Member of Technical Staff - Post Training, Applied

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

• Act as the technical owner for enterprise customer post-training engagements involving text workloads
• Translate customer requirements into concrete post-training specifications and workflows
• Design and execute data generation, filtering, and quality assessment processes for text corpora
• Run supervised fine-tuning, instruction tuning, RLHF, DPO, and other preference alignment workflows
• Design task-specific evaluations for text model performance and interpret results
• Build reusable applied tooling and workflows that accelerate future customer engagements

Requirements

• Hands-on experience with data generation and evaluation for LLM post-training
• Experience training or fine-tuning models using SFT, instruction tuning, RLHF, DPO, or similar preference alignment methods
• Strong intuition for text data quality and evaluation design
• Experience with text-specific post-training workflows: chat model alignment, instruction tuning, or text data curation at scale
• Proficiency with open-source ML ecosystem (Hugging Face, PyTorch) and modern model architectures

Preferred Qualifications

• Experience delivering applied ML work to external customers with measurable outcomes
• Familiarity with inference optimization frameworks (vLLM, SGLang, TensorRT)
• Experience building reusable ML tooling or evaluation infrastructure

Benefits

• Competitive base salary with equity
• 100% 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