Member of Technical Staff - Inference Systems

The role

You will design and build benchmark suites for inference performance, model quality, and knowledge evaluation. You will also port models onto different runtimes and maintain the inference engine layer.

What you will do

• Design and build benchmark suites covering inference performance, model quality, and knowledge evaluation across hardware targets.
• Run external partner verifications by evaluating solutions against benchmarks and delivering findings.
• Port models like LFM2 onto different runtimes and frameworks and verify correctness end-to-end.
• Maintain and extend the inference engine layer built on llama.cpp, ONNX, and MLX.
• Make benchmark results explainable and verifiable for internal teams and partners.

Required qualifications

• Hands-on experience with at least one inference framework like llama.cpp, ONNX Runtime, or MLX, including internals and modification.
• Experience designing and building benchmarking pipelines, including methodology, validation, and reproducibility.
• Strong C++ and Python in performance-sensitive contexts.
• Solid understanding of inference fundamentals: quantization, decoding strategies, memory layout, and how they interact.

Nice to have

• Experience porting models across runtimes and verifying numerical correctness.
• Prior work with external partners or clients in a technical validation or evaluation capacity.
• Familiarity with edge inference targets and the constraints that come with them.

Benefits

• Competitive base salary with equity in a unicorn-stage company
• 100% of medical, dental, and vision premiums paid for employees and dependents
• 401(k) matching up to 4% of base pay
• Unlimited PTO
• Company-wide Refill Days throughout the year

About the company

Spun out of MIT CSAIL, liquid-ai builds general-purpose AI systems that run efficiently across deployment targets. They partner with enterprises across consumer electronics, automotive, life sciences, and financial services.