Senior Conversational AI Research Engineer - Multimodal NLP

Google DeepMind; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Equity

Bonus target

Benefits

Job summary

Google DeepMind is seeking research-focused software engineers embedded across the company to design and deploy novel multimodal conversational agents and AI-driven features. You will develop audio-first models and leverage external tools to enable real-time dialog, while aligning with safety and ethics in a world-class research environment.

Join a pioneering AI lab that collaborates with universities and publish papers, with opportunities to impact billions of users and advance AI development

Qualifications

• Bachelor’s degree in Computer Science, Machine Learning, Mathematics, Cognitive Science, or a related technical field, or equivalent practical experience.
• 8 years of experience in data preparation, training, and evaluation of ML models.
• Experience building or implementing AI/ML-driven features or infrastructure (e.g., working with Large Language Models (LLMs), NLP, or data pipelines).
• Experience in Machine Learning, Artificial Intelligence, AI algorithms, and data analysis.

Responsibilities

• Partner with the Gemini or DeepMind teams to design, develop, and deploy novel multimodal conversational agents.
• Develop audio-first models capable of orchestrating and planning complex dialogs, including leveraging external tools like search when necessary.

Skills

Data preparation

ML model training

AI/ML features

NLP & data pipelines

Data analysis

Education

Bachelor's degree or equivalent

Job description

Google DeepMind is seeking research-focused software engineers embedded across the company to design and deploy novel multimodal conversational agents and AI-driven features. You will develop audio-first models and leverage external tools to enable real-time dialog, while aligning with safety and ethics in a world-class research environment.

Join a pioneering AI lab that collaborates with universities and publish papers, with opportunities to impact billions of users and advance AI development