Advanced Dram Process Integration Engineer in United States

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. Tenstorrent is seeking a SoC Physical Design Verification Engineer to drive full-chip signoff and ensure manufacturable, high-quality silicon across advanced technology nodes. You’ll lead physical verification closure (DRC, LVS, ERC, etc.), debug issues using standard industry PV tools, and collaborate across RTL, PD, CAD, and packaging teams to achieve successful tapeouts. If you thrive in a fast-paced environment and enjoy solving complex challenges in cutting-edge silicon, we’d love to hear from you. This role is hybrid , based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. 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 A seasoned engineer with a strong background in CPU/IP/SoC physical verification and tapeout closure. A hands-on problem solver who excels at debugging and driving signoff through complex verification flows. A collaborative team player who works effectively across RTL, PD, CAD, and foundry interfaces. A mentor and technical leader passionate about building efficient, manufacturable silicon. What We Need BS/MS in Electrical/Electronics Engineering (or related) with 7–14 years of hands-on CPU/IP/SoC physical verif

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Senior Principal Network Engineer to help design, deploy, and optimize next‑generation AI data center networks. AI training and inference workloads require extremely high bandwidth, deterministic low latency, and zero‑packet‑loss networking environments. In this role, you will partner closely with the Network Architecture Lead to design and scale high‑performance computing (HPC) network fabrics supporting GPU clusters. You will work across hardware, networking, and AI application layers to ensure Graphcore’s large‑scale AI infrastructure operates at peak performance. The ideal candidate brings deep experience operating hyperscale or HPC data center networks and has expertise in high‑speed Ethernet fabrics, RDMA technologies, advanced automation, and telemetry systems. The Team The Data Center Network Engineering team designs and operates the high‑performance network fabrics that power Graphcore’s AI compute platforms. The team collaborates closely with hardware engineering, AI researchers, and infrastructure teams to build scalable networking environments optimized for distributed training and infe

About the Team OpenAI’s People team hires, engages, and retains world-class talent to safely build and deploy AGI that benefits all of humanity. The People Analytics team helps leaders make better, evidence-based talent decisions. About the Role As a People Research Scientist, you will bring deep expertise in research design, measurement, experimentation, and applied data science to OpenAI’s most important People programs. You will design studies, evaluate people processes, and help leaders better empower employees, strengthen organizational systems, and deliver exceptional employee experiences. This is a high-ownership individual contributor role combining hands-on research, methodological leadership, and scalable people science capabilities. We’re looking for an experienced researcher who can turn ambiguous People questions into rigorous designs, validated insights, and actionable recommendations. This role is based in San Francisco, CA or Mountain View, CA, with occasional travel to our San Francisco office. What You’ll Do: Design rigorous research and evaluation strategies for recruiting, organizational health, manager effectiveness, employee experience, and talent outcomes. Apply advanced statistical modeling, machine learning, and research methods to inform program design, evaluate effectiveness, and quantify business impact. Partner with People Operations, data engineering, and people systems teams to define data requirements, improve data quality, establish documentation standards, and ensure research datasets are governed, reproducible, and privacy-preserving. Build scalable people science infrastructure, including self-service agentic tools, automated validation workflows, reusable research datasets and analytical pipelines. Develop research playbooks that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable, and scalable research across the organization. Communicate findings through c

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. About the role: We are seeking an experienced Optical Network Engineer to lead Laser related work within our optical interconnect efforts for large-scale compute systems. The role also requires broad, hands-on optical validation experience across IM/DD-based interconnects, working from lab characterization through production readiness and scaled deployment. In this role you will: Drive laser-focused requirements and technical direction within the broader optical interconnect roadmap. Lead evaluation and validation of optical components and subsystems, including laser-based elements, in lab and production-representative environments. Support end-to-end optical testing for IM/DD interconnects (e.g., module/system bring-up, characterization, debug, and readiness for scale). Work with external partners to align on development milestones, performance targets, and quality expectations. Own technical issue triage and resolution across performance, reliability, and manufacturability topics. Collaborate across internal teams to support integration, rollout, and operational success at scale. You might thrive in this role if you have: Strong experience in laser-focused optical engineering (development, validation, manufacturing readiness, or field support). Broad hands-on background with IM/DD optical technologies and optical test/debug workflows. Experience working with external suppliers/manufacturing partners and production-oriented execution. Demonstrated ability to debug complex t

We are developing advanced multi-rack, multi-tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud-native stack for datacenter products like GB200. In this role, You will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi-rack, multi-tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team. What you’ll be doing: Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc. Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities. Drive joint architecture reviews and “whiteboard” sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests. Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites. Deliver technical collateral-design docs, how-to guides, demo scripts-and present at customer on-sites, KubeCon, and SlurmUG. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins). Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters. Proven track record debugging large-scale, cloud-native stacks across ne

