Lead, Multimodal AI Research & Engineering

Google LLC; Mountain View (CA); On-site; USD 262,000 - 364,000; Full time

Benefits offered by this job

Equity

Bonus target (25%)

Benefits

Job summary

Google LLC in Mountain View, CA, USA is hiring a Research Engineering Manager for Multimodal AI at Google Labs. You will lead a multidisciplinary team of researchers and engineers, shaping technical strategy for audiovisual data curation, model training, evaluation, and real-time inference.

The role emphasizes driving production-ready research, collaborating with DeepMind and other Google teams, and delivering scalable AI solutions across platforms.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development or ML research with Python or C++, including design/deploy of ML systems.
• 3 years in a technical leadership or people management role leading engineers/research scientists in AI/ML, CV, audio, or multimodal systems.

Responsibilities

• Guide and mentor a focused, multidisciplinary pod of research scientists and software engineers as a technical lead manager.
• Define and execute the technical roadmap for high-signal audio-visual data curation, multimodal training, and end-to-end evaluation frameworks.
• Contribute to low-latency multimodal serving and streaming inference systems in real-time experiences.
• Partner with product and engineering leaders to transition research breakthroughs into production.
• Establish engineering and scientific excellence across model iteration and cross-Google platform integration.

Skills

Software development

ML research

Leadership

Education

Bachelor's degree

Master's or PhD preferred

Tools

Python

C++

Job description

Google LLC in Mountain View, CA, USA is hiring a Research Engineering Manager for Multimodal AI at Google Labs. You will lead a multidisciplinary team of researchers and engineers, shaping technical strategy for audiovisual data curation, model training, evaluation, and real-time inference.

The role emphasizes driving production-ready research, collaborating with DeepMind and other Google teams, and delivering scalable AI solutions across platforms.