Stock Yard in United States

We’re looking for a Marketing Operations Manager to strengthen the systems, reporting, and operational foundation behind our go-to-market motion. You’ll help our teams move with cleaner data, more reliable workflows, and clearer visibility into pipeline performance. You’ll work across Marketing, Sales, and RevOps to improve routing, automation, attribution, and reporting. This role is a good fit for someone who enjoys solving operational problems, building scalable processes, and turning data into better decisions. What you’ll do here Own and improve lead routing workflows, including routing logic, SLAs, data quality, and handoff reliability. Manage lead and marketing operational improvements across Salesforce, HubSpot, and the broader GTM tech stack. Audit CRM and enrichment data to keep systems clean, accurate, and useful. Reduce manual work through better workflows, automation, documentation, and QA. Evaluate and help roll out new tools that make the marketing tech stack simpler and more scalable. Partner with Sales and RevOps to evolve systems as the business grows. Support recurring and ad hoc Marketing reporting, including QBRs, campaign analysis, marketing team requests, and KPI dashboards. Improve visibility into pipeline and funnel performance by troubleshooting data discrepancies, refining attribution, and surfacing insights. What we’re looking for 4+ years of experience in Marketing Operations, Revenue Operations, or GTM Systems roles at B2B organizations. Strong hands-on experience with Salesforce and HubSpot, including workflows, data hygiene, and system troubleshooting. Experience managing or improving lead routing processes, including routing logic, SLAs, ownership rules, and handoffs. Experience with B2B funnel reporting, pipeline visibility, conversion tracking, or performance analysis. A strong execution mindset, with the ability to prioritize, document, and improve systems in a fast-moving environment. Strong attention to detail and clear cross-fu

As a Forward Deployed Engineer on the Feature Flags team, you'll partner directly with customers to accelerate their feature flag implementations — from initial architecture consulting through prototype builds to full-scale migrations. This role is for someone who wants to write code with customers, not just advise them. You'll work hands-on inside customer codebases to unblock complex, high-stakes deployments, directly influencing deal velocity and customer success. Working closely with Sales, Solutions, and Engineering, you'll be the technical force that turns a signed contract into a live, adopted implementation. What You'll Do: Serve as the hands-on technical partner for strategic customers implementing Datadog Feature Flags, from pre-sales technical validation through post-sales delivery Consult on flag architecture and implementation approach for complex environments — multi-service, multi-platform, high-scale deployments Build prototype flag implementations directly in customer codebases to prove value and de-risk technical decisions early in the sales cycle Implement flags across diverse and advanced deployment modes (server-side, client-side, edge, mobile, streaming/real-time) tailored to each customer's stack Drive full flag migrations to completion — including legacy system cutover — efficiently and with minimal customer engineering burden Identify patterns across customer implementations and feed them back to Product and Engineering to improve the core product and reduce future implementation time Collaborate closely with Engineering on technical edge cases, product gaps, and implementation tooling Partner with Sales and Solutions to accelerate deal cycles by removing technical risk and uncertainty Who You Are: 5 years of professional software engineering experience, with hands-on coding ability across the stack you're deployed into Experience with feature flagging, experimentation, or config management systems (internal or vendor) Comfortable dropping i

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Build Core Data Engineering Primitives at Cloud Scale Data pipelines are foundational infrastructure — when they're fast, correct, and maintainable, customers build on them with confidence. If you've spent the bulk of your career building large-scale data infrastructure — designing streaming or transformation primitives, reasoning hard about consistency and fault tolerance, and owning the systems that run under millions of customer workloads — this role might be for you. You'll be working on the streaming and transformation layer at Snowflake: the constructs that define how customers move, shape, and maintain data. AI has a real presence in this work — in how customers use these pipelines and in how we think about building them — but the core job is hard distributed systems engineering, and that's what we're hiring for. About the Team We build the core data engineering primitives that power Snowflake's streaming and transformation capabilities. From the constructs customers use to define real-time pipelines to the execution fabric that makes those pipelines reliable and cost-efficient at cloud scale, our team owns the full stack of declarative data engineering. We're a small, high-ownership team operating close to the product — which means your decisions ship, your architec