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're looking for a Director of Engineering to join our leadership team in the AI Functions product portfolio, a hybrid director/principal engineer role at the forefront of AI-powered analytics. Our mission is to democratize AI by surfacing powerful AI functions directly in SQL for analyzing structured and unstructured data, with minimal configuration. We handle the full AI lifecycle behind the scenes, so data analysts, engineers, and scientists can build data transformation pipelines with AI using the most sophisticated building blocks seamlessly within their existing SQL workflows. The AI Functions product portfolio represents one of the most strategic and impactful product surfaces within Snowflake, bringing together two of the company's core strengths: its industry-leading ability to process massive volumes of data and its growing capability to make that data AI-ready. By embedding advanced AI and LLM-powered functions directly into SQL, this portfolio transforms Snowflake from a data platform into an intelligent data system where structured and unstructured data can be seamlessly prepared, enriched, and analyzed using AI at scale. This convergence enables customers to operationalize AI within their existing workflows, unlocking faster insights, more powerful applicatio

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. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

Become a part of our caring community Humana invites MBA and other advanced-degree students to join its Summer 2027 Internship Program. This immersive experience allows students to contribute to meaningful, enterprise-level work across a range of business functions, engage with executive leaders, and develop the skills and perspective needed for a successful healthcare career after graduation. We are seeking purpose-driven leaders who demonstrate intellectual curiosity, agility, sound judgment, and a high degree of emotional intelligence. Strong candidates embrace complex challenges, navigate ambiguity confidently, and are motivated to shape the future of healthcare. MBA Strategy & Operations Internship opportunities are available across several strategic areas, including: CenterWell Pharmacy – Business Development CenterWell Pharmacy Hub Team CenterWell Pharmacy Operations Consumer Product Enablement & Solutions Corporate Strategy Insurance Product Solutions Pharmacy Business Integration Pharmacy Product Management Provider Network Operations – Humana Military Sales Strategy Transformation Office Value-Based Care Enablement Strategy <p style

About the Team The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI. About the Role We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement. In this role, you will: Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas. Define the data strategy for all the data subject areas you own. Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue. Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions. Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics. Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems. Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response. Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders. You might thrive in this role if yo

About the Team OpenAI is building the world’s most advanced AI infrastructure ecosystem. The Site Readiness & Development team owns the upstream diligence and development work required to convert powered-land opportunities into executable infrastructure options. About the Role The Site Selection Lead sets the site-selection strategy for powered-land and greenfield/brownfield opportunities. This role defines, with cross-functional partners, what makes a site attractive, executable, and scalable, then turns that shared rubric into portfolio choices and deployment plans. Key Responsibilities Own the site-selection strategy across priority geographies, including market maps, pipeline segmentation, source refreshes, live-location tracking, and portfolio prioritization. Convene Power, Land, Development, Engineering, Construction, Environmental, Community, Commercial, Legal, and Finance partners to define the shared rubric for a high-quality site. Translate that rubric into clear screening criteria across power readiness, land control, timing, scale, cost, community risk, environmental constraints, AHJ path, budget, schedule, and counterparty credibility. Orchestrate Commercial, Legal, Finance, Power, and Development teams to shape exclusivity, initial terms, site-control strategy, funding assumptions, and the path to deployment before deeper commitment. Build a deployment plan for top candidates that identifies capacity, sequencing, capital implications, critical-path approvals, risks, owners, and stage-gate decisions. Lead conceptual site planning and test-fit screening using boundaries, map layers, buildings, substations, roads, parking, laydown, stormwater, utility corridors, acreage, and estimated load. Maintain a single decision-support view of pipeline stage, site health, power readiness, finance review, maps, project evidence, outstanding source data, owners, deadlines, and escalations. Present executive-ready advance, defer, or stop recommendations with clear

About the Team Industrial Compute is building the world's most advanced AI infrastructure. Working alongside our capital partners, engineering teams, and construction organizations, we design and deliver large-scale, mission-critical compute campuses that power the next generation of AI. Our Design organization brings together engineering, construction, and digital design to ensure facilities are coordinated, constructible, and optimized from the earliest planning phases through deployment. About the Role We are seeking a BIM Designer & Coordinator to support the planning and design of large-scale industrial and mission-critical facilities. In this role, you will develop, coordinate, and maintain multidisciplinary BIM models across Civil, Electrical, Mechanical, Architectural, and Structural disciplines, enabling early design validation, constructability reviews, equipment planning, and cross-functional coordination. You will partner closely with internal engineering teams, external design consultants, contractors, and project stakeholders to produce coordinated BIM deliverables that improve design quality, reduce project risk, and support efficient execution across Industrial Compute's global infrastructure portfolio. Key Responsibilities: Develop and maintain conceptual and schematic BIM models for large-scale industrial and MEP-intensive facilities. Coordinate BIM models across Civil, Electrical, Mechanical, Architectural, and Structural disciplines. Create and maintain federated models used for design reviews, spatial coordination, constructability analysis, and clash detection. Model major building systems including equipment layouts, utility corridors, electrical rooms, mechanical rooms, structural framing, site infrastructure, and architectural constraints. Coordinate equipment clearances, maintenance access, routing zones, shafts, risers, utility entrances, and major MEP pathways. Translate engineering sketches, basis-of-design documents, equipment lists

