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Hpc Dev Ops Engineer in Austin

3 active opportunities · Updated October 2026

Explore current hpc dev ops engineer jobs in Austin. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Austin, Texas, United States· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

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

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📍 Austin, Texas, United States· Full-time
✓ High-confidence listing

$100K – $500K/yr

Quick readStrong listing-quality and freshness signals

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. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. 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 C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim

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📍 Austin, Texas, United States· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world's most transformative technologies. Our AI Engineering Campus in Austin plays an important role in building the future of AI computing. The Opportunity As Technical Services Director, you will lead the teams that operate and evolve Graphcore's engineering labs, high-performance computing (HPC) platforms, and data center environments globally. You will be accountable for reliable, secure, cost-effective infrastructure that supports demanding engineering, AI, silicon-development, and validation workloads. This role combines people leadership, infrastructure strategy, operational excellence, capacity and financial planning, procurement, and program delivery. You will partner with Engineering, Information Technology, Security, Finance, Facilities, Supply Chain, customers, and external suppliers. The position is based onsite in Austin and requires travel to company facilities, data centers, and supplier locations, including international travel. What You'll Do Lead, recruit, mentor, and develop the systems administration, lab operations, and technical services teams responsible for the facility supporting global Engineering and Research and Development. Own the reliability, efficiency, protection, safety, supportability, and continuous improvement of engineering labs, HPC systems, and infrastructure facilities. Establish service levels, operating standards, escalation paths, performance measures, monitoring, observability, automation, ticketing, and configuration-management practices. Translate engineering and customer requirements into infrastructure roadmaps, capacity p

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