Solutions Architect

About the Company

Spun out of MIT CSAIL, Liquid AI builds general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability.

Responsibilities

• Own customer engagements end-to-end from technical validation to go-live
• Build customer-specific demos and proofs-of-concept using Liquid models
• Lead technical discovery to map customer architectures to Liquid solutions
• Co-own the product-field feedback loop to influence the product roadmap
• Create reusable assets including reference architectures and engagement playbooks

Requirements

• Applied ML skills with hands-on experience building demos or prototypes
• Experience in both pre-sales and post-sales technical customer engagements
• Strong customer-facing communication skills for technical and business buyers
• Understanding of AI architectures and deployment tradeoffs (latency, model size, etc.)

Preferred Qualifications

• Familiarity with small or efficient model deployment on edge or on-device hardware
• Experience with quantization (INT4/INT8, GGUF, AWQ) and model serving frameworks (vLLM, TensorRT-LLM, llama.cpp)
• Experience designing and debugging model evaluations
• Track record of technical thought leadership or industry presentations

Benefits

• Competitive base salary with equity
• 100% coverage of medical, dental, and vision premiums for employees and dependents
• 401(k) matching up to 4% of base pay
• Unlimited PTO plus company-wide Refill Days