Senior Applied Scientist, Security Issue Management
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The role
Design and implement novel AI/ML solutions to tackle complex security challenges and enhance builder experience.
Develop state-of-the-art models and LLM-based agentic systems that understand builder intent and automate security workflows.
Identify bottlenecks across the software development lifecycle, run rigorous experiments, and measure downstream impact on engineering velocity and code quality.
Integrate ML models into production security tooling with cross-functional engineering teams, balancing security excellence with developer productivity.
Design and conduct experiments (A/B tests, observational studies) to evaluate algorithms and iterate quickly; establish ML experimentation and deployment best practices.
Communicate results to leadership and stakeholders, gather builder feedback, and translate research findings into practical, scalable solutions.
Develop state-of-the-art models and LLM-based agentic systems that understand builder intent and automate security workflows.
Identify bottlenecks across the software development lifecycle, run rigorous experiments, and measure downstream impact on engineering velocity and code quality.
Integrate ML models into production security tooling with cross-functional engineering teams, balancing security excellence with developer productivity.
Design and conduct experiments (A/B tests, observational studies) to evaluate algorithms and iterate quickly; establish ML experimentation and deployment best practices.
Communicate results to leadership and stakeholders, gather builder feedback, and translate research findings into practical, scalable solutions.
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