Member of Technical Staff, AI Systems Engineer

Requirements

• BS, MS, or PhD in Computer Science, Computer Engineering, or related field
• Software engineering experience focusing on systems programming, ML infrastructure, or AI compilers
• Expertise in Python: Deep understanding of memory management, concurrent programming
• Experience with LLM Inference Engines: Hands-on experience modifying or extending frameworks like SGLang, vLLM, DeepSpeed-FastGen, or TensorRT-LLM
• PyTorch Internals: Strong experience writing PyTorch C++ extensions and custom operators
• Hardware Interfacing: Proven track record of integrating ML workloads with accelerators using custom SDKs, APIs, or low-level drivers

Nice to Haves

• Prior experience working on non-CUDA software ecosystems (e.g., AMD ROCm, AWS Neuron, Google XLA)
• Familiarity with AI compilers and intermediate representations (MLIR, Apache TVM, OpenAI Triton)
• Strong understanding of underlying LLM architectures (Transformers, MoE) and attention algorithms
• Previous experience at an AI silicon startup or working on custom accelerators (Google TPU, AWS Trainium)

What You'll Be Doing

• Framework Integration: Architect and develop backend integration for custom AI chip in SGLang
• Custom Operator Development: Write custom C++ / PyTorch extensions
• Performance Optimization: Profile and optimize end-to-end LLM inference
• Cross-Functional Collaboration: Work closely with hardware and compiler teams
• Testing & Deployment: Build robust testing pipelines for model validation

Perks & Benefits

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.