Staff Principal Ai Engineer Jobs

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ full-stack engineers to shape purchasing experiences and monetization capabilities across OpenAI products. You’ll work across web experiences, product APIs, and shared components, combining strong product judgment with technical depth. The work ranges from improving checkout conversion and performance to enabling new pricing models, offers, and ways for customers to purchase our products. You’ll help identify opportunities, turn ambiguous goals into concrete technical plans, and lead initiatives from exploration through launch. As patterns emerge across products, you’ll develop reusable capabilities that make future launches faster and more consistent. This is a hands-on technical leadership role with substantial ownership over architecture, implementation, and product outcomes. This role is based in San Francisco, with three days per week in the office. In this role, you will: Architect and build purchasing experiences end to end, from frontend interactions through the product APIs and backend integrations that support them. Improve checkout conversion, performance, and reliability through experimentation, product analytics, and customer insights. Develop shared checkout components and monetization capabilities that support new products, pricing models, offers, and distribution channels. Partner with Product, Design, Growth, and Data Science to

NOTE ON ELIGIBILITY : this role is for industry candidates already working in software engineering for the past 1+ years. New grads and current students should NOT apply to this role (instead, visit pplx.ai/newgrads ). About the role In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, through Search, Comet, and Computer. Product Engineering owns those experiences end to end, from the interface a user touches to the search and model calls behind it, on top of roughly 200M queries a day and a 200B+ URL index. This is a full stack role in the truest sense. There are no frontend or backend lanes here, and no one waits for a ticket before starting. It suits people who love to build and want the room to do it. What you have shipped and how quickly you learn tell us far more than years on a resume or where you went to school. What you will do Own a user-facing surface end to end, from the interaction, design, and frontend through the application logic, APIs, data models, and the search or model calls behind them. Ship to production continuously. New engineers typically have code in front of users in their first week. Build with AI as a primary tool, not a novelty. We expect you to use agents and coding models aggressively to move faster, and to have sound judgment about when their output is wrong. Turn ambiguous product ideas into working prototypes, then use real usage data and evals to decide what survives. Raise the quality bar on reliability, latency, and craft for the surfaces you own. Work directly with designers, PMs, and research engineers, without unnecessary process in between. What we look for 1+ years of professional software engineering experience, or a track record of strong internships where you shipped production code at scale. Strong in at least one backend language, such as Python or Go, with real experience across services, APIs, and relational data m

The Chief of Staff is a high-visibility leadership role responsible for the operational success of the SVP, General Manager’s organization. Acting as a strategic partner, you will ensure the business operates at peak velocity by driving key initiatives, improving organizational effectiveness, and aligning teams around strategic priorities. You will translate high-level goals into clear execution plans across the business, providing clarity in a fast-paced, complex environment. This role is designed for a seasoned operator who excels at driving accountability among senior leaders and building the systems necessary to scale a SaaS business. You will identify operational gaps, mitigate risks before they impact the bottom line, and act as an extension of leadership—prioritizing, executing, and communicating critical projects to enable the executive team to operate at maximum efficiency. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 5 days a week. ** As a Chief of Staff You Can Expect: Drive the Operating Cadence: Design and manage the GM's leadership meetings, QBRs, and planning cycles to keep the team aligned and hitting KPIs. Force Execution: Partner with Sales, Customer Success, Account Management, Implementation, Product leaders to unblock projects and hold senior stakeholders accountable for deliverables. Own Plan Integrity: Keep the team aligned to the quarterly and annual plan, hold leaders accountable for the commitments behind it, and flag risk early, before it shows up as a miss in the business review. Drive Alignment & Follow-Through: Ensure decisions and commitments made in leadership meetings are clearly communicated across the team, tracked to completion, and actually followed through on, closing the loop between what was decided and what gets done. Prioritize Ruthlessly: Act as a surrogate for the GM in high-level meetings, surfacing critical risks early and filtering out noise to focus

