Member of Technical Staff - Post Training, Applied (Audio)
Remote • San Francisco • FullTime
Posted 6mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Engineer
About the job
Liquid AI, a company spun out of MIT CSAIL, is developing general-purpose AI systems designed for efficient deployment across various targets, from data centers to on-device hardware, prioritizing low latency, minimal memory usage, privacy, and reliability. They are expanding rapidly and seeking exceptional talent to join their team. This role focuses on "LFM2.5-Audio," Liquid's multimodal speech and text language model, which handles speech-to-speech conversation, ASR, and TTS without separate components, making it ideal for real-time, on-device applications. The core challenge for this position is adapting audio models to understand user intents and translate them into structured tool calls, enabling voice-driven function calling for enterprise customers. This position offers a unique opportunity to work at the intersection of advanced audio models and real-world deployment, owning the applied post-training work from data generation to delivery, and directly influencing the evolution of Liquid's post-training and audio stacks.
Responsibilities
- Act as the technical owner for enterprise audio post-training engagements.
- Translate customer requirements into post-training specifications and workflows for audio models.
- Design and build function calling capabilities for audio models, enabling spoken user intents to map to structured tool calls.
- Design and execute data generation pipelines for speech-to-speech and text-to-text training.
- Run supervised fine-tuning, preference alignment, and reinforcement learning workflows on audio language models.
- Design task-specific evaluations for audio function calling and integrate learnings back into post-training pipelines.
Requirements
- Hands-on experience with post-training for language models (SFT, preference alignment, and/or RL).
- Experience with data generation and evaluation pipelines for LLM or audio model training.
- Strong intuition for data quality and evaluation design.
- Familiarity with function calling, tool use, or structured output training for language models.
- Experience with speech or audio language models (speech-to-speech, ASR, TTS, or multimodal audio-text systems).
- Prior exposure to customer-facing or applied ML delivery environments.
- Experience with alignment or RL techniques beyond basic supervised fine-tuning.
- Familiarity with on-device or low-latency inference constraints.
Benefits
- Competitive base salary
- Equity in a unicorn-stage company
- 100% coverage of medical, dental, and vision premiums for employees and dependents
- 401(k) matching up to 4% of base pay
- Unlimited PTO
- Company-wide Refill Days