Staff Research Engineer, Generative AI & Production ML

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

Benefits offered by this job

Equity

Bonus program

Job summary

Google DeepMind seeks a Staff Research Engineer, Applied AI to lead development and deployment of novel AI-powered applications using Google's generative AI models. You will rapidly develop features and collaborate with partner teams to deliver impactful solutions, translating research into real-world products.

Ideal candidates have strong ML/system design backgrounds, experience shipping complex ML systems, and the ability to work in early-stage environments where products scale from concept to

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field, or equivalent practical experience.
• 8 years of software development experience, including system design, data structures, and algorithms.
• 5 years of experience building, training, and deploying machine learning models into production environments.

Responsibilities

• Partner with cross-functional teams to define objectives and technical designs.
• Curate datasets, design evaluations, and perform model fine-tuning for real-world performance.
• Lead development of novel solutions from concept to production using internal platforms and DeepMind foundation models.
• Share learnings with core research teams and disseminate deployment signals for future models.
• Set best practices for generative AI deployment and demonstrate capabilities of frontier models.

Skills

Software development

System design

Data structures & algorithms

ML deployment

Education

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

Tools

Python

TensorFlow

PyTorch

ML frameworks

Job description

Google DeepMind seeks a Staff Research Engineer, Applied AI to lead development and deployment of novel AI-powered applications using Google's generative AI models. You will rapidly develop features and collaborate with partner teams to deliver impactful solutions, translating research into real-world products.

Ideal candidates have strong ML/system design backgrounds, experience shipping complex ML systems, and the ability to work in early-stage environments where products scale from concept to