Perplexity is seeking an experienced Machine Learning Research Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. Responsibilities Relentlessly push search quality forward — through models, data, tools, or any other leverage available Architect and build core components of the search platform and model stack Design, train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models Conduct advanced research in representation learning, including contrastive learning, multilingual, and multimodal modeling for search and retrieval Deploy models — from boosting algorithms to LLMs — in a scalable and performant way Build and optimize RAG pipelines for grounding and answer generation Collaborate with Data, AI, Infrastructure, and Product teams to ensure fast and high-quality delivery Qualifications Deep understanding of search and retrieval systems, including quality evaluation principles and metrics Proven track record with large-scale search or recommender systems Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models Expertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applications Strong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR) Self-driven, with a strong sense of ownership and execution Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron in Boise, Idaho has a current need for a Senior or Staff R&D Photolithography Materials Engineer . Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As an R&D Photolithography Materials Engineer at Micron Technology Inc., we are responsible for photolithography material selection and optimization for advanced memory devices. In this position, you will develop new technology and photo materials that meet device requirements and integrate new technology into manufacturing processes. This work could include photo materials for any photo processes including hardmasks and resists for I-line (365nm) through EUV (13.5nm). Additionally, you will address process and materials issues with pilot manufacturing and work on continuous improvements for manufacturability. Job Responsibilities: Lead long-term resist screening projects. Define success criteria with process owners, evaluate multiple rounds of design of experiments (DOEs) with suppliers, and identify top materials for detailed evaluation on devices in technology development. Broad knowledge and experience in photoresist chemistry with an ability to direct material optimization and development with our suppliers Work in a cleanroom, follow safety proc

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Member of Technical Staff (MTS) – 3D NAND Process Integration Job / Role Summary The role drives advanced 3D NAND technology pathfinding and process integration within the Advanced NAND Technology team in Singapore. It leads the translation of device concepts, materials, and process architecture into validated, manufacturable technology solutions. The position coordinates end-to-end development from concept through technology validation, applies data-driven, AI-assisted, and model-based methods to resolve complex scaling challenges, and collaborates across Device, Probe, Test, Design, and Operations to improve performance, yield learning, execution, and future-node roadmap readiness. Main Responsibilities Lead 3D NAND integration, pathfinding, and advanced architecture enablement in support of the technology roadmap. Drive end-to-end technology development from concept through validation, including learning vehicles, chara

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 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 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 own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), 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 top of it, whether that is a kern

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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), 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 collection over billions of objects. You'

1KOMMA5° At 1KOMMA5° , we pursue a clear vision: Living on wind and sunlight forever for free . To make this a reality, we are building the energy system of the future with Heartbeat AI. Want to be part of it? We bring together regional craftsmanship and scalable software: We don't think of solar, batteries, heat pumps, and e-mobility as isolated components, but control them as an intelligent, integrated overall system in our virtual power plant. Directly connected to the electricity market – in real time, fully automated. This way, energy is used when it is available from renewables and particularly cost-effective. By 2030, our goal is to transition 1.5 million households to renewable energies. Over 3,000 people are working towards this every day, at more than 80 locations worldwide, from Finland to Australia. Want to take responsibility and build solutions that truly matter? Apply now and help us shape the energy world of tomorrow. Learn more about our Product & Tech team! Deine Position Heartbeat AI is our energy optimisation platform that always provides our customers with the cleanest and cheapest energy. As Chief of Staff to the Go-to-Market Director, you are the operational backbone that keeps the go-to-market engine running at full speed across all markets. You own the details, the data, and the day-to-day execution, freeing the Go-to-Market Director to focus on strategy and the bigger picture, while you make sure nothing falls through the cracks. You own the operational rhythm of the Go-to-Market Director's agenda, translating strategic priorities into concrete plans, timelines, and next-day action items. You track performance data and KPIs across all markets, spotting issues early and surfacing clear, decision-ready insights before being asked. You bring structure to ambiguity, designing the project management architecture, systems, and processes that keep complex, multi-market initiatives moving without anything getting lost. You proactively identify what

CSQ128R3 The Senior Staff Enablement Partnership Lead is a strategic, mission-critical leadership role responsible for scaling and accelerating Databricks’ customer enablement business through a global partner ecosystem. This role owns the end-to-end global partnerships activation, from strategy on expanding partnership models and commercial offerings to enabling our partners and setting the operational and quality standards that ensure non-linear learner and training revenue growth. Its mandate is to accelerate the growth of users with Databricks skills and certifications while materially scaling the practice toward its multi-year objectives. Reporting into the Global Customer Enablement Practice, you will serve as the global single-threaded owner for the partnership models, working across Learning Curriculum and Delivery, Legal, Finance, Commercialization, Regional Customer Enablement and GTM Enablement to bring the strategic vision to life. The impact you will have: Strategy and Program Design: Drive the multi-year partnership vision and strategy with an opinionated, benchmarked point of view and stretch targets, and develop programs to bring the strategy to life with appropriate architecture and governance. Global Operating Model and RoE: Establish the global operating model and rules of engagement (RoE) with partner leadership to minimize cross-regional channel conflict (with regional adjustments), and define audit mechanisms and quality metrics for engagement excellence. Offering, Commercialization and GTM: Own the SKU structure, pricing, and commercial terms for partner products, along with the global GTM framework to drive partner-influenced learners and training revenue. Partnership Enablement Standardization: Lead end-to-end enablement programs for global partners—including curriculum, certification, and readiness—ensuring flawless execution, adherence to rules of engagement, and consistent high-quality engagements. Cross-Functional Align

