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
- Design, build, and deploy production-grade ML models and systems for real-time threat detection, mitigation, and protection against evolving cyber threats at cloud scale.
- Own the full ML lifecycle end-to-end — from problem formulation, data engineering, and model development through to production deployment, monitoring, and continuous improvement.
- Architect and optimize ML pipelines, training infrastructure, and serving systems to meet strict latency, throughput, and reliability requirements at AWS scale.
- Bridge the gap between research and production by translating novel ML approaches into robust, scalable, and maintainable systems that operate in real-time security environments.
- Design and implement feature engineering workflows and large-scale data processing pipelines to support rapid experimentation and reliable model iteration.
- Collaborate closely with software engineering teams to integrate ML models into distributed, low-latency security services, driving engineering decisions around model serving, infrastructure, and system design.
- Analyze large-scale production data to identify patterns, anomalies, and emerging threat vectors, and translate findings into measurable improvements to detection and mitigation capabilities.
- Establish and improve best practices for ML system design, model evaluation, A/B testing, and production monitoring across the team.
- Mentor junior scientists and engineers, raising the bar on both scientific rigor and engineering quality.
Basic Qualifications
- 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 using managed ML/AI solutions
Preferred Qualifications
- 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 with popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience in applied research
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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, CA, Santa Clara - 192,200.00 - 260,000.00 USD annually USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually