Performance And Systems Engineer in San Francisco

About the Team OpenAI’s Applications Engineering organization builds and operates the products that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role You will be a Senior Android engineer on OpenAI’s Applied Foundations team, building the core mobile experiences that power how users sign up, manage their account, family features, pay for services, stay safe, and interact with OpenAI’s products with confidence. This role is about creating high-quality products as well as reusable Android foundations that product teams across different OpenAI apps depend on to ship quickly while meeting the highest standards for security, reliability, and user trust. You’ll own complex client-side systems spanning UI, networking, local state, payment integrations and Apple platform integrations, and work closely with backend, product, and safety partners to shape the architecture that supports OpenAI’s mobile ecosystem at global scale. You might thrive in this role if you: Have 4+ years of professional software engineering experience. Have a proven track record of building high-quality Android applications in production. Are fluent in Kotlin (and/or Java) and familiar with Android development tools and architecture components. Prioritize performance, security, and user experience in mobile development. Enjoy working cross-functionally to bring ambitious product ideas to life. Care deeply about performance, security, and user experience. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Engineer to lead the engineering, characterization, and productionization of flexible and compliant components in robotic platforms. You will partner closely with cross-functional teams to translate material concepts into engineered subsystems that meet functional, durability, and manufacturing requirements. This role focuses on understanding how soft materials behave in dynamic mechanical systems — including fatigue, creep, hysteresis, wear, and environmental degradation — and designing assemblies that perform consistently at scale. You will work with materials such as elastomers, foams, thermoplastic polyurethanes (TPUs), engineered fabrics, knitted and woven textiles, cables, and other flexible load-bearing or transmission elements, integrating them with rigid hardware, sensors, and actuators using fabrication methods such as bonding, molding, lamination, and sewn assemblies. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Design and integrate compliant or flexible materials into mechanical subsystems and rigid hardware interfaces. Leverage FEA tools to characterize material behavior under operational loads, including tension, compression, abrasion, fatigue, and environmental exposure. Develop test methods and validation protocols to evaluate durability, performance, and failure modes of soft components. Collaborate with cross-functional teams to transition early prototypes into manufacturable designs. Source and evaluate materials in collaboratio

About the Team OpenAI’s Applications Engineering organization builds and operates the products that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role You will be a Senior iOS engineer on OpenAI’s Applied Foundations team, building the core mobile experiences that power how users sign up, manage their account, family features, pay for services, stay safe, and interact with OpenAI’s products with confidence. This role is about creating high-quality products as well as reusable iOS foundations that product teams across different OpenAI apps depend on to ship quickly while meeting the highest standards for security, reliability, and user trust. You’ll own complex client-side systems spanning UI, networking, local state, payment integrations and Apple platform integrations, and work closely with backend, product, and safety partners to shape the architecture that supports OpenAI’s mobile ecosystem at global scale. In this role, you will: Build and ship new experiences on iOS that showcase the power of AI. Optimize app performance, reliability, and responsiveness at global scale. Design and maintain shared iOS frameworks and primitives for account, trust, and commerce flows that are used across OpenAI’s mobile apps. Establish robust testing frameworks and refine app architecture for long-term maintainability. Collaborate with product, design, research, and backend teams to deliver high-impact features. Provide technical leadership to shape the future of OpenAI’s iOS platform. You might thrive in this role if you: Have 4+ years of professional software engineering experience. Hav

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 Software Engineer on Collections Infra, you’ll help scale the infrastructure behind Notion’s database block. Databases power views, boards, charts, forms, and the workflows customers use to run their companies; as Notion grows into larger enterprise deployments and AI-native work, those systems need to become faster, more reliable, and ready for much higher concurrency. This team sits between infrastructure and product, building backend architecture that improves the customer experience while becoming a platform other Notion teams can build on. You’ll work on problems like database load performance, microservices, high-volume writes from agents, and the flexibility that makes Notion databases powerful and hard to scale. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: By your 90th day, you’ll understand how Collections Infra supports Notion’s database

About the Team The Search research team focuses on building the systems that help AI systems find, retrieve, and use information from the world. We aim to make answers more useful and grounded for more than a billion ChatGPT users. About the Role We’re looking for a Technical Program Manager to lead a broad portfolio of research and engineering programs that power search. You’ll partner closely with researchers, engineers, and product leaders to turn ambitious goals into clear plans, resolve dependencies, and move complex technical work forward. This role combines technical depth, product judgment, and hands-on execution. You’ll work across retrieval, indexing, and model improvements, while collaborating with policy, legal, and external data partners. You’ll help teams make informed tradeoffs and build practical ways of working that support a fast-moving research environment. This role is based in San Francisco, CA. In this role, you will: Lead programs across model training, retrieval, large-scale indexing, and search infrastructure. Translate evolving goals into prioritized workstreams with clear owners, milestones, dependencies, and resource needs. Partner with research, engineering, and product leads to define requirements and make tradeoffs across scope, quality, performance, timelines, and cost. Establish program success metrics and use them to guide priorities and track improvements in coverage, answer quality, responsiveness, and trust. Identify technical and cross-functional risks early, drive blockers to resolution, and communicate progress and decisions clearly to teams and leadership. Coordinate with product, policy, legal, and external partners on data access, use, and presentation, helping teams resolve decisions that span technical and non-technical domains. Manage dependencies with data providers and build repeatable processes that help research and engineering teams execute effectively as the search effort grows. You might thrive in this role if you

