Senior Runtime Engineer

About the role

The Runtime Team builds a high-performance, distributed and scalable software execution environment for SambaNova SambaStack and Cloud platforms to support data-flow applications such as ML training and inference and HPC applications. We are searching for a software engineer who will work on all parts of the runtime stacks, supporting AI, ML, and scientific applications in high-performance distributed systems. You will participate in building, testing and deploying next-generation high-performance compute systems for AI applications at scale.

Responsibilities

div]:bg-bg-000/50 [&_pre>div]:border-0.5 [&_pre>div]:border-border-400 [&_.ignore-pre-bg>div]:bg-transparent [&_.standard-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.standard-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8 [&_.progressive-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.progressive-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8">

_*]:min-w-0 gap-3 [&_>_*:last-child]:mb-0 print:block print:[&_>_*_+_*]:mt-3 standard-markdown">

In this role, you'll design and implement new features across the runtime stack including:

New and enhanced features to support high-performance, scalable ML inference and training applications

Drivers and kernels for next generation silicon

Eliminate networking bottlenecks to enable high performance distributed systems

User-space libraries for high performance and high utilization of HW resources

User-facing tools (analysis, job and HW management, profiling, debugging, etc) for Datascale systems

Cross-functional collaboration including Hardware, ML Application, Compiler, and DevOps

Required Qualifications

Bachelor's or higher degree in Computer Science, Engineering, or related field (or equivalent experience)

5+ years of software engineering experience, often with emphasis on distributed systems, networking, or cloud infrastructure

Proven experience building, testing, and tuning software for distributed, high-performance systems. In-depth knowledge of user libraries, and runtime stacks

Solid understanding of Switching and Routing and ability to configure and debug switches and routers for maximum application performance

Significant experience with RDMA and RoCE networking stacks, such as RDMA based verbs and congestion management

Hands-on experience with kernel drivers and system-level software that directly interfaces with hardware

Expertise in designing and optimizing systems that handle massive parallel workloads, including machine learning training and inference tasks that involve billions of operations per second

Deep understanding of hardware-software interaction, including registers, device memory management, and the intricacies of accelerator design. Experience working with ASIC accelerators is highly desirable

Familiarity with distributed systems architecture, including networking, communication protocols, and the challenges of scaling compute resources efficiently

Hands-on experience with software development tools such as Git, Jenkins, and Jira, with an ability to drive automation and continuous integration efforts

Ability to work at the intersection of hardware and software, designing systems that optimize both performance and reliability

Preferred Qualifications

Experience designing or working closely with custom hardware accelerators (ASICs, FPGAs, etc.) and understanding low-level interactions

Knowledge of SDN, DPDK, SONiC, or modern networking frameworks and background with distributed communication libraries (e.g., UCX, MPI, NCCL).

Familiarity with deploying high-performance systems in distributed, cloud, or data center environment