kernels for critical model operations and workloads. Extend and improve compiler support to efficiently target

Software Engineer — San Francisco, CA, USA. Apply via Workday.

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role operates on a hybrid schedule requiring two days of in-office collaboration per week. The position must be based in the San Francisco Bay Area. About the Role We're hiring a Software Engineer II within our Fulfillment organization — the backend systems that get the right job to the right Tasker and see it through to completion. You'll join Fulfillment Lifecycle, the team that decides how jobs are matched to Taskers for our partner and marketplace business, increasingly using unstructured data and experimentation to make matching smarter and fulfillment more reliable. The team is part of a company-wide platform modernization effort, breaking a legacy monolith into well-bounded, API-first services. We're hiring for a strong backend engineer who thrives on complex, data-intensive problems, is comfortable with ambiguity, and takes pride in well-tested, observable, production-ready code. What You'll Work On B

About the Team The Plugin Developer Platform team builds the APIs, SDKs, and tools that let people extend ChatGPT and Codex. We work on plugins, connectors, the Model Context Protocol (MCP), and interactive apps. We want anyone to be able to turn a useful workflow into a plugin, share it, and have other people use it. A plugin can package instructions and skills with connections to the tools and data it needs. Our work covers plugin creation and publishing, the systems that run plugins across our products, and open standards that developers can build on. About the Role We’re looking for platform-minded engineers who know what it takes to build a platform developers want to use. You’ll work across developer-facing interfaces, APIs, and backend systems. You’ll own features from the first developer conversation through implementation and release. You’ll talk directly with developers, partners, and the open-source community. Their experience will inform the APIs and abstractions you design, the problems you prioritize, and the tradeoffs you make. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. What You’ll Do Design and ship APIs, SDKs, and services that developers use to extend ChatGPT and Codex. Make plugins easier to create, test, publish, update, and share. Improve compatibility and consistency across ChatGPT and Codex, including interactive app experiences. Contribute to MCP and other open standards, bringing practical developer needs into their design. Work with developers and partners to understand recurring problems and improve the platform, tooling, and documentation. Work with Product, Research, Security, and Trust & Safety on permissions, compatibility, and safe, reliable execution. You Might Thrive Here If You Have built software that other developers use. Your experience might include an open-source project, an API or SDK, a developer platform, internal too

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Product Engineer on the Dedicated Inference team, you'll shape the state-of-the-art developer experience for deploying and operating AI workloads in production. From the CLI and SDKs to APIs, observability, and debugging workflows, you'll build the tools customers rely on every day to manage mission-critical inference deployments. Few teams at Baseten have as much breadth and visibility as Dedicated Inference. The team is often at the forefront of new product development, giving engineers the opportunity to shape the experience of some of our most important customers. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Dedicated Inference team: Chains for multi-component workflows Asynchronous inference Model APIs for frontier models Model training built for production inference RESPONSIBILITIES Implement new features and products for the team Design ergonomic APIs and abstractions to solve customer problems Fix bugs and resolve customer issues with urgency Work across the stack - regardless of where you start, you’ll end up touching both React Components and Kubernetes Pods Work closely with the product and forward deployed engineering teams to develop and drive new product ideas REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Python, Go, or Javascript proficie

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Develop infrastructure components for our ML inference platform using Python and Go Implement and maintain Kubernetes deployments for model serving Contribute to our inference orchestration layer for model deployments Build and enhance monitoring systems for model performance metrics Implement efficient resource management solutions for ML workloads Support infrastructure automation to improve ML deployment workflows Work closely with team members to implement technical solutions Help balance performance optimization with system reliability Participate in technical discussions around infrastructure improvements Learn and apply infrastructure best practices REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus Working knowledge of Kubernetes and containeriza

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Are you passionate about advancing the application of artificial intelligence? We are looking for a Software Engineer focused on ML performance to join our dynamic team. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM Inference. If you are a backend engineer who thrives on making things faster and is excited about open-source ML models, we look forward to your application. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, kv cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure. Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to debug ML performance issues. Apply and scale optimization techniques across a wide range of ML models, particularly large language models. Collaborate with a diverse team to design and implement innovative solutions. Own projects from idea to production. REQUIREMENTS Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. Experience with one

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Software Engineer on the Internal Tooling team, you will own the internal operating system that sits at the heart of how Baseten operates. Capacity helps unlock revenue by carefully balancing supply and demand. The operating system manages all aspects of the customer lifecycle: from onboarding to managing complex customer SLA requirements. This role is for engineers who want to own a product end to end, not just implement tickets. You will work directly with the Capacity, Sales, and Engineering teams to understand requirements, define solutions, and ship software that removes friction from some of the most high-stakes workflows in the company. If something is slow, manual, or error-prone in the capacity fulfillment lifecycle, you will be the one to fix it. You are a strong fit if you have strong product intuition, move fast without sacrificing quality, and take satisfaction in building tools that make the people around you measurably more effective. RESPONSIBILITIES Own the Capacity product end to end: scoping, design, implementation, and iteration based on feedback from internal stakeholders Translate complex operational requirements from Capacity, Sales, and SRE teams into clean, ergonomic product experiences Build and maintain full-stack features across the Capacity toolchain, including UI surfaces, APIs, and backend services Identify workflow bottlenecks and manual processes across the capacity lifecy