Research Engineer, Conversational Agentic AI, DeepMind

In Small and Medium-Sized Business (SMB) Cloud Sales, we are experts in Google Workspace and Google Cloud solutions. The SMB Sales team helps businesses discover the potential of Google Cloud and work smarter. The SMB team’s priority is to maximize business growth in the segment, and grow the business through multiple channels. The team also participates in research and experimenting with data-driven, scalable solutions to improve conversion rate and customer lifetime value. As a Mid Market Territory Manager, you will help grow Google Cloud Platform (GCP) business directly and via partners. By advocating the innovative ability of our products, you will bring opportunities through the full cycle, while delivering the highest quality customer experience. You will help organizations enhance their growth with your passion for Google products. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

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.

• Leverage new sources of data (real and synthetic) to empower new real-time dialog capabilities.

• Work with infra teams to design models suitable for streaming bi-directional dialog, so the user experience is always fluid and low-latency.

• Prototype and evaluate new technologies.

Qualifications Minimum 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.

Preferred qualifications:

• One or more publications in conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR).

• Research background in NLP/Generative AI.