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Micron Technology

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Official opening at Micron Technology. Role involves advanced engineering across design, testing, verification, and silicon delivery pipelines. Candidate will collaborate with multi-site engineering teams on high-performance compute and semiconductor architectures. Apply directly via official career portal.

Micron Technology

Verified

Official opening at Micron Technology. Role involves advanced engineering across design, testing, verification, and silicon delivery pipelines. Candidate will collaborate with multi-site engineering teams on high-performance compute and semiconductor architectures. Apply directly via official career portal.

Micron Technology

Verified

Official opening at Micron Technology. Role involves advanced engineering across design, testing, verification, and silicon delivery pipelines. Candidate will collaborate with multi-site engineering teams on high-performance compute and semiconductor architectures. Apply directly via official career portal.

Micron Technology

Verified

Official opening at Micron Technology. Role involves advanced engineering across design, testing, verification, and silicon delivery pipelines. Candidate will collaborate with multi-site engineering teams on high-performance compute and semiconductor architectures. Apply directly via official career portal.

Micron Technology

Verified

Official opening at Micron Technology. Role involves advanced engineering across design, testing, verification, and silicon delivery pipelines. Candidate will collaborate with multi-site engineering teams on high-performance compute and semiconductor architectures. Apply directly via official career portal.

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. Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API. This role is hybrid, based in Cyprus. 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 Bring up, run, and debug modern ML models (e.g., transformers) using PyTorch or TensorFlow. Analyze model behavior and performance, and identify bottlenecks across the stack. Improve efficiency, correctness, and scalability of model execution in real systems. Work closely with compiler, kernel, and hardware teams to drive performance and system-level improvements. Help translate state-of-the-art model architectures into production-grade, high-performance deployments. What We Need Strong experience building and working with ML models in PyTorch or TensorFlow. Strong understanding of modern ML model architectures (ex: transformers). Solid software engineering fundamentals with strong debugging and problem-solving skills. Comfort working in a fast-moving, research-meets-engineering environment. Bonus, not required: experience with profiling or performance tuning, or familiarity with quantization, flash attention, kernel fusion, memory hierarchies, C++, CUDA, or systems programming. What You Will Learn How to bring state‑of‑the‑art LLMs and vision models to high performance on a custom AI accelerator. How to trace and fix performance bottlenecks from PyTorch code down to kernels and memory systems. How to turn research‑grade models into reliable, production deployments on new hardware. The practical trade‑offs between techniques like quantization, FlashAttention, and kernel fusion when you’re optimizing real throughput, latency, and memory. How your findings can drive changes across compiler, kernel, and hardware teams in a full‑stack co‑design loop Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