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 Engineering Manager (Player & Coach), you will lead and mentor a team of Forward Deployed Engineers focused on building, scaling, and optimizing LLM inference workloads for Baseten customers. Applying both hands-on technical ownership and managerial leadership, you will guide your team through the processes of designing, deploying, and managing high performance, low latency AI applications on Baseten’s platform. FDE at Baseten is not a sales function – we are a mix of engineering, product, and customer architects who contribute to the core Baseten codebase, drive large portions of our feature roadmap, and execute on complicated customer engagements. You will also partner with product, infrastructure, and other customer engineering teams to ensure that large language models (LLMs) and other generative AI systems deliver best-in-class performance, reliability, and cost efficiency in production environments. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Leadership & Team Management Lead, mentor, and grow a team of Forward Deployed Engineers, providing guidance on technical direction, project execution, and professional deve

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: 5+ years of engineering experience running production infrastructure at a large scale Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters Experience with Kubernetes dev and production coding and support Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving Experienc

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. Our Industrial Compute organization develops and deploys large-scale AI campuses designed to support the next generation of frontier model training and inference workloads. The Hardware Operations team is responsible for ensuring the reliability, availability, and lifecycle health of OpenAI’s compute infrastructure. We partner closely with Data Center Operations, Fleet Health Engineering, Manufacturing, Network Infrastructure, Capacity Planning, and our infrastructure partners to maintain world-class operational performance across rapidly expanding AI environments. As we scale globally, we are building the operational frameworks, reliability standards, and sustaining engineering practices required to support thousands of GPUs and servers across multiple campuses. About the Role We are seeking a Datacenter Hardware Technician Lead to serve as the senior on-site technical authority for hardware reliability and fleet health at one of OpenAI’s flagship AI campuses. This role operates at the intersection of hardware operations, sustaining engineering, and fleet reliability. You will partner closely with Cloud Service Provider operations teams, OpenAI fleet-health engineers, hardware engineering teams, and OEM vendors to identify, diagnose, and resolve hardware issues affecting production systems. Beyond day-to-day operational support, you will drive root cause investigations, reliability improvement initiatives, lifecycle management programs, and operational readiness efforts. You will help establish hardware maintenance standards, operational procedures, and best practices that scale across future OpenAI infrastructure deployments. The ideal candidate combines deep hands-on datacenter hardware expertise with strong troubleshooting, failure analysis, and cross-functional leadership skills. Candidates must be able to sit onsite at our

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: Baseten’s Model Performance (MP) team is responsible for ensuring the models running on our platform are fast, reliable, and cost‑efficient. As part of this team, you’ll focus on Model APIs — the infrastructure powering our hosted API endpoints for the latest open‑source models. This work spans distributed systems, model serving, and developer experience. You’ll join a small, high‑impact team operating at the intersection of product, model performance, and infra, helping to define how developers interact with AI models at scale. RESPONSIBILITIES: Design, build, and operate the Model APIs surface with focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling and multi-modal serving Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, implement custom CUDA operators, tune memory allocation patterns for maximum throughput and optimize communication patterns across multi-GPU setups Productionize performance improvements across runtimes with deep understanding of their internals: speculative decoding implementations, guided generation for structured outputs, custom scheduling and routing algorithms for high-performance serving Build comprehensive benchmarking frameworks that measure real-world performance across different model architectures, batch sizes, sequence lengths, and hardware configurations Productionize performa

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity As an Applied Scientist specializing in Small Language Models and AI Training, you will lead research and development efforts focused on building efficient, high-performance language models tailored for practical applications. You will work closely with research, engineering, and product teams to advance model training techniques, optimize architectures, and scale AI solutions. Your work will directly contribute to AI systems that are safe, interpretable, and impactful across diverse usage scenarios. What You’ll Do Lead research and development of novel training methodologies and architectures for small and efficient language models. Design, implement, and evaluate model training experiments to improve performance, robustness, and generalization of language models. Collaborate closely with research scientists and engineers on scalable training pipelines and model deployment strategies. Develop techniques for model compression, fine-tuning, and domain adaptation to optimize models for real-world applications. Ensure AI safety, fairness, and alignment principles are integrated into model training processes and evaluat

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collecti

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll set technical direction for the primitives that other teams (filesystems, training, sandboxes) build on, balancing durability, latency, throughput, and cost. You'll own the roadmap from today's hardest problems (garbage collection at petabyte scale, active-active replication, rate limiting that protects the upstream without wasting ut

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 Manager (Player & Coach) of the Solution Architect team, you will lead and mentor a team of Solution Architects who will partner closely with Sales and customers to translate business needs into technical solutions, run technical discovery, and guide repeatable deployments and proofs of value for customers. Applying both hands-on technical ownership and managerial leadership, you will guide your team through the processes of owning discovery calls, demos, technical scoping and driving POC’s through to execution as well as designing, deploying, and managing high performance, low latency AI applications on Baseten’s platform. You will also partner with product, infrastructure, and other customer engineering teams to ensure that large language models (LLMs) and other generative AI systems deliver best-in-class performance, reliability, and cost efficiency in production environments. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Forward Deployed Engineering team: Forward Deployed Engineering on the frontier of AI The fastest, most accurate Whisper transcription Deploy production-ready model servers from Docker images Deploy custom ComfyUI workflows as APIs RESPONSIBILITIES Leadership Lead, mentor, and grow a team of Solution Architects, providing guidance on technical direction, project execution, and professional development. Set clear goals and ensure timely, high-quality d