Liquid AI

Liquid AI

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

San Francisco · Staff+

Sponsorship not specifiedDetected 200 days ago
Machine LearningData EngineeringNLPLLMs

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odds of building a lasting career here

36Risky
Cap-exempt (no lottery)0
Sponsors this role74
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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Files H-1B transfers

2 transfer filings in the last year, covering 2 workers. Median labor-condition decision: 22 days. An employer that already files transfers is one that can take over an existing H-1B.

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About the role

  • LFM2.5-Audio is Liquid's end-to-end multimodal speech and text language model.
  • At 1.5B parameters, it handles speech-to-speech conversation, ASR, and TTS without requiring separate components, making it uniquely suited for real-time, on-device deployment.
  • We're now bringing this model to enterprise customers.

Responsibilities

  • Spun out of MIT CSAIL, we build 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.
  • You'll own the applied post-training work that adapts LFM2.5-Audio for customer use cases end-to-end, from data generation through delivery.
  • Real ML work: You will fine-tune audio and speech models, build audio data pipelines, and ship solutions to enterprise customers under real-time on-device constraints.

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.
  • Familiarity with function calling, tool use, or structured output training for language models.

Nice to have

  • 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.
  • Has built and shipped function calling capabilities that reliably translate spoken user intents into tool calls for production use cases.
  • Has made durable contributions to Liquid's general-purpose post-training and audio pipelines by feeding applied learnings back into baseline model development.

Compensation

  • Competitive base salary with equity in a unicorn-stage company
  • We pay 100% of medical, dental, and vision premiums for employees and dependents
  • 401(k) matching up to 4% of base pay

Benefits

  • Compensation: Competitive base salary with equity in a unicorn-stage company
  • Health: We pay 100% of medical, dental, and vision premiums for employees and dependents
  • Time Off: Unlimited PTO plus company-wide Refill Days throughout the year

Company info

  • We are scaling rapidly and need exceptional people to help us get there.
  • If you care about data quality, evaluation, and making models actually work in production, this is a chance to shape how applied audio AI is done at a foundation model company.
  • We partner with enterprises across consumer electronics, automotive, life sciences, and financial services.

This listing is sourced directly from Liquid AI's careers page and normalized into a canonical job model.