Come build intelligent systems that secure the foundation of our cloud using computer vision and applied machine learning to automate real-time production decisions that protect every AWS location globally.
The Amazon Optics team builds and manages services used by AWS employees to secure our physical sites. Our services allow customers to protect AWS locations and preserve the trust that all AWS users have in us. You will work with other software development engineers and Applied Scientists every day to build, deploy, and optimize machine learning models that automate real-time security decisions at scale. The models you build and operate will run across every AWS region, making automated determinations that directly impact the physical security posture of every AWS customer.
You will partner directly with Applied Scientists to translate research into production-grade inference pipelines. You will own the full lifecycle of ML model deployment: from training infrastructure through real-time serving, monitoring, and iteration. You will build the systems that take a model from notebook to production, ensuring low-latency inference at scale with high reliability.
Our team provides solutions where "can't be done" is not an answer. You will stretch yourself and grow. You will share your knowledge with others and help others achieve. You will be empowered to automate away operational inefficiencies for both the team and our customers. You will solve complex architecture problems with solutions that are extensible and scale, yet always look for ways to simplify. You will work with the team on multiple products deployed to every AWS region using AWS services in a fully IaC deployment environment where you own everything end to end: design, development, testing, deploying.
You will join a team that values strong intuition but seeks metrics and data to validate assumptions.
Key job responsibilities
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: training infrastructure, real-time serving, monitoring, retraining, 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
BASIC QUALIFICATIONS
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Knowledge of machine learning model architecture and inference
PREFERRED QUALIFICATIONS
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
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, MD, Annapolis Junction - 143,700.00 - 194,400.00 USD annually
USA, NY, New York - 158,100.00 - 213,800.00 USD annually
USA, VA, Arlington - 143,700.00 - 194,400.00 USD annually
USA, VA, Herndon - 143,700.00 - 194,400.00 USD annually
