ML Research Engineer

Maple is a company focused on building AI agents for local businesses that handle customer interactions over natural voice. As an ML Research Engineer, you will transform advanced research into practical voice agents and optimize various AI models to enhance performance in real-world applications.

Responsibilities:

• Optimize speech recognition (ASR), large language models (LLMs), and text-to-speech (TTS) for real-world use, ensuring accuracy in diverse, noisy environments
• Fine-tune LLMs with retrieval-augmented generation (RAG), reinforcement learning (RL), and prompt engineering for dynamic, context-aware conversations
• Integrate AI components into autonomous agents capable of complex tasks like scheduling, order-taking, and issue resolution
• Create human-in-the-loop and automated systems to monitor performance, detect anomalies, and continuously improve models from real-world feedback
• Develop pipelines to construct knowledge graphs from business data, powering adaptive AI interactions
• Work with infrastructure teams to scale models efficiently across GPU/TPU clusters and edge devices, minimizing latency
• Manage rapid experimentation, training, and highly optimized production inference
• Lead evaluations, error analysis, and iterative improvements to maintain robustness and scalability
• Balance research innovation with practical usability by closely working with product and customer teams
• Publish research, contribute to open-source, and present at industry-leading conferences