Trade Operations Engineer in United States

Job Details: Job Description: The Role and Impact As a GPU Platform Hardware Design Engineer, you will play a pivotal role in designing and developing high-quality GPU hardware platforms that drive innovation in high-performance computing, graphics, and visualization technologies. You will lead the design process from initial feasibility studies through board layout, tapeout, and platform power-on, ensuring robust functionality and compatibility with industry standards. Your expertise in platform-level requirements, electrical engineering applications, and system bring-up will directly contribute to delivering cutting-edge GPU systems that accelerate Intel's leadership in computing. Business group The Data Center Group (DCG) is dedicated to advancing Intel's role in powering the digital world with leading-edge technologies. Focused on delivering innovative solutions for data center and cloud environments, DCG supports high-performance computing and graphics to enable capabilities such as AI, machine learning, and advanced visualizations. As part of the GPU IP Engineering team within DCG, you'll contribute to developing GPU systems that meet the evolving demands of the industry while supporting Intel's broader mission to create world-changing technology. Key Responsibilities - Design, develop, and evaluate electronic components, PCBs, and integrated circuits for GPU hardware platforms. - Translate platform-level requirements into detailed specifications and ensure adherence throughout the design process. - Define component placement and trace routing rules to optimize board layouts for performance, power, and signal integrity. - Conduct feasibility studies, board layout, tapeout, and platform power-on activities. - Perform functionality tests and utilize tools to verify platform configurations and compatibility. - Research, develop, and validate firmware, hardwa

VTS's Lease integrations connect our platform to the property management and accounting systems - Yardi, MRI, JDE, and others - that our customers run their portfolios on. When those integrations are healthy, data flows automatically and customers trust what they see in VTS. The Integrations and API Support Advisor owns the health of these integrations end-to-end - proactively monitoring for failures before customers notice them, and resolving the inbound requests that come in when something breaks or needs to change. Success in this role is simple to state and hard to deliver: every integration stays active, and customers can always rely on the integrity of the data VTS is showing them. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. ** What you can expect as an Integrations and API Support Advisor: At VTS, you'll join the Integrations Support team as a critical layer between our customers' source systems and the VTS platform. You'll: Own Integration Health : Monitor active Yardi, MRI, SAP, and custom API integrations for failures, stalled syncs, and missed feeds. Proactively identify and resolve issues - such as failed nightly imports, integrations stuck in "processing," or ETL files not arriving via SFTP - before they escalate into customer-reported problems. Resolve Data Integrity Issues : Investigate and fix discrepancies between VTS and source systems, including mismatched square footage, missing or duplicated leases, orphaned records, incorrect rent or lease terms, and unit/space mapping errors. Trace root causes across the integration pipeline rather than just patching symptoms. Manage the Customer Support Queue : Respond to and resolve inbound tickets covering the full integration lifecycle - API credential and access requests, asset archiving and disposition processing, source ID/BU remapping, stacking and site plan corrections, and MRI/Yardi version upgrades and migrations. Par

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a Design Verification Engineer to contribute to the unit-level verification of our RISC-V CPU front end—including instruction fetch, branch prediction, and surrounding fetch control structures. As a key individual contributor within our front-end DV team, you will focus on building testbenches, generating stimulus, and developing checkers for complex microarchitectural scenarios. This role is hybrid, based out of Austin, TX or Santa Clara, CA. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Front-End Experience: Solid background verifying CPU front-end blocks—such as instruction fetch, branch predictors (BTB, TAGE, RAS), instruction caches/TLBs, or decode—using SystemVerilog, UVM, and C++. Unit-Level Focus: Hands-on experience building clean, controllable unit testbench environments with precise stimulus and checking. Reusable Design: Pragmatic approach to building transactors, predictors, and scoreboards that can be reused across verification levels. Collaborative Problem Solver: Comfortable working alongside RTL designers to trace and fix misspeculation, redirect, and edge-case fetch bugs. What We Need Unit-Level Verifica

Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have a presence across the US and Europe including New York, Dublin, Seattle, Palo Alto, and Chicago. We support office-based and remote work and align projects with convenient work hours for each time zone. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. ​​This role can be based out of our US offices or remotely in the North America region. Candidate Profile 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema d

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We’re building the observability product for OpenAI—from scalable infrastructure to a rich, AI-powered UI. Our systems ingest over petabytes of logs and billions of time series metrics across our fleet. We're now layering intelligence on top—think agents that summarize SEVs, auto-generate dashboards, or help engineers debug through notebook-like UIs. We’re hiring software engineers across the stack—infra, backend, and product. You’ll join a small, gritty team building both foundational infra and novel internal tools to make OpenAI's production systems reliable, performant, and observable. What You’ll Do Own core observability infrastructure, including distributed logging, time series, and trace storage Build AI-native tools that help engineers detect, understand, and resolve issues autonomously. Contribute to UI experiences like dashboards, notebooking, or interactive debugging Collaborate closely with engineers, researchers, user ops, and other teams across the company to build the next generation observability product You Might Be a Fit If You: Have operated large-scale distributed systems in production. ( especially logging systems or some other time series databases) Thrive in ambiguous environments and roll up your sleeves to solve unscoped problems. Have full-stack chops or product sensibilities—you're excited to build real tools people use. Have strong fundamentals in systems, networking, and cloud infra (Kubernetes, AWS, etc). Bonus : built or contributed to observability systems (e.g. Prometheus, OpenTelemetry, etc). Why This Team We’re b