Member of Technical Staff - Post Training, Applied (Audio)

The role

You will adapt audio models for enterprise products by owning data, post-training, evaluation, and delivery. You will work with customers to define reliable behavior and improve Liquid's audio models and post-training pipelines.

What you will do

• Lead technical work on enterprise audio engagements from scoping to model delivery.
• Build evaluations combining automated checks with human listening.
• Build and curate speech and text datasets from real and synthetic dialogue.
• Fine-tune audio models to translate speech into structured tool calls and natural spoken responses.
• Test on target devices and review failures with customers.
• Bring reusable datasets, evaluations, and training improvements back into core pipelines.
• Define success by asking customers for examples and turning answers into tests.
• Investigate model failures by inspecting audio, predicted calls, and training examples.
• Explain evidence, uncertainty, and recommendations regarding quality and hardware tradeoffs.

Required qualifications

• Hands-on experience post-training a language or multimodal model.
• Experience designing task-specific evaluations and breaking results down by failure mode.
• Experience building and validating training datasets.
• Familiarity with function calling, tool use, or structured model outputs.

Nice to have

• Experience fine-tuning or evaluating speech-to-speech, speech recognition, text-to-speech, or multimodal audio-text systems.
• Experience delivering an applied ML project directly with a customer.
• Hands-on work with preference optimization or reinforcement learning beyond supervised fine-tuning.
• Experience evaluating models on devices with tight latency or memory budgets.

Benefits

• Competitive base salary plus equity
• Unlimited PTO
• Company-wide Refill Days
• Comprehensive health coverage
• Paid leave for pregnancy, parenting, medical needs, and caring for family

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.