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision? What you will be doing: Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models. Improve AI compilers to hide communications or perform automatic fusion. Conduct in-depth AI workload performance characterization on multi-GPU clusters. Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads. Author

Become a part of our caring community Humana invites MBA and other advanced-degree students to join its Summer 2027 Internship Program. This immersive experience allows students to contribute to meaningful, enterprise-level work across a range of business functions, engage with executive leaders, and develop the skills and perspective needed for a successful healthcare career after graduation. We are seeking purpose-driven leaders who demonstrate intellectual curiosity, agility, sound judgment, and a high degree of emotional intelligence. Strong candidates embrace complex challenges, navigate ambiguity confidently, and are motivated to shape the future of healthcare. MBA Primary Care & Clinical Innovation Internship opportunities are available across several strategic areas, including: Clinical Performance & Innovation CenterWell Primary Care Organization Primary Care Organization Practice Technology Portfolio & Change Management Value Based Care Enablement Medical Specialty Operations Across these strategic areas, interns help translate priorities in primary care and clinical innovation into action through strategic planning, business case development, cross-functional coordination, process improvement, portfolio execution, and transformation support. They may contribute to initiatives that strengthen clinical performance, advance technology-enabled care, improve operational efficiency, and deliver greater value for patients and the enterprise while supporting sound governance and continuous improvement. Location and work arrangement : This is a 12-week, in-person internship based primarily at Humana’s headquarters in Louisville, KY, with limited opportunities in Arlington, VA; Chicago, IL; Fort Lauderdale, FL; Boston, MA; Nashville, TN; and New York

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent advances in our multimodal image models have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering, unlocking entirely new creative and professional workflows. We work at the intersection of research, infrastructure, and product to build the systems that power image generation at global scale. Our team partners closely with researchers, product engineers, designers, and platform teams to bring state-of-the-art image capabilities to millions of users while continuously pushing the boundaries of what AI-powered creation can do. About the Role We are looking for an experienced Backend Engineer to join the Image Generation team and help build the systems that power image creation and editing across ChatGPT. You'll work on the core backend infrastructure that enables users to generate, edit, and iterate on visual content using cutting-edge multimodal AI models. This includes building highly scalable services, orchestration systems, APIs, storage platforms, and distributed infrastructure that support billions of image generations and editing workflows. You'll partner closely with product, research, and mobile teams to transform breakthrough AI capabilities into reliable, performant experiences used by millions around the world. In this role, you will: Design, build, and operate backend systems that power image generation and image editing experiences in ChatGPT. Develop scalable APIs, services, and infrastructure that support multimodal AI workflows. Optimize reliability, latency, throughput, and cost across large-scale distributed systems. Partner with researchers to productionize new im

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside leading cloud providers, engineering firms, construction partners, utilities, and equipment manufacturers, we are delivering hyperscale AI campuses that enable the next generation of frontier AI models. The Strategic Sourcing team develops and executes the commercial strategies that ensure our infrastructure programs have reliable access to the equipment, materials, and strategic partners needed to deliver at unprecedented scale. We partner closely with Infrastructure Delivery, Capacity Planning, Design Engineering, Hardware Operations, Finance, Legal, and our external suppliers to build a resilient global supply network capable of supporting Industrial Compute's long-term growth. As we continue expanding globally, strategic sourcing becomes a critical competitive advantage, ensuring our infrastructure programs remain cost-effective, resilient, and capable of executing against aggressive deployment timelines. About the Role We are seeking a Strategic Sourcing Manager, Data Center Infrastructure: Owner Furnished Equipment to lead sourcing strategy for the critical infrastructure systems that power Industrial Compute campuses. This role will develop commercial strategies, negotiate strategic supplier agreements, and manage relationships across engineering, construction, manufacturing, and infrastructure partners responsible for delivering mission-critical facilities. You will work closely with Infrastructure Delivery, Capacity Planning, Engineering, Finance, Construction, and external suppliers to ensure Industrial Compute has the capacity, supplier relationships, and commercial frameworks required to support rapid global expansion. The ideal candidate has experience sourcing major infrastructure systems for hyperscale data centers, mission-critical facilities, industrial construction, semiconductor manufacturing, energy infrastr