Applied Scientist, Optics

About the Role

Amazon Optics is building a unified physical security platform that consolidates alarm management, device monitoring, and video surveillance data. The Applied Scientist will develop AI/ML services to automate false alarm resolution, enable intelligent signal processing, and deliver predictive insights from security event data. The role focuses on large‑language‑model (LLM) based systems and computer‑vision applications to support security teams across Amazon’s global infrastructure.

• Design and develop machine‑learning models for automated alarm triage, false alarm suppression, and anomaly detection across physical security signal streams (access control events, intrusion alarms, video analytics triggers).
• Build and optimize LLM‑based systems that allow security operators to query, summarize, and interact with incident data using natural language.
• Develop predictive models that identify emerging security patterns, correlate multi‑source signals, and enable proactive incident response before threats materialize.
• Research and implement computer‑vision applications for video‑based threat detection, object classification, and automated situational awareness during active incidents.
• Architect end‑to‑end ML pipelines from data ingestion through model training, evaluation, deployment, and monitoring in production.
• Collaborate with software engineers to integrate ML solutions into the Optics platform’s real‑time event processing infrastructure.
• Define evaluation frameworks including precision/recall metrics for alarm classification, latency requirements for real‑time inference, and A/B testing protocols for model improvements.
• Own model performance in production, including drift detection, retraining cadences, and incident‑driven model updates.
• Identify and scope ambiguous problem areas where ML can transform incident response workflows, even when the business problem is not yet fully defined.
• Drive scientific breakthroughs in areas such as multimodal fusion, few‑shot learning for rare security events, and reinforcement learning for dynamic response prioritization.
• Advise team members on best practices for model selection, feature engineering, and experimental design.
• Influence product roadmaps by translating scientific capabilities into customer‑facing features that reduce mean time to resolution and false alarm rates.
• Engage with cross‑functional stakeholders—including security operations, hardware engineering, and partner teams—to align scientific investments with operational needs.
• Reduce false alarm rates through intelligent signal classification and contextual filtering.
• Decrease mean time to detection and resolution for genuine security incidents.
• Increase automation coverage for routine incident types, freeing human operators for complex threat assessment.
• Publish internal research and contribute to the broader ML/security community through papers and patents.

• 3+ years of building models for business application.
• PhD or Master’s degree with 4+ years of experience in CS, CE, ML, or a related field.
• Experience in patents or publications at top‑tier peer‑reviewed conferences or journals.
• Proficiency in Java, C++, Python, or a related language.
• Experience in one or more of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing.

• Experience using Unix/Linux.
• Professional software‑development experience.

Salary range: MD: $142,800 – $193,200 annually; NY: $172,400 – $223,400 annually; VA: $142,800 – $193,200 annually. Compensation includes sign‑on payments and restricted stock units (RSUs). Optional benefits include