Vision & Multimodal AI Research Scientist

Google LLC; Mountain View (CA); Presencial; USD 207.000 - 300.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity

Bonus target

Benefits

Descripción de la vacante

Google LLC in Mountain View seeks a Research Scientist to design, implement, and scale state-of-the-art LLMs for multimodal understanding. You will run large-scale experiments, prototype architectures, and collaboratively push research ideas toward production-ready foundations that impact real-world products and platforms.

The role emphasizes independent data generation, model training, and optimization pipelines, with opportunities to publish and contribute to the wider research community

Formación

• 3 years of software engineering or related technical field.
• 2 years of work experience in an applied research setting.
• Experience in Artificial Intelligence or Machine Learning.
• Experience developing autonomous agents, multi-agent workflows, or agentic frameworks; and designing/evaluating LLMs and multimodal models.
• Contributions to research communities or publications at conferences (NIPS/ICML/ACL/CVPR).

Responsabilidades

• Design, implement, and scale state-of-the-art LLMs core image/video understanding capabilities.
• Drive end-to-end experimental workflows across pre-training and post-training.
• Build robust, scalable infra and data pipelines for multimodal training and eval benchmarks.
• Partner with Research Scientists and SWEs to transition research into production-ready foundation models.
• Analyze experiment metrics and failure modes to identify opportunities for model quality improvement.

Conocimientos

Software engineering

Applied research

AI/ML experience

Autonomous agents

LLMs & multimodal models

Publications

Educación

Master's degree in CS/AI/ML

PhD preferred

Descripción del empleo

Google LLC in Mountain View seeks a Research Scientist to design, implement, and scale state-of-the-art LLMs for multimodal understanding. You will run large-scale experiments, prototype architectures, and collaboratively push research ideas toward production-ready foundations that impact real-world products and platforms.

The role emphasizes independent data generation, model training, and optimization pipelines, with opportunities to publish and contribute to the wider research community