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Senior Applied Scientist, Perimeter Protection Applied Science
Seattle, Washington, USAPosted 2 days ago
Full-timeonsite
Job Description
Join the AWS Perimeter Protection team as a Senior Applied Scientist, where you will bring your deep ML engineering expertise to design, build, and scale AI-driven security solutions that protect AWS customers worldwide. This role is ideal for someone who has already built and shipped production ML systems at industry scale and is looking to apply that experience to high-impact security challenges. You will own the full ML lifecycle — from research and prototyping to production deployment and optimization — powering services including Web Application Firewall, DDoS Protection, Bot Management, and Infrastructure Protection. With services spanning all AWS regions and handling trillions of requests per week, you will solve complex engineering and science problems where model performance, system reliability, and low-latency inference are critical.
Key job responsibilities
- Develop and implement advanced AI/ML models and algorithms to enhance the capabilities of our security services, enabling proactive threat detection, mitigation, and protection against evolving cyber threats.
- Collaborate with security engineers and researchers, to understand business/domain requirements, analyze data patterns, and translate insights into actionable solutions.
- Design and drive implementation of data pipelines and ETL processes to ingest, process, and analyze large-scale security data from multiple sources, ensuring data quality and integrity.
- Conduct in-depth data analysis, feature engineering, and model evaluation to continuously improve the performance and accuracy of AI/ML-based security solutions.
- Participate in the development and deployment of AI/ML models into production environments, ensuring scalability, reliability, and performance at cloud scale.
- Collaborate with cross-functional teams to ensure seamless integration of AI/ML solutions with our security services and infrastructure.
- Contribute to the development of best practices, documentation, and knowledge-sharing within the team and the broader organization.
- Engage in research and exploration of emerging technologies and techniques relevant to AI/ML-based security solutions, stay up-to-date with the latest trends cybersecurity, and incorporate new techniques and methodologies into our security offerings.
Join the AWS Perimeter Protection team as a Senior Applied Scientist, where you will bring your deep ML engineering expertise to design, build, and scale AI-driven security solutions that protect AWS customers
- 3+ years of building machine learning models 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
- Experience in building machine learning models for business application
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience in applied research
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience using managed ML/AI solutions
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
Key job responsibilities
- Develop and implement advanced AI/ML models and algorithms to enhance the capabilities of our security services, enabling proactive threat detection, mitigation, and protection against evolving cyber threats.
- Collaborate with security engineers and researchers, to understand business/domain requirements, analyze data patterns, and translate insights into actionable solutions.
- Design and drive implementation of data pipelines and ETL processes to ingest, process, and analyze large-scale security data from multiple sources, ensuring data quality and integrity.
- Conduct in-depth data analysis, feature engineering, and model evaluation to continuously improve the performance and accuracy of AI/ML-based security solutions.
- Participate in the development and deployment of AI/ML models into production environments, ensuring scalability, reliability, and performance at cloud scale.
- Collaborate with cross-functional teams to ensure seamless integration of AI/ML solutions with our security services and infrastructure.
- Contribute to the development of best practices, documentation, and knowledge-sharing within the team and the broader organization.
- Engage in research and exploration of emerging technologies and techniques relevant to AI/ML-based security solutions, stay up-to-date with the latest trends cybersecurity, and incorporate new techniques and methodologies into our security offerings.
Join the AWS Perimeter Protection team as a Senior Applied Scientist, where you will bring your deep ML engineering expertise to design, build, and scale AI-driven security solutions that protect AWS customers
- 3+ years of building machine learning models 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
- Experience in building machine learning models for business application
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience in applied research
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience using managed ML/AI solutions
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually