Staff AI Safety & Responsible ML Researcher

Apple Inc.; Seattle (WA); On-site; USD 216,000 - 394,000; Full time

Benefits offered by this job

Comprehensive medical coverage

Dental coverage

Retirement benefits

Employee stock programs

Tuition reimbursement

Relocation assistance

Job summary

Apple Inc. is seeking leaders, scientists, engineers and researchers to tackle ambitious AI projects. You will research red-teaming methods for LLMs and diffusion models, develop safeguards for safe deployment, and build tools to assess and explain LLM failures throughout the deployment lifecycle.

The role requires a PhD or equivalent in CS, deep ML expertise, and hands-on experience with TensorFlow or PyTorch. Collaborative work across diverse teams is essential.

Qualifications

• PhD or equivalent experience in Computer Science or related field.
• Demonstrated expertise in ML research and deployment lifecycle.
• Deep understanding of LLM.
• Hands-on experience with TensorFlow or PyTorch.
• Ability to formulate a research problem, design, experiment, implement and communicate solutions.
• Ability to work in a diverse collaborative environment.

Responsibilities

• Research and advance red-teaming methods for LLMs and diffusion models.
• Research and develop mitigations and safeguards to ensure safe deployment of LLMs in Apple products.
• Develop tools, metrics, and datasets to assess LLM safety across deployment lifecycle.
• Create methods to interpret and explain failures in language models.

Skills

ML research

LLM

TensorFlow

PyTorch

Experiment design

Collaboration

Education

PhD or equivalent in Computer Science

Job description

Apple Inc. is seeking leaders, scientists, engineers and researchers to tackle ambitious AI projects. You will research red-teaming methods for LLMs and diffusion models, develop safeguards for safe deployment, and build tools to assess and explain LLM failures throughout the deployment lifecycle.

The role requires a PhD or equivalent in CS, deep ML expertise, and hands-on experience with TensorFlow or PyTorch. Collaborative work across diverse teams is essential.