Staff Applied AI Engineer: Generative ML Systems Lead

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

Job summary

DeepMind in Mountain View, CA, USA is seeking a Staff Research Engineer, Applied AI to lead the development and deployment of novel applications leveraging Google's generative AI models. You will rapidly develop new features and collaborate with partner teams to deliver impact for Google and top customers.

The role requires 5+ years of production ML experience and expertise in GenAI/LLMs, transformers, and model fine-tuning, with a track record of shipping complex ML systems from concept to

Qualifications

• Bachelor's degree or equivalent practical experience in a relevant field.
• 8 years of software development experience including system design, data structures, and algorithms.
• 5 years of building, training, and deploying ML models into production environments.

Responsibilities

• Partner with cross-functional teams to define product objectives and technical designs.
• Curate specialized datasets, design evaluations, and perform model fine-tuning for real-world performance.
• Lead from 0 to 1, building agents and workflows powered by DeepMind foundation models.
• Share learnings with core research teams, including deployment signals and edge cases.
• Set best practices for generative AI deployment and demonstrate frontier model capabilities end-to-end.

Skills

Software engineering

System design

Algorithms

Data structures

ML deployment

Production ML

Education

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field

Tools

Deep learning frameworks

ML platforms

Job description

DeepMind in Mountain View, CA, USA is seeking a Staff Research Engineer, Applied AI to lead the development and deployment of novel applications leveraging Google's generative AI models. You will rapidly develop new features and collaborate with partner teams to deliver impact for Google and top customers.

The role requires 5+ years of production ML experience and expertise in GenAI/LLMs, transformers, and model fine-tuning, with a track record of shipping complex ML systems from concept to