Senior HRI Scientist — Conversational AI & Memory

Amazon; Berwick (Columbia County); On-site; USD 184,000 - 249,000; Full time

Benefits offered by this job

Health insurance

RSUs (restricted stock units)

Paid time off

Job summary

Amazon seeks an Human-Robot Interaction (HRI) Applied Scientist to develop expressive, socially intelligent robot interactions focusing on verbal and non-verbal communication, memory, and long-term relationships with people in real-world environments.

The role emphasizes LLMs, multimodal inputs, reinforcement learning from human feedback, and bridging research with engineering to deploy practical robotic systems.

Qualifications

• PhD or master's with 6+ years of applied research experience.
• Experience building ML models for business applications.
• Strong publication record at major HRI/ML/AI/HCI conferences.
• Experience designing, running, and analyzing user studies with real participants.
• Experience mentoring junior scientists/engineers.
• Experience applying ML to interactive or socially situated systems.

Responsibilities

• Develop interactive systems using LLMs, multimodal inputs, and RL from human feedback.
• Design conversational systems with turn-taking, grounding, and context from environment/history.
• Integrate perception streams to understand social context for lifelike interactions.
• Develop memory and personalization systems for long-term relationships with users.
• Stay updated on HRI/NLP/multimodal AI advances and apply them to robotics.
• Lead technical projects from conception to production deployment.
• Mentor junior scientists and engineers.
• Bridge research initiatives with practical engineering implementations.

Skills

Machine learning

NLP

Multimodal AI

Human-robot interaction

Python/Java/C++ programming

Leadership

Education

PhD or MS + 6+ years applied research

Tools

PyTorch

JAX

Python

Java

C++

Job description

Amazon seeks an Human-Robot Interaction (HRI) Applied Scientist to develop expressive, socially intelligent robot interactions focusing on verbal and non-verbal communication, memory, and long-term relationships with people in real-world environments.

The role emphasizes LLMs, multimodal inputs, reinforcement learning from human feedback, and bridging research with engineering to deploy practical robotic systems.