Technical Sourcer in United States

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog makes products self-driving . It's the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Desktop , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change wh

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

We are seeking an exceptional, technically strong, and highly motivated Technical Product Manager to drive NVIDIA's healthcare Physical AI simulation platform. This is a rare opportunity to build foundational enabling technologies at the intersection of physical AI, robotics, simulation, and healthcare, redefining how leading healthcare device and robotics companies develop, train, evaluate, and deploy next-generation Physical AI systems. What You'll Be Doing: Bring innovative physics simulation to healthcare . Identify and integrate advances in physics simulation into enabling technologies that empower healthcare developers to build and validate solutions across robot learning, in-silicon product development, and in-silicon clinical trials—without owning the end applications themselves. Define the product vision and strategy for healthcare Physical AI simulation , spanning classical physics-based and generative simulation, and enabling developers to tackle some of the hardest challenges in healthcare on the path toward Physical AI and in-silicon product development. Develop PRDs with clear technical requirements, benchmarks, product metrics , and evaluation frameworks for simulation fidelity, scalability, policy performance, sim-to-real transfer, and developer efficiency. Lead cross-functional execution across research, engineering, product, developer relations, marketing, and business development to bring new simulation capabilities from research into open-source releases and production adoption. Drive early-access partnerships with healthcare developers, including robotics OEMs and MedTech companies. Translate partner requirements and feedback into detailed platform features and work closely with engineering to deliver them. Help build the horizontal NVIDIA

About the Team OpenAI's Industrial Compute organization builds and operates the infrastructure required to train and serve frontier AI models. The Capacity Planning team connects rapidly changing research and product demand with the compute, networking, storage, power, data center, hardware, and operational resources required to make that demand executable. About the Role We are seeking a Technical Program Manager to build and lead capacity planning across OpenAI's large-scale AI infrastructure. You will translate uncertain workload demand into clear infrastructure requirements, allocation decisions, supply commitments, activation priorities, and long-range capacity strategies. This role sits at the intersection of research, engineering, infrastructure, finance, sourcing, deployment, and operations. You will create the planning models, operating cadences, governance mechanisms, and source-of-truth systems that allow teams to understand what capacity is required, what is available, what is at risk, and what decisions must be made. This is not a finance-only forecasting or reporting role. Success requires technical fluency across the infrastructure stack, strong analytical judgment, and the ability to move consequential decisions forward when requirements, timelines, and supply conditions change quickly. Key Responsibilities Own capacity-planning processes across near-term workload allocation, quarterly execution, and longer-range infrastructure horizons. Translate research, training, inference, and product demand into compute, accelerator, cluster, networking, storage, rack, power, and site requirements. Develop scenarios that make assumptions, confidence levels, constraints, sensitivities, and decision points explicit. Reconcile requested demand against contracted, delivered, installed, activated, and workload-usable capacity. Partner with research and engineering teams to understand workload priorities, technical dependencies, utilization patterns, and changing req

About the Team The Product & Platform teams at OpenAI are responsible for delivering the company’s most impactful offerings—such as ChatGPT, our API platform, and new enterprise capabilities—to a global and diverse customer base. These systems must perform at scale and deliver exceptional experiences to developers, consumers, and businesses alike. The ChatGPT engineering org builds and operates the systems that bring product improvements to users across backend services, web, mobile, and desktop platforms. The Developer Velocity team partners with product engineering, platform, infrastructure, reliability, engineering acceleration, and observability teams to make everyday development faster and releases safer, more predictable, and easier to operate. About the Role We are seeking a Technical Program Manager to improve developer velocity and deployment excellence across ChatGPT. You will lead durable improvements to local development, CI, testing, build systems, release trains, progressive rollout, and post-deployment validation. You will identify the highest-leverage sources of engineering friction, align teams around shared standards and metrics, and drive adoption of tooling and workflows that improve both speed and reliability. This role combines systems thinking, technical program leadership, and hands-on operating rigor across a broad engineering surface. 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 assistance to new employees. In this role, you will: Own the cross-functional roadmap for improving local development, CI, testing, build workflows, and release infrastructure. Create a durable intake and prioritization mechanism for developer friction, using evidence to focus teams on the highest-impact improvements. Lead programs that improve deployment speed and safety, including pre-merge confidence, progressive rollout, release guardrails, rollback readiness, and post-deploy valida

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:

Role Overview Sureify is looking for an organized, curious Technical Support Analyst to join our Client Support Services team. This role is for someone who wants to be at the intersection of client support, technical investigation, and operations. In today's evolving tech landscape, the most effective support professionals are multi-disciplinary — capable of bridging client business flows and internal technical execution. Your primary mission is to ensure that issues raised in multi-vendor environments are clearly understood, documented, and routed to the right teams. You are the technical translator who makes sure nothing is lost between what the client describes and what our engineers need to act on to resolve the issue. Key Responsibilities Multi-Vendor Triage & Translation: Participate in triage calls involving clients and 3rd-party vendors. Analyze reported issues and determine if the reported issue falls within Sureify systems or an external partner and direct the resolution path accordingly. Translate client discussions into clear, actionable tickets. Investigation and Analysis: Reproduce reported issues and establish what the data actually shows — querying database tables with SQL, reviewing application logs, and inspecting API responses — so every ticket you raise carries technical context an engineer can act on immediately. Global Coordination: Facilitate hand-offs with our India-based engineering teams, including occasional early-morning syncs to align overnight progress with US client priorities. Customer Operations: Take ownership of customer operations projects — support portals, professional services surveys — gathering requirements, defining scope, and delivering solutions for internal teams to run going forward. Internal Documentation Management: Design and structure our Professional Services Confluence sites. This includes organizing the site structure, maintaining page content, and keeping our internal "source of truth" accurate and easy to na

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. About the Role This role offers the exciting opportunity to leverage your technical expertise and leadership skills to drive programs that enhance our products, applications, platforms, and ultimately, the experiences of millions of customers, shoppers, and part

The Applications Development Technology Senior Lead Analyst is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology Team. The overall objective of this role is to lead applications systems analysis and programming activities. Responsibilities: Lead the architecture, design, development, and delivery of enterprise UI applications. Strong hands-on experience with Angular and Ext JS for developing scalable and responsive user interfaces. Strong experience with Java and Spring Boot for designing and developing backend services and APIs. Experience deploying, supporting, and troubleshooting applications in ECS/containerized environments . Define application architecture, technical standards, reusable components, and development best practices. Provide technical leadership to development teams, including design reviews, code reviews, performance optimization, and troubleshooting . Strong understanding of CI/CD pipelines , including automated build, testing, deployment, and release processes. Hands-on experience with GitHub , including source-code management, branching strategies, pull requests, code reviews, and integration with CI/CD pipelines. Strong knowledge of open-source technologies and frameworks , with hands-on implementation experience. Ability to evaluate and select appropriate open-source libraries, frameworks, and tools , considering security, licensing, maintainability, vulnerabilities, and enterprise standards. Drive application modernization, technical improvements, and adoption of engineering best practices. Work closely with architects, developers, infrastructure teams, product owners, and business stakeholders to deliver solutions successfully. Prov

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 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 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