Applied AI Research Engineer: Responsible AI & LLMs

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

Benefits offered by this job

Equity

Benefits

Job summary

Google DeepMind seeks a research-focused software engineer to join the Applied Research and Responsibility team in Mountain View. You will design, prototype, and scale AI engineering solutions, collaborating with Research Scientists to advance responsible AI and real-world impact.

You will establish best practices for code quality, scalability and system design, present complex trade-offs to leadership, and help drive technical direction across cross-functional teams.

Qualifications

• Bachelor's degree in CS, Math or related field, or equivalent practical experience.
• 8 years of Python programming experience.
• Experience with generative AI, NLP and large language models (LLMs).
• Experience with Cloud AI/ML systems and tools (e.g., Kaggle, TensorFlow, PyTorch).

Responsibilities

• Design, prototype, scale AI engineering solutions and run experiments to address responsibility priorities.
• Work with Research Scientists to advance responsible AI.
• Establish best practices for code quality, scalability, and system design.
• Present complex engineering trade-offs and research results to cross-functional leaders.
• Lead project teams and set technical direction.

Skills

Python programming

Generative AI

NLP

LLMs

TensorFlow

PyTorch

Cloud AI/ML tools

Education

Bachelor's degree in CS or related field

Master's degree or PhD (preferred)

Tools

TensorFlow

PyTorch

Kaggle

Job description

Google DeepMind seeks a research-focused software engineer to join the Applied Research and Responsibility team in Mountain View. You will design, prototype, and scale AI engineering solutions, collaborating with Research Scientists to advance responsible AI and real-world impact.

You will establish best practices for code quality, scalability and system design, present complex trade-offs to leadership, and help drive technical direction across cross-functional teams.