Salary range - $250k - $350k | Equity - up to 0.5% | In-person NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for a Research Engineer to own problems end to end across our models, inference service, and product. You won't just train a model and hand it off. You'll take it from training through benchmarking, into our inference stack, and work with the team to integrate it into our products. We're a small team that has shipped the current state of the art OCR model, Chandra. Our models collectively have 70k+ Github stars. Our tools are used internally at frontier AI labs like Anthropic, and Fortune 500 enterprises like Siemens. Our team focuses on training small, efficient models that outperform much larger LLMs on domain-specific tasks (like OCR, structured extraction, tables). We move fast, prioritize practical results, and build tools that are open, reproducible, and built to last. You'll test hypotheses quickly, iterate on results, and balance experimental rigor with shipping to customers. Day to day: A typical project might look like: identify a gap in extraction quality on long documents, train and benchmark a new model, optimize it for inference, and work with the team to ship it to users. Concretely: Train and evaluate models: Train task-

Salary range: $225k - $300k | Equity: 0.15% - 0.35% | In-Person: NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We’re looking for a fullstack engineer who wants to build the interfaces, tools, and infrastructure that help developers and enterprises use our models. You’ll work across the stack to shape how people interact with OCR, extraction, and document-understanding systems. That includes building core inference workflows, creating intuitive UI for complex parsing tasks, and improving the developer experience across our open-source repos and API. This is a high-ownership role that blends engineering, product thinking, and community engagement. You will work closely with the founders and the rest of the team to ship features, improve performance, and make our technology accessible to a global community of builders. As a small and fast-moving team, roles are fluid. You should enjoy working across backend, frontend, performance, and user-facing surfaces. Your work will directly influence how teams evaluate and deploy our models. Day to day, you will: Ship features to our open source repos, API, and internal tooling. Design and build frontend features that make document parsing more interactive and understandable. Optimize inference performance and improve th

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. Role Overview We are seeking an experienced ASIC Package Signal Integrity / Power Integrity Engineer to drive electrical architecture, modeling, optimization, and validation for the most advanced AI/HPC silicon and package design. This role focuses on high-speed SerDes and memory channel architecture, advanced 2.5D/3D package SI/PI, substrate to package co-design, power-delivery-network optimization, electromagnetic modeling, and simulation-to-measurement correlation. The ideal candidate has strong hands-on experience with high-speed channel and PDN analysis across ASIC packages, interposers, substrates, and power-delivery structures, and can translate simulation results into practical design requirements for interposers and package substrate design optimization. The engineer will work closely with ASIC, package, system, mechanical, thermal, power, and silicon validation teams from early architecture and feasibility studies through production bring-up. In this role you will Own SI/PI architecture and analysis for advanced AI ASIC packages from early feasibility studies through production. Develop and optimize high-speed electrical channels for 200G/400G SerDes, PCIe, HBM, DDR, and chiplet/die-to-die interfaces. Perform package, interposer and substrate modeling using 2D/3D electromagnetic solvers. Define and optimize package stack-ups, transmission-line structures, via transitions, breakout structures, return paths, ground shielding, bump maps, and ball maps based on SI/PI re

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. The Game Engine team at Roblox works on the systems that power the experiences at the heart of the metaverse. Our code is the technical foundation in our client, editor, and our simulation servers. The Game Engine team is broadly split into departments — Audio-Video-Communication, Avatar, Core AI, Digital Matter, Productivity, and Systems. This position is for the Systems Runtime pod. The Runtime pod builds and maintains the foundational C++ components that power the entire Roblox engine and Studio stack. We own the runtime layer — the performance, efficiency, and usability of the core primitives that every other engineering team relies on. Think of Runtime as the “standard library” and execution engine for Roblox's C++ world. Our ownership centers on three pillars: Concurrency System — our task scheduler and fiber runtime power how work is parallelized across CPU cores, letting teams scale features across platforms while keeping code understandable and debuggable. Memory System — we own the engine's memory allocator stack, tracking pipelines, and observability tooling to make memory behavior predictable and prevent leaks and fragmentation. Profiling and Observability — we build and evolve

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. OVERVIEW Every year, people across the world spend nearly one trillion dollars on groceries. But food is more than sustenance — it's identity, ritual, culture, and care. The way we eat shapes our health, our routines, and our relationships. Yet for most people, translating a desire to eat better or live healthier into actual, lasting habit change remains hard. The Instacart Consumer team is at the forefront of reimagining how people relate to food at home. We're building new product experiences around meals, nutrition, and health that go beyond the transaction — helping people discover what to cook, build routines that stick, and feel confident in the choices they make for themselves and their families. As a Staff Researcher on the Consumer team, you will shape the foundational understanding of how and why people change (or struggle to change) their food behaviors.

