ML Research Engineer

📋 Description

• Optimize ASR, LLMs, and TTS for real-world use in noisy environments.
• Fine-tune LLMs with RAG, RL, and prompts for context-aware chats.
• Integrate AI components into autonomous agents for scheduling and orders.
• Implement human-in-the-loop and automated monitoring to improve models.
• Develop pipelines to construct knowledge graphs from business data.
• Scale models across GPU/TPU clusters and edge devices to minimize latency.

🎯 Requirements

• 3-7+ years deploying ML models, ideally in voice, NLP, graphs, or agents.
• Deep knowledge in speech recognition, LLMs, RL/dialogue, TTS, and ontologies.
• Proficiency in PyTorch or JAX; CUDA/Triton optimization preferred.
• Minimize latency and resource use on GPUs/TPUs or edge hardware.
• Strong data-driven approach with measurable improvements.
• BS, MS, or PhD in CS, EE, Mathematics, or equivalent.

🎁 Benefits

• Meaningful equity
• Real product with real usage and growing revenue
• In-person culture, fast feedback, and zero bureaucracy
• Small team that feels like a founding team
• Health, dental, vision, 401k, life insurance, and unlimited PTO
• Tools budget, coffee budget, whatever-you-need-to-be-great budget