Senior/Lead Applied Scientist, Responsible AI
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The role
You will design and implement enterprise-grade Trust Layer models and responsible AI tools ensuring fairness, accountability, and transparency throughout the AI development lifecycle.
Analyze data and model outputs to identify trust and safety issues; define testing protocols for different data types and architectures; recommend mitigations and safe thresholds for deployment.
Set technical goals and guide research and engineering teams on responsible AI best practices; weigh ethical trade-offs in algorithmic design.
Contribute to the development and adoption of libraries and tools for evaluation, testing, and mitigation of risks; build features that improve explainability and user trust.
Collaborate with cross-functional partners and industry peers to advance the state of responsible AI in production systems.
Qualifications include practical ML experience; strong Python and ML framework skills (TensorFlow, PyTorch); production ML deployment experience; and a passion for ethics and fairness.
Analyze data and model outputs to identify trust and safety issues; define testing protocols for different data types and architectures; recommend mitigations and safe thresholds for deployment.
Set technical goals and guide research and engineering teams on responsible AI best practices; weigh ethical trade-offs in algorithmic design.
Contribute to the development and adoption of libraries and tools for evaluation, testing, and mitigation of risks; build features that improve explainability and user trust.
Collaborate with cross-functional partners and industry peers to advance the state of responsible AI in production systems.
Qualifications include practical ML experience; strong Python and ML framework skills (TensorFlow, PyTorch); production ML deployment experience; and a passion for ethics and fairness.
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