Technical Support Expert 2 in United States

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're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo

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’re looking for strong engineers with experience building developer tools that users love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful interfaces that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python libraries with broad user-bases, ideally including some experience maintaining open-source software. Knowledge of advanced Python features, especially async programming. A strong product sense that manifests as a focus on developer ergonomics and productivity. A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our NYC or Stockholm office. Any of the following would be a plus:

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're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

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: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

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're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. Over the past years, Linear has experienced incredible organic growth and has become an instrumental tool for many of the world’s best product teams. We believe customer support should always feel like an extension of that experience. As a Product Support Specialist at Linear, you’ll contribute to the future of our product by surfacing customer feedback and insights, contributing to our technical documentation, and engaging a technical customer community via social channels. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based within U.S. and Canada Pacific or Mountain Time. You can work from anywhere within those time zones. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you’ll do Support customers in end-to-end engagement, including onboarding, account setup, debugging issues, feature and integration discovery Investigate and resolve inbound customer issues reported through all communication channels, including email, Slack, Twitter, and Reddit Partner with our engineering team to document and reproduce bugs Surface trends and insights from customer feedback to the team at large to inform product choices Lead select strategic projects to improve the support experience, inter

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. Our Talent team is looking for an experienced and discerning technical recruiter to help build Linear’s next generation of engineering talent. This is a hands-on, high-impact role for someone who sees recruiting as a craft. Your primary focus will be growing our engineering team in North America. You’ll work closely with engineering leadership and our existing recruiters across product, infrastructure, AI, mobile, and emerging technical roles. You’ll own the full search, from mapping talent markets and activating networks through assessment, work trial support, and close. Linear engineers tend to combine technical depth with product judgment, craftsmanship, and significant ownership. Finding them requires more than matching resumes to requirements. We’re looking for someone who can recognize these qualities, reach candidates with precision, and continually sharpen their judgment through close partnership with our team. All recruiters at Linear are generalists and may support other functions as company priorities evolve, but engineering will be the primary focus of this role. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North American (Eastern time zone), with a strong preference for the New York City area. Being in New York enables closer partnership with our growing local team, c

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. At Roblox, we are growing and looking for a Technical Sourcer (short-term) to help build, scale, and influence our recruiting landscape. We are a fun and collaborative team focused on recruiting engineering talent. This person is a strong communicator, collaborator, and leads by example. Successful Builders embrace change and we encourage bringing in fresh ideas and a culture of feedback. You will directly impact the growth of the company and support our scaling efforts. The role is 6-12 month, with extensions possible depending on performance and business needs. We follow a hybrid schedule out of our San Mateo office, requiring in-office presence Tuesday–Thursday. You Will: Partner closely with Roblox recruiters and business leaders to deeply understand each team’s goals and talent needs, then identify, attract, and engage top candidates who will drive our mission forward Proactively source and engage top talent through Gem, LinkedIn Recruiter, SeekOut, and other platforms Influence and improve processes to help the team work smarter, faster, and at scale Share talent market insights with hiring managers to guide decisions on leveling, compensation, and candidate profiles Mentor and coach

We are Datadog’s in-house technical leaders. The Technical Account Management team drives Datadog’s continued global growth by ensuring our customers realize long-term value from our platform through successful adoption, expansion, and partnership. As a Manager 1 in Technical Account Management, you will lead and develop high-performing technical teams while influencing strategy, execution, and outcomes across customers, internal partners, and the broader organization. Manager 1 leaders at Datadog are people-first managers, trusted collaborators, and operational owners. You will coach and mentor individual contributors, drive execution against team and organizational goals, and serve as a strong voice for customer needs and technical excellence. At Datadog, we place value in our office culture; the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead and coach a team of up to 6 Technical Account Managers, providing regular 1:1s, team meetings, and bi-annual performance feedback Own and track team KPIs , including scheduling, utilization, productivity, and delivery outcomes Partner closely with Sales, Customer Success, Presales, Product Management, Support, and Marketing to align post-sales strategy and execution Lead and participate in customer-facing engagements when appropriate, including escalations, strategic reviews, and key account discussions Drive account strategy discussions focused on product adoption, expansion, and services delivery Actively participate in recruiting , hiring, and onboarding efforts across your team and the broader organization Gather and synthesize customer feedback to influence product direction, process improvements, and internal initiatives Lead multiple OKR initiatives annually , coordinating and delegating efforts across your team Demonstrate thought leadership by identifyi

