Senior System Software Engineer - AI Data Platform - Inference Factory Optimization

• Develop efficient infrastructure and tools for automating complex software processes.
• Drive Performance Optimization: Implement advanced test harnesses, benchmarking frameworks, and analytical tools to rigorously characterize and optimize the performance and efficiency of our software and hardware platforms.
• Apply deep knowledge of operating systems, kernel internals, device drivers, memory management, storage, networking, and high-speed interconnects to build and troubleshoot highly performant systems.
• Work with engineering teams to understand needs, define requirements, and deliver efficient solutions.
• Set performance goals, monitor feedback, analyze data, and make continuous improvements for system reliability.
• Influence Technical Strategy: Contribute to defining technical strategies and roadmaps for our platform automation initiatives, ensuring alignment with company-wide goals and standard methodologies.

• Bachelor’s or equivalent experience in Computer Science, Computer Engineering, or a related technical field, or Master’s degree or equivalent experience in a similar field.
• 5+ years of industry experience in software development, focusing on infrastructure, distributed systems, automation, and/or performance engineering.
• Expertise in System-Level Programming: Proven ability to develop robust tools and automation using programming languages such as C++, Python, or Go.
• Deep Understanding of System Software: Experience with operating system internals, device drivers, memory management, and debugging performance issues in complex compute applications.
• Distributed Systems: Experience in designing, building, and operating large-scale distributed systems, with knowledge of networking protocols, cluster management, and high-performance interconnects.
• Automation and CI/CD Proficiency: Experience building and maintaining automated testing, benchmarking, and continuous integration/continuous deployment pipelines.
• Problem-Solving and Analytical Skills: Outstanding analytical, problem-solving, and debugging skills, with a track record of resolving complex technical challenges.
• Collaboration and Communication: Excellent interpersonal and communication skills, with the ability to articulate complex technical concepts to diverse audiences and collaborate effectively across teams.

Ways to stand out from the crowd

• Experience optimizing performance for AI/Machine Learning workloads, especially inference applications, on diverse hardware platforms.
• Prior experience building or contributing to large-scale compute infrastructure solutions in cloud environments or on-premises data centers.
• Experience with containerization and orchestration technologies, such as Docker and Kubernetes.
• Familiarity with performance profiling tools and methodologies for hardware and software systems.
• Track record of driving significant efficiency gains or architectural improvements in large-scale systems.

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