Senior Staff Machine Learning Engineer - AI Safety and Guardrails
Is this job for you?
Build my CV Build your CV and see how well you match this role — and every other one.
Track your applications on mobile The free Whileresume app, on iPhone and Android.
The role
As a key member of the CSP ML team, you will own guardrails and AI safety across AI-powered systems such as chatbots, assistants, and copilots, ensuring reliability and governance alignment.
Collaborate with ML, engineering, product, policy, trust, security, and legal teams to identify risks, design monitoring systems, and deploy effective safeguards.
Design guardrails to mitigate issues like hallucinations, privacy breaches, prompt injections, harmful responses, and bias.
Build and operate continuous risk monitoring pipelines with human-in-the-loop feedback to enable rapid mitigation and auditing.
Work with evaluation and data platform teams to develop data flywheels for fixing model failure modes and improving guardrails.
Ensure AI features comply with global privacy and regulatory standards, own documentation, and scale safety features across products and platforms.
Collaborate with ML, engineering, product, policy, trust, security, and legal teams to identify risks, design monitoring systems, and deploy effective safeguards.
Design guardrails to mitigate issues like hallucinations, privacy breaches, prompt injections, harmful responses, and bias.
Build and operate continuous risk monitoring pipelines with human-in-the-loop feedback to enable rapid mitigation and auditing.
Work with evaluation and data platform teams to develop data flywheels for fixing model failure modes and improving guardrails.
Ensure AI features comply with global privacy and regulatory standards, own documentation, and scale safety features across products and platforms.
See the full job post
Responsibilities, requirements, skills and benefits — create your free account.
or
Already have an account?
Log inYou might also like these jobs
No closely matching jobs yet — here are the most recent ones.