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join our team as a Senior SSD Firmware Lead / Architect and help define the future of data storage. In this role, you will lead the architecture and development of firmware for our industry-leading DirectFlash™ SSD Modules, which power Pure Storage platforms used by both enterprise and hyperscale customers. You will work closely with hardware engineers, controller vendors, and systems teams to design firmware architecture, bring up new hardware platforms, and improve performance and reliability. WHAT YOU'LL DO Define and drive the firmware architecture for next-generation DirectFlash™ SSD modules, including subsystem design, firmware modularization, and system integration. Work with controller vendors and hardware teams to bring up new SSD controller SoCs and enable features such as PCIe, NAND interfaces, power-loss protection, and telemetry. Develop firmware components supporting NVMe and OCP SSD specifications, ensuring compliance, performance, and interoperability. Debug complex cross-layer issues involving firmware, controller hardware, NAND media, and host systems. Improve SSD data path performance and latency through firmware design and analysis. Review designs, mentor engineers, and improve development tools, testing, and automation. WHAT YOU BRING Extensive experience developing SSD firmware for enterprise or hyperscale systems, with strong knowledge of SSD architecture and controller design. Solid underst

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pipeline Engineering team at Everpure™ as a Full Stack Software Engineer to build and scale the pipeline visibility layer for FlashArray, FlashBlade, and Hyperscale — the core platform through which engineers and customers understand and act on CI results . In this high-impact position, you will own responsive web interfaces, API gateway architecture, and AI-assisted workflows that convert raw pipeline data into actionable signal, eliminating operational toil across our engineering organization. WHAT YOU'LL DO Build the Pipeline Visibility Layer: Architect and ship high-performance web applications using modern JavaScript/TypeScript frameworks to deliver real-time pipeline status, test results, and failure analytics at enterprise scale. Own Gateway & Backend Services: Develop and operate low-latency API gateways and backend microservices using typed systems languages (such as Go or Rust) to aggregate data across systems, enforce strict multi-tenant boundaries, and maintain reliable system contracts. Deliver Secure Access Controls: Implement robust authentication and authorization protocols (OAuth2/OIDC, SSO, RBAC) to ensure internal teams and external customers experience seamlessly scoped and fully audited access. Integrate AI Triage Workflows: Engineer retrieval-augmented generation (RAG) pipelines and LLM integrations over test metadata and failure logs to automate root-cause summaries, flak

Perplexity is looking for a highly skilled Expert Systems Engineer to join our Search Core team. For the indexing and data processing stream. This role is critical to building next-generation search products and technologies. Responsibilities Design and build core search engine components, especially indexing pipelines, data storage formats that operate at the scale of billions of pages Develop streaming and batch data processing with YT systems for search index construction in a high-load environment Push the limits of hardware performance through low-level optimizations and systems-level tuning Tackle challenges in multithreading, concurrency, and system-level optimization Design and build core search engine components, including indexing pipelines, retrieval algorithms, and ranking systems that operate at the scale of billions of pages Develop streaming and batch data processing systems for search index construction in a high-load environment Push the limits of hardware performance through low-level optimizations and systems-level tuning Tackle challenges in multithreading, concurrency, and system-level optimization Qualifications 3+ years of hands-on experience in systems programming (Rust, C++, C, or similar) Ownership of full project lifecycle you don't just write a fast inner loop, you care about how the system is built, deployed, operated, and scaled in production Knowledge of Python or other scripting languages Knowledge of Data processing systems (YT/Kafka/Hadoop) Passion for writing clean, efficient, and scalable systems-level code Strong knowledge of algorithms and data structures, and the ability to apply them effectively Deep understanding of multithreading, including various approaches, challenges, and trade-offs Experience building high-load, distributed, and hardware-adjacent services Solid understanding of Linux internals (syscalls, networking stack, memory model, kernel tuning) Familiarity with low-level optimization techniques (memory management,