Amazon
Senior Applied Scientist, Security Issue Management
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Senior Applied Scientist, Security Issue Management
role at
Amazon
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
Other locations (remote options may be available)
Are you interested in building Agentic AI solutions that solve complex builder experience challenges with significant global impact? The Security Tooling team designs and builds high-performance AI systems using LLMs and machine learning that identify builder bottlenecks, automate security workflows, and optimize the software development lifecycle—empowering engineering teams worldwide to ship secure code faster while maintaining the highest security standards.
Key job responsibilities
Design and implement novel AI/ML solutions for complex security challenges and improve builder experience.
Drive advancements in machine learning and science.
Balance theoretical knowledge with practical implementation.
Navigate ambiguity and create clarity in early‑stage product development.
Collaborate with cross‑functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions.
Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results.
Establish best practices for ML experimentation, evaluation, development and deployment.
A day in the life
Integrate ML models into production security tooling with engineering teams.
Build and refine ML models and LLM‑based agentic systems that understand builder intent.
Create agentic AI solutions that reduce security friction while maintaining high security standards.
Prototype LLM‑powered features that automate repetitive security tasks.
Design and conduct experiments (A/B tests, observational studies) to measure downstream impacts of tooling changes on engineering productivity.
Present experimental results and recommendations to leadership and cross‑functional teams.
Gather feedback from builder communities to validate hypotheses.
Basic Qualifications
5+ years of building machine learning models or developing algorithms for business application experience.
PhD, or Master's degree and 6+ years of applied research experience.
Experience programming in Java, C++, Python or related language.
Experience with neural deep learning methods and machine learning.
Preferred Qualifications
Experience with large‑scale machine learning systems such as profiling and debugging and understanding of system performance and scalability.
Experience with modeling tools such as R, scikit‑learn, Spark MLLib, MxNet, Tensorflow, NumPy, SciPy, etc.
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. The compensation for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market and may include equity, sign‑on payments, and other forms of compensation.
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Senior Applied Scientist, Security Issue Management
role at
Amazon
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
Other locations (remote options may be available)
Are you interested in building Agentic AI solutions that solve complex builder experience challenges with significant global impact? The Security Tooling team designs and builds high-performance AI systems using LLMs and machine learning that identify builder bottlenecks, automate security workflows, and optimize the software development lifecycle—empowering engineering teams worldwide to ship secure code faster while maintaining the highest security standards.
Key job responsibilities
Design and implement novel AI/ML solutions for complex security challenges and improve builder experience.
Drive advancements in machine learning and science.
Balance theoretical knowledge with practical implementation.
Navigate ambiguity and create clarity in early‑stage product development.
Collaborate with cross‑functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions.
Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results.
Establish best practices for ML experimentation, evaluation, development and deployment.
A day in the life
Integrate ML models into production security tooling with engineering teams.
Build and refine ML models and LLM‑based agentic systems that understand builder intent.
Create agentic AI solutions that reduce security friction while maintaining high security standards.
Prototype LLM‑powered features that automate repetitive security tasks.
Design and conduct experiments (A/B tests, observational studies) to measure downstream impacts of tooling changes on engineering productivity.
Present experimental results and recommendations to leadership and cross‑functional teams.
Gather feedback from builder communities to validate hypotheses.
Basic Qualifications
5+ years of building machine learning models or developing algorithms for business application experience.
PhD, or Master's degree and 6+ years of applied research experience.
Experience programming in Java, C++, Python or related language.
Experience with neural deep learning methods and machine learning.
Preferred Qualifications
Experience with large‑scale machine learning systems such as profiling and debugging and understanding of system performance and scalability.
Experience with modeling tools such as R, scikit‑learn, Spark MLLib, MxNet, Tensorflow, NumPy, SciPy, etc.
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. The compensation for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market and may include equity, sign‑on payments, and other forms of compensation.
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