Job description

We are looking for a highly adaptable Research Engineer to join our Responsible Frontier AI Research team. In this role, you will drive rapidly evolving research engineering priorities. Because the landscape of responsible AI shifts quickly, you will need to pivot seamlessly between different research initiatives and nimble experiments, building robust infrastructure, scaling evaluations, and implementing mitigations. You will be expected to operate with a high degree of independence, architect complex ML systems from scratch, and work across leadership and cross-disciplinary stakeholders. You will be joining a specialized Applied Research and Responsibility team within Google while closely partnering with teams across Deepmind, Research, Product, and Policy to identify and address key challenges in responsible AI. Our work remains deeply integrated with Google DeepMind. Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google . • Design, prototype, scale engineering solutions, and run rigorous experiments to address emerging research priorities within the Responsibility portfolio. • Work with Research Scientists to advance the state of the art in Responsible AI. • Act as a technical anchor for the team, establishing best practices for code quality, scalability, and system design. • Present complex engineering trade-offs and research results clearly to cross-functional stakeholders and leadership. • Bachelor's degree in Computer Science, Machine Learning, Mathematics, or a related technical field, or equivalent practical experience. • 8 years of experience in machine learning engineering or large-scale software systems. • 3 years of experience in Python programming • 3 years of experience with ML frameworks such as JAX, PyTorch, or TensorFlow. Minimum qualifications: • Bachelor's degree in Computer Science, Machine Learning, Mathematics, or a related technical field, or equivalent practical experience. • 8 years of experience in machine learning engineering or large-scale software systems. • 3 years of experience in Python programming • 3 years of experience with ML frameworks such as JAX, PyTorch, or TensorFlow. Preferred qualifications: • Master's degree or PhD in Computer Science, Engineering, or a related field with a focus on Machine Learning. • Experience working directly on AI safety, or responsible AI research. • Experience in Python and C++ for high-performance ML library development. • Experience with harmful manipulation detection, persuasion modeling, deceptive behavior analysis, or AI safety evaluation and mitigation. • Experience building evaluation frameworks, benchmarks, or automated testing pipelines for ML models.

Requirements

Must-haves

We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Design, prototype, scale engineering solutions, and run rigorous experiments to address emerging research priorities within the Responsibility portfolio.
Work with Research Scientists to advance the state of the art in Responsible AI.
Act as a technical anchor for the team, establishing best practices for code quality, scalability, and system design.
Present complex engineering trade-offs and research results clearly to cross-functional stakeholders and leadership.
Bachelor's degree in Computer Science, Machine Learning, Mathematics, or a related technical field, or equivalent practical experience.
8 years of experience in machine learning engineering or large-scale software systems.
3 years of experience in Python programming
3 years of experience with ML frameworks such as JAX, PyTorch, or TensorFlow.
Bachelor's degree in Computer Science, Machine Learning, Mathematics, or a related technical field, or equivalent practical experience.
8 years of experience in machine learning engineering or large-scale software systems.
3 years of experience in Python programming
3 years of experience with ML frameworks such as JAX, PyTorch, or TensorFlow.

Nice-to-haves

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Master's degree or PhD in Computer Science, Engineering, or a related field with a focus on Machine Learning.
Experience working directly on AI safety, or responsible AI research.
Experience in Python and C++ for high-performance ML library development.
Experience with harmful manipulation detection, persuasion modeling, deceptive behavior analysis, or AI safety evaluation and mitigation.
Experience building evaluation frameworks, benchmarks, or automated testing pipelines for ML models.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningpython

Platform: google
Effort: medium