Advanced Packaging Substrate Supplier Enablement Lead Jobs

Senior Engineer, Process Integration, Advanced NAND — Fab 10N/X, Singapore. Apply via Workday.

Dry Etch MTS/Principal Engineer, Process Development SG, Advanced NAND — Fab 10N/X, Singapore. Apply via Workday.

Wet Process - Senior Engineer, Process Development SG, Advanced NAND — Fab 10N/X, Singapore. Apply via Workday.

Photolithography Staff/Sr Engineer, Process Development, Advanced NAND — Fab 10N/X, Singapore. Apply via Workday.

Principal Engineer, Films/Diffusion - Procurement and Operations Central Team Advanced Development — Hiroshima - Fab 15, Japan. Apply via Workday.

Principal Engineer, Region E, Operations Central Teams Advanced Development Team — Hiroshima - Fab 15, Japan. Apply via Workday.

Senior/Staff/Principal/MTS Engineer, Etch - Procurement and Operations Central Team Advanced Development — Boise, ID - Main Site. Apply via Workday.

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 looking for a mid- to senior-level Physical Design Engineer who will contribute to the physical design of high-performance chips for industry-leading AI/ML architectures, spanning implementation from synthesis through tapeout. You will partner with front-end and physical design engineers to optimize floorplanning, timing, power, performance, and area across multiple IPs. Along the way, you will build end-to-end ASIC expertise while learning from experienced engineers across the chip development process. This role is hybrid , based out of Austin, TX, Fort Collins, CO, 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 An engineer excited to work on high-performance designs for industry-leading AI/ML architectures. A collaborative problem solver who enjoys working with experienced engineers across ASIC disciplines. Grounded in logic design fundamentals and gate- and transistor-level implementation. Curious about how early architectural and RTL decisions shape physical implementation and final chip quality. What We Need A BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a relat

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 looking for a mid- to senior-level Physical Design Engineer with a strong background in static timing analysis (STA). In this role, you will help converge multi-million-gate designs on advanced process nodes and partner with cross-functional teams through final signoff and tapeout. This role is hybrid , based out of Austin, TX, Fort Collins, CO, 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 A physical design engineer with 8+ years of experience in STA, timing closure, and advanced-node design implementation. Experienced with timing flows, constraints, clocking, CDC, RDC, derates, uncertainties, guardbanding, and final signoff. Skilled in writing and debugging SDC constraints, creating ECOs, developing closure strategies, and analyzing worst-case corners. A strong collaborator and communicator who can drive results across distributed, cross-functional engineering teams. What We Need Drive timing convergence across blocks, partitions, sections, and top-level designs; generate and validate timing models and publish results. Analyze timing violations, develop and propagate fixes, debug timing-flow issues, and

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 an Physical Design Engineer to lead cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. 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 BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes. Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs. Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows. Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independent

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 talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA 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 hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-

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 talented Physical Design Engineers to implement high-performance partitions for an industry-leading AI SOC. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid, based out of Austin,TX or Santa Clara, CA 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 Experienced with synthesis and place-and-route flows, especially using Synopsys Design Compiler / Fusion Compiler and IC Compiler II. Comfortable in a small, cross-functional physical design team, owning a block or subsystem and partnering on tapeout milestones with clear communication and accountability. Ideally bring extra depth in areas such as UPF/multi-voltage power domains, SoC interface IP integration (e.g. I3C, UART), signoff breadth (DRC/LVS, EM/IR, LEC/Formality), multi-clock/CDC-aware implementation, PLL/DLL integration, and DFT-aware physical implementati

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’re looking for a Timing Engineer to join our silicon team. In this role, you’ll drive static timing analysis and closure for complex, high-performance designs. You’ll collaborate closely with logic, DFT, and physical design teams to debug constraints, optimize paths, and ensure our chips meet performance targets across corners and modes. This role is hybrid , based out of Austin, TX, Fort Collins, CO, 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 Experienced in STA and passionate about enabling silicon to meet aggressive performance goals. Analytical and detail-oriented, with a strong understanding of timing paths, constraints, and optimization strategies. A collaborative team player who works well across logic, DFT, and physical design boundaries. Resourceful and self-driven, capable of developing scripts and methodologies that improve timing closure workflows. What We Need 7+ years of industry experience and a proven record of successful tapeouts. Deep knowledge of STA tools and techniques, including noise, crosstalk, and OCV analysis. Proficiency in writing and debugging SDC constraints, creating ECOs, and

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