Member of Technical Staff - Post Training, Applied (Audio)
Core
Own end-to-end post-training projects for LFM2.5-Audio, adapting frontier audio models for enterprise customers to enable voice-driven function calling and real-time on-device deployment.
Role type
Senior IC applied machine-learning engineer (audio post-training)
Builds
Production-ready audio models with function calling capabilities for enterprise customers
Domain
Generative AI, Audio Language Models, Enterprise Software
Deliverable
production ML models
Required skills
Post-training for language models (SFT, preference alignment, RL), Data generation and evaluation pipelines for LLM/audio models, Function calling and tool use training, Model adaptation and evaluation design
Preferred skills
Speech/audio language models (speech-to-speech, ASR, TTS), Customer-facing ML delivery, Alignment/RL techniques beyond SFT, On-device/low-latency inference constraints
Technologies
LFM2.5-Audio, Audio data pipelines, Function calling frameworks
Responsibilities
Translate customer requirements into post-training specifications, Design and build function calling capabilities for audio models, Execute data generation pipelines for speech-to-speech and text-to-text training, Run supervised fine-tuning and reinforcement learning workflows, Design task-specific evaluations for audio function calling
Seniority
Senior, hands-on IC