Senior Engineer, AI Systems

Overview

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Advancing the World's Technology Together

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what s possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We re dedicated to empowering people to be their true selves. Together, we re building a better tomorrow for our employees, customers, partners, and communities.

The AGI (Artificial General Intelligence) Computing Lab  dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems.

Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner.

Join us in our passion to shape the future of computing!

This role is being offered under the AGICL lab as a part of DSRA. We are a research-driven systems lab working at the intersection of large language models, accelerator hardware, and high-performance software stacks. Our mission is to design, prototype, and optimize next-generation AI systems through tight hardware-software co-design.

Our team works hands-on with cutting-edge accelerator hardware, experimental memory systems, and emerging domain-specific languages (DSLs). We build and optimize a Triton-based software stack that pushes the limits of performance, efficiency, and scalability for modern LLM workloads.

We are looking for a Senior AI Systems Engineer with deep experience in high performance Triton kernel development on modern accelerators. In this role, you will design, analyze, and optimize performance-critical kernels used in large scale LLM inference and training pipelines. You will work closely with hardware architects, compiler engineers, and ML researchers to identify performance bottlenecks, interpret profiling data, and co-design solutions that span software and hardware boundaries.

This role is ideal for engineers who enjoy working close to the hardware stack while still reasoning deeply about model level abstractions.

Location:

Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

• Design, implement, and optimize high-performance Triton kernels for LLM workloads on existing accelerators.
• Analyze kernel performance using profiling tools; interpret metrics such as latency, throughput, occupancy, memory bandwidth, and compute utilization.
• Identify performance bottlenecks in kernel design (e.g., memory access patterns, synchronization, tiling strategies) and propose concrete optimizations.
• Work across the stack; from model architecture to kernel implementation to ensure end-to-end performance efficiency.
• Collaborate with hardware and compiler teams on hardware-software co-design, providing feedback that influences future accelerator and DSL designs.
• Prototype and evaluate kernel optimizations using upcoming DSLs and experimental compiler flows.
• Contribute to the evolution of a Triton-based software stack used for cutting-edge research and production-grade experimentation.
• Document design decisions, performance trade-offs, and optimization strategies clearly for internal and external stakeholders.

• Bachelor s with 5+ years, or Master s with 3+ years, or PhD s with 0+ years of industry experience.
• Strong experience writing high-performance Triton kernels for GPUs or other accelerators.
• Solid understanding of LLM fundamentals, including attention mechanisms, transformer architectures, and inference/training workflows.
• Deep knowledge of accelerator hardware architecture, including memory hierarchies (HBM, SRAM, caches).
• Proven ability to read and interpret profiling data and performance counters.
• Experience…