About The Role
RadixArk is looking for a Generalist Systems Engineer to work across the entire AI systems stack—from kernels to Kubernetes—building and optimizing large-scale inference and training infrastructure. You'll tackle whatever hard problems need solving to push SGLang and our systems forward, rapidly ramping up on new hardware platforms and debugging critical performance issues across the full stack.
Requirements
4+ years experience building production ML systems or high-performance distributed systems
Bachelor's or Master's degree in Computer Science, Electrical Engineering, or equivalent industry experience
Strong systems fundamentals: operating systems, networking, performance engineering
Comfort working across multiple layers of the stack, from hardware to application
Experience with at least one of:
CUDA / Triton / Pallas
JAX / XLA
Distributed systems or HPC
Proficiency in Python, C++, Rust, or Go with production-quality code standards
Demonstrated ability to quickly learn new technologies and debug complex performance issues
Responsibilities
Work across the entire AI systems stack: runtimes, compilers, kernels, networking, storage, Kubernetes, observability
Design and optimize LLM inference and training systems at scale:
High-performance serving (prefill, decode, KV cache, parallelism)
Large-scale training and post-training (fine-tuning, RL, MoE)
Debug and resolve critical performance issues across runtime → kernel → hardware
Quickly ramp up on new hardware platforms (NVIDIA, AMD, TPU)
Build core infrastructure: schedulers, memory managers, communication layers, API services
Contribute to SGLang, Miles, and other open-source projects with features, optimizations, and architectural improvements
Write technical documentation, benchmarks, and best practices for the community
Conduct design and code reviews focused on performance, reliability, and maintainability
About RadixArk
RadixArk is an infrastructure-first company built by engineers who've shipped production AI systems at xAI, created SGLang (20K+ GitHub stars, the fastest open LLM serving engine), and developed Miles (our large-scale RL framework). We're on a mission to democratize frontier-level AI infrastructure by building world-class open systems for inference and training. Our team has optimized kernels serving billions of tokens daily, designed distributed training systems coordinating 10,000+ GPUs, and contributed to infrastructure that powers leading AI companies and research labs. We're backed by well-known investors in the infrastructure field and partner with Google, AWS, and frontier AI labs. Join us in building infrastructure that gives real leverage back to the AI community.
Compensation
We offer competitive compensation with significant founding team equity, comprehensive health benefits, and flexible work arrangements. The US base salary range for this full-time position is: Competitive Compensation + equity + benefits. Our salary ranges are determined by location, level, and role. Individual compensation will be determined by experience, skills, and demonstrated expertise in systems engineering and ML infrastructure.
Equal Opportunity
RadixArk is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
See other positions
