The role involves building intelligent systems that enhance the security of AWS physical locations through computer vision and machine learning. You will collaborate with software engineers and Applied Scientists to develop and optimize machine learning models for real-time security decisions. The team values innovation and operational excellence, focusing on automating processes and improving efficiency. You will be responsible for the entire lifecycle of ML model deployment, ensuring high reliability and low-latency performance across AWS regions.

• 3+ years of non-internship professional software development experience
• 2+ years of experience in design or architecture of new and existing systems
• Experience with Machine Learning and Large Language Model fundamentals
• 1+ years of experience in designing and developing large-scale software applications using C#, C++, Java, or Perl
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
• 3+ years of experience in the full software development life cycle

• Build and deploy machine learning models that automate real-time physical security decisions across all AWS regions.
• Partner with Applied Scientists to operationalize research models into production-grade inference pipelines.
• Own the full ML model lifecycle, including training infrastructure, real-time serving, monitoring, and iteration.
• Design and implement low-latency, high-reliability distributed systems for model serving at scale.
• Build computer vision pipelines that process video and image data for automated threat detection.
• Develop and maintain Infrastructure as Code (IaC) for all ML and application infrastructure.
• Monitor model performance in production, identify drift, and drive continuous improvement.
• Contribute to system design and architecture decisions that balance innovation with operational excellence.
• Participate actively in code reviews, providing meaningful feedback to peers and senior engineers.
• Collaborate cross-functionally with security operations, hardware, and product teams to define requirements.
• Drive operational excellence through automation, runbooks, and proactive risk mitigation.
• Mentor team members and contribute to a culture of knowledge sharing and technical growth.

• Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.