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Staff Network Engineer Location: MPK/Bellevue/Dublin Snowflake's Enterprise Technology Network Services team is looking for a Senior Network Engineer to lead the design, operation, and optimization of our Zero Trust and secure-access platform. This role is Zscaler-centric — you will own the health, performance, and roadmap of our ZIA/ZPA deployment — while working across a modern, multi-cloud network stack that supports a global workforce of 10,000+ users. You'll be the escalation point for the most complex connectivity issues and a driver of automation and observability across the environment. What You'll Do Own and operate the Zscaler platform (ZIA, ZPA, ZDX, ZCC) end-to-end, including policy frameworks, app-segmentation models, PAC/traffic-forwarding standards, App Connector topology, and NSS/log-streaming design. Troubleshoot secure-access incidents like tunnel flapping, broker/connector health, SSL inspection edge cases, DNS/DTLS failures, and lead root-cause analysis for systemic issues. Manage Palo Alto firewalls, Panorama and GlobalProtect VPN, while planning migration toward Zscaler solutions. Support Aruba (Central) Wireless, Ekahau and Cisco Catalyst switches globally. Design, install, and configure network devices and ISP circuits at new offices. Build automatio

About the Team OpenAI's Enterprise team builds AI-powered enterprise products and shared platform capabilities that help organizations put advanced AI to work securely and at scale. Our work spans enterprise workflows, agent experiences, integrations, identity, administration, security, governance, and deployment. About the Role As a Technical Program Manager on Enterprise, you will lead the technical strategy and execution behind the products and shared capabilities that make ChatGPT, Codex, and future OpenAI products useful, secure, and scalable for organizations. You will translate customer needs, competitive dynamics, and product priorities into actionable plans, influence architectural direction, and deliver durable capabilities across application, platform, and infrastructure layers. The role requires deep technical fluency, strong product judgment, and the ability to move between hands-on execution and broader enterprise strategy. 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: Drive technical strategy and execution for enterprise product and AI workflow initiatives, from design through implementation, launch, customer rollout, and iteration. Partner with engineering teams to influence architectural direction, interface definitions, and implementation tradeoffs across full-stack products, APIs, integrations, and shared platform systems. Translate enterprise customer requirements into actionable product priorities across AI-powered workflows, agent experiences, integrations, permissions, data access, evaluations, identity, security, governance, and deployment readiness. Represent the needs of enterprise buyers, IT administrators, security teams, business leaders, developers, and end users in product and technical decisions. Identify adoption barriers, competitive gaps, and opportunities to make OpenAI products easier for organizations

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Risk Operations Technology Enablement team sits within the Risk Operations org and is responsible for partnering across Risk teams to shape the technical infrastructure that enables us to scale our Risk operations and achieve our dual goals of preventing bad actors from exploiting Stripe’s systems and delivering an exceptional user experience for legitimate users. More specifically, our team partners with Risk product and engineering teams to identify, scope, prioritize, pilot, and roll out technical infrastructure and tooling improvements to protect Stripe and serve our users. From the application of AI to our reviews, to agent diagnostic and resolution tools, to review and support case routing, to our user-facing risk support surfaces, our team’s mandate is expansive and a major lever in both protecting Stripe and its users from risk as well as improving the user experience. What you’ll do You’ll lead and develop a high-performing team of Engineering Program Managers who deliver technical programs with step-change impact for Stripe. You’ll build strong partnerships and operating mechanisms with Risk Engineering and Product, co-develop the strategy for Risk’s technical infrastructure grounded in a deep understanding of the Risk technology stack, and own mission-critical technical processes (e.g., Risk Ops tooling-stack prioritization). Responsibilities Shape and drive alignment on Risk Operations’ technical strategy that enables us

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 Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

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