Graphcore

Verified

About us We are looking for a disciplined and dynamic Systems Engineer with focus on server CPU based system to join our growing compute rack validation team. Candidate we are seeking should have demonstrated work-experience in leading server rack and blade hardware systems deployment, hardware installation, and inventory management activities in the Austin, TX area. As a diligent leader in Systems Engineering, you will drive multiple aspects of post-silicon validation throughout the life cycle of the program. In this high visibility position, you will be part of a technical team chartered to innovate and improve system bring-up and enablement capabilities, as well as silicon and system validation to deliver the highest quality, industry leading technologies to market. Your technical leadership skills, systems engineering and hardware bring-up, validation and debug expertise will be necessary towards product development, definition, root cause and resolution. Your agility and collaborative approach will be essential to work within System Validation & other engineering teams (System Architects, SoC and Rack FW etc). The ideal candidate will be driving key areas around at-scale system validation including ARM based server and rack level systems bring-up (nodes and rack level systems). Candidate will be immersed in challenging system enablement work, ramp-up post-silicon capabilities in engineering lab environments, validation tests execution/triage. The candidate will be leading contributor towards state-of-the-art HW bring-up and lab capabilities for Grapchore’s system engineering. The candidate should be able to work in a global environment while maintaining a synergetic culture. Primary Responsibilities: Install, configure, commission (and decommission if needed) blade servers, chassis, switches, and supporting infrastructure. Lead rack and stack activities, including mounting equipment, cable management, and labelling. Execute hardware upgrades, replacements, and troubleshooting of server and network components. Maintain accurate asset records within DCIM platforms and inventory management systems. Conduct physical audits and reconcile inventory discrepancies. Track hardware movements, deployments, and decommissions through established change management processes. Document installation procedures, rack layouts, cabling diagrams, and inventory updates. Support data center migration, expansion, and refresh projects. Collaborate with engineering, operations, logistics, and project management teams. Adhere to all data center safety, security, and operational standards. Develop, setup and scale key methodologies for at-scale test execution, lab HW and system SW capabilities as well as system visibilities and debug tools necessary for successful system (HW/SW/FW) bring-up and system validation at blade and rack level for AI compute rack. Ability to work independently in a production ready environment, and a commitment tomaintaining accurate inventory and asset records. Triage issues found during server rack validation bring-up, Post-Silicon Validation, and production phases of the program. Ensure issues are solved on time with quality. Lead test execution of key domains within AI compute solutions like CPU, GPU, memory, HBM, IO etc. Drive technical innovation to improve capabilities across system validation, including tools, script development, technical and procedural methodology enhancement, and various internal and cross-functional technical initiatives. Qualifications: Strong analytical/problem-solving skills and pronounced attention to details Experience in Blade server installation and maintenance (Cisco UCS, HPE Synergy, Dell MX, or similar). Rack and stack deployments in enterprise or hyperscale environments. Copper and fiber cabling installation and management. DCIM and asset management platforms. Strong understanding of server, storage, and networking hardware. Experience performing inventory audits and maintaining asset accuracy. Ability to read rack elevation diagrams, cabling schematics, and deployment documentation. Familiarity with ticketing and change management systems. Exposure to Linux (ubuntu) OS bootable images and system firmware basics for image building, provisioning and firmware flashing. Exposure to automation testing, to enable execution of hardware acceptance tests, best-known-config testing etc. Exposure to python script development and execution. Proven experience in understanding, defining and enabling storage (storage rack), networking capabilities (network rack, DNS, DHCP etc) in a lab environment to help add end-to-end validation and debug capabilities for rack and blade validation. Excellent communication and coordination skills. Detailed oriented, highly organized, able to prioritize, and juggle multiple work streams to tight deadlines. Technical leadership: capable of championing new tools, methods, and capabilities to drive platform validation improvements in schedule, quality, or coverage. Experience working with data center technical staff, 3rd party vendors, ODMs etc throughout the life cycle of server system product development. Must be a self-starter, and able to independently drive tasks to completion Preferred Qualifications: Masters or PhD in Electrical Engineering, Computer Engineering or a related field. 10+ years of work experience demonstrating working on complex systems engineering challenges to validate and debug HW-FW-SW challenges in a server compute rack or data center blade environment. Experience designing and deploying modern AI/ML rack scale systems Knowledge of industry standards and best practices for hardware development Familiarity with emerging technologies in AI and Data Center infrastructure. Comfortable meeting, engaging and collaborating with ODM partners and staffing vendors across the globe. USA Benefits In addition to a competitive salary, Graphcore offers flexible working and a comprehensive benefits package designed to support your health, wellbeing and financial future. Our benefits include medical, dental and vision coverage, Flexible Spending Accounts (FSAs), Health Savings Accounts (HSAs), disability and life insurance, a 401(k) retirement plan, commuter benefits, wellness services and an Employee Assistance Programme (EAP). We welcome people of different backgrounds and experiences; we're committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

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 building next-generation AI systems that push the boundaries of model training, inference, and large-scale distributed compute. The ML Models team sits at the intersection of cutting-edge AI research and high-performance hardware, bringing state-of-the-art machine learning models to life on Tenstorrent’s custom AI accelerators. From training large language models to optimizing inference performance at scale, this team works across the full stack to turn breakthrough research into production-ready AI systems. If you are passionate about advancing the frontier of AI research, inference and training optimizations, this is an opportunity to shape how future AI models are developed and deployed. This role is hybrid, based out of Toronto, ON and Boston, MA. 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 Strong Python and PyTorch experience developing and training deep learning models. Deep understanding of ML architectures, LLM training, and inference optimization. Hands-on experience training large-scale machine learning models. 4+ years of industry and/or academic experience in ML research and LLM development. PhD, published research, or experience with speculative decoding is highly valued. What We Need Lead research and development efforts focused on LLM training and inference optimization. Train, evaluate, and optimize state-of-the-art AI models on Tenstorrent hardware. Improve performance through techniques such as speculative decoding, quantization, kernel fusion, flash attention, and distributed training. Investigate system bottlenecks and collaborate cross-functionally to drive performance improvements. Translate cutting-edge ML research into scalable, production-ready solutions. What You Will Learn How to optimize AI models on custom AI accelerators from application to silicon. How large-scale ML systems are deployed, tuned, and scaled in production. How hardware, compiler, kernel, and ML teams collaborate to maximize performance. The challenges and tradeoffs of scaling modern AI workloads across custom hardware. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.