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb's mission is to create a world where people can Belong Anywhere. As we grow to achieve that mission, we're looking to add a technical, hands-on, and mission-driven Senior Manager of Technical Program Management (TPM) for the Infrastructure team to lead AI Platforms initiatives spanning Search Relevance, Machine Learning Infrastructure (MLI), and Search Knowledge Infrastructure (SKI). This person will partner with our engineering & product teams to build/enhance data-driven decision making across multiple areas in Airbnb. They will partner closely with senior ICs and engineering directors across Airbnb on processes, strategy and execution. In this role, you will collaborate closely with the Machine Learning (ML) engineers, infrastructure engineers and product managers from across Airbnb to develop holistic solutions that ensure a vibrant and equitable marketplace. The Search Relevance, Machine Learning Infrastructure (MLI), and Search Knowledge Infrastructure (SKI) teams power the ranking, recommendations, model infrastructure, and search intelligence capabilities that make up a core part of Airbnb's AI Platforms, including: Search Ranking for Stays, Experiences, and Services, Home Page Recommendations, Search Bar AutoSuggest and Autocomplete, Marketing Technology, and the ML infrastructure and platform capabilities that support them. The team also creates the fabric for personalization and the underlying model infrastructure, used both on and off platform for Airbnb. We collaborate with many teams including Search Infrastructure, Guest and Host Experiences, MD

About the Team The Industrial Compute team is responsible for building the physical infrastructure that powers OpenAI’s largest-scale AI systems. We design, deploy, and operate next-generation compute infrastructure across a rapidly expanding global footprint, combining OpenAI-owned infrastructure with strategic cloud and infrastructure partners to support frontier AI workloads. As our infrastructure footprint grows, operational excellence across third-party providers becomes increasingly critical. Our team ensures external infrastructure partners consistently deliver the reliability, performance, and operational maturity required to support OpenAI’s rapidly expanding compute environment. About the Role We are seeking a Hardware Technical Program Manager, Infrastructure Partner Operations to lead operational delivery across OpenAI’s third-party infrastructure partners, including major cloud service providers and strategic compute vendors. In this role, you will serve as the primary operational program manager for external infrastructure partners, driving accountability for service delivery, operational readiness, incident management, performance reporting, and continuous operational improvement. You will work closely with partner engineering and operations teams while coordinating internally across Hardware Engineering, Infrastructure Operations, Capacity Planning, Networking, Supply Chain, Deployment, Reliability Engineering, and executive leadership. Success in this role requires someone who understands how hyperscale infrastructure organizations operate, can establish strong operational governance with external partners, and is comfortable driving complex technical programs without direct ownership of the underlying infrastructure. Key Responsibilities Own operational engagement with third-party infrastructure providers, ensuring consistent execution against operational commitments, service-level agreements (SLAs), and performance expectations. Develop operationa

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

About the Team The Stargate organization is responsible for building and scaling the physical infrastructure systems that power OpenAI’s next generation of AI training and inference platforms. This includes the manufacturing, deployment, and operational execution required to bring large-scale compute infrastructure online globally. The team operates at the intersection of data center infrastructure, hardware manufacturing, supply chain, deployment operations, and systems planning. We partner closely across Infrastructure Strategy, Manufacturing Operations, Capacity Planning, Supply Chain, Deployment, and Engineering to execute one of the largest infrastructure scale-outs in the industry. About the Role We are seeking a Technical Program Manager, Rack Delivery to drive operational execution across rack manufacturing, site readiness, and deployment coordination for Stargate infrastructure programs. This role will serve as a key connective layer between manufacturing partners, deployment teams, and infrastructure readiness programs to ensure rack production and delivery timelines remain aligned with site availability and deployment sequencing. You will help manage operational execution across contract manufacturers (CMs), support build planning and RCCA processes, and coordinate deployment readiness across multiple concurrent infrastructure programs. You will also partner closely with Demand Planning teams to translate strategic planning inputs into actionable SKU-level manufacturing and delivery schedules. This role is ideal for someone who thrives operating across ambiguity, manufacturing operations, infrastructure deployment, and large-scale cross-functional execution. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation support. Key Responsibilities Drive cross-functional coordination between rack manufacturing, deployment operations, and site readiness programs. Manage operational execution acros

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: We’re looking for a Technical Enablement Manager to own the end-to-end learning, knowledge, and training experience for Notion’s global customer experience (CX) teams—spanning onboarding, change management, and continuous learning. This is an opportunity to build, lead and innovate on programs that ensure customer-facing support teams have the knowledge, skills and processes they need to consistently deliver high-quality support experiences to Notion customers. You’ll set the enablement strategy, partnering closely with CX leadership and cross-functional partners to identify skill, knowledge and process gaps, and translate those needs into durable enablement solutions—content, workflows, and programs. This role is based in New York City, USA. 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: Own end-to-end CX enablement for a business vertical: define learning outcomes, readiness expectations, and content strategy across