Senior Staff Software Engineer, Groq

• You consistently ship high-impact, production-ready code while collaborating effectively with cross-functional teams
• You possess deep expertise in computer architecture, operating systems, algorithms, hardware-software interfaces, and parallel/distributed computing
• You've mastered system-level programming (C++, Rust, or similar) with emphasis on low-level optimizations and hardware-aware design
• You excel at profiling and optimizing systems for latency, throughput, and efficiency, with zero tolerance for wasted cycles or resources
• You're committed to automated testing and CI/CD pipelines, believing that "untested code is broken code."
• You're deeply curious about system internals—from kernel-level interactions to hardware dependencies—and fearless enough to solve problems across abstraction layers down to the PCB traces
• You make pragmatic technical judgments, balancing short-term velocity with long-term system health
• You write empathetic, maintainable code with strong version control and modular design, prioritizing readability and usability for future teammates
• Nice to have: Experience shipping complex projects in fast-paced environments while maintaining team alignment and stakeholder support
• Nice to have: Expertise operating large-scale distributed systems for high-traffic internet services
• Nice to have: Experience deploying and optimizing machine learning (ML) or high-performance computing (HPC) workloads in production
• Nice to have: Hands-on optimization of performance-critical applications using GPUs, FPGAs, or ASICs (e.g., memory management, kernel optimization)
• Nice to have: Familiarity with ML frameworks (e.g., PyTorch) and compiler tooling (e.g., MLIR) for AI/ML workflow integration
• Early-career engineers: If you've built high-performance systems in school/research and want to dive into cutting-edge hardware/software engineering, we'll invest in your growth to scale with the team

Desirable

• Build and operate real-time, distributed compute frameworks and runtimes to deliver planet-scale inference for LLMs and advanced AI applications at ultra-low latency, optimized for heterogeneous hardware and dynamic global workloads
• Develop deterministic, low-overhead hardware abstractions for thousands of synchronously coordinated GroqChips across a software-scheduled interconnection network. Prioritize fault tolerance, real-time diagnostics, ultra-low-latency execution, and mission-critical reliability
• Future-proof Groq's software stack for next-gen silicon, innovative multi-chip topologies, emerging form factors, and heterogeneous co-processors (e.g., FPGAs)
• Foster collaboration across cloud, compiler, infra, data centers, and hardware teams to align engineering efforts, enable seamless integrations, and drive progress toward shared goals
• Reduce operational overhead, improve SLOs, and make tokens go brrrrrrrrrrr—positioning Groq as the largest inference powerhouse on earth.
• Your code will run at the edge of physics—every clock cycle saved reduces latency for millions of users and extends Groq's lead in the AI compute race