Job Details

Artificial Intelligence Research Scientist

Redwood City, CA (on-site M-F)

Our client is a high-growth AI company building next-generation voice agents for customer interactions across sales, support, and operations. Backed by leading investors, the team is scaling rapidly with strong revenue traction and a focus on real-time, production-grade AI systems.

About the Role

This is a research-driven, high-impact role for ML researchers who want to push the boundaries of real-time conversational AI. You'll focus on advancing model capabilities for human-like voice agents operating in complex, real-world environments, spanning LLMs, speech, and multimodal systems. Your work will bridge cutting-edge research with deployment, directly shaping core product experiences and infrastructure.

Responsibilities

• Research and develop new techniques across LLMs and audio models to improve reasoning, latency, and conversational quality in real-time voice systems.
• Rapidly prototype, train, and iterate on experimental models and pipelines, turning research ideas into working end-to-end prototypes.
• Design and maintain evaluation frameworks, datasets, and metrics to benchmark performance on complex, real-world voice and dialog tasks.
• Collaborate with engineering to translate research insights into scalable, production-ready systems powering live customer conversations.
• Build human feedback loops and annotation workflows to incorporate subjective conversational quality signals into model improvement.
• Stay at the frontier of ML research and bring new approaches into the stack, from pre-training and post-training methods to multimodal architectures for voice agents.

Qualifications

• 1–5 years of experience in audio and/or multimodal ML research or engineering in industry or academia.
• Strong ML research background in areas such as LLM pre-training/post-training, ASR, TTS, or multimodal systems.
• Deep technical foundation in modern ML, including PyTorch, model architectures, and the underlying math.
• Proven ability to design and run experiments on open-ended problems, iterate quickly, and analyze complex model behavior.
• Track record of translating research into working systems in real-world, latency-sensitive environments.
• Excellent communication skills and comfort working cross-functionally in fast-paced, high-ownership settings.

Preferred Skills

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, AI, or a related field, or equivalent research-level experience.
• Experience shipping models for real-time voice or conversational products (for example, call centers, assistants, interactive agents).
• Prior work with reinforcement learning from human feedback (RLHF), preference modeling, or large-scale human evaluation pipelines.
• Experience in early-stage startups or small, high-performing ML teams with high ownership ceilings.