Amazon
Software Development Engineer, Amazon Optics
$144K–$214K
New York, NY +2 · Full-time · Posted Sep 11, 2026
- Location
- New York, NY
Annapolis Junction, MD
Herndon, VA - Experience
- 3+ years professional software development; 2+ years design or architecture; 1+ years large-scale software development.
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
About the job
Build and operate computer vision and machine learning systems that automate real-time physical security decisions across AWS locations.
What you'll do
- Deploy and maintain ML models and production inference pipelines, including training infrastructure, serving, monitoring, and iteration.
- Design low-latency, reliable distributed systems and computer vision pipelines for threat detection; maintain Infrastructure as Code.
- Collaborate with scientists and cross-functional teams on architecture, operations, code reviews, and model improvement.
What they ask for
- 3+ years of non-internship professional software development experience.
- 2+ years of non-internship design or architecture experience involving design patterns, reliability, and scaling.
- Experience with Machine Learning and Large Language Model fundamentals, including model architecture, training/inference lifecycles, and optimization.
- 1+ years designing and developing large-scale software applications or systems using C#, C++, Java, or Perl; Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
Nice to have
- 3+ years of full software development life cycle experience.
- Bachelor's degree in computer science or equivalent.
Pay
143,700.00 - 194,400.00 USD annually (base salary); 158,100.00 - 213,800.00 USD annually (base salary); 143,700.00 - 194,400.00 USD annually (base salary)
Tools
C#, C++, Java, Perl, Infrastructure as Code (IaC)
AI focus
Build and deploy computer vision and machine learning models for automated security decisions; operationalize research into inference pipelines and manage model training, serving, monitoring, retraining, and iteration. Requirements also include Machine Learning and Large Language Model fundamentals.
Model-written summary · the original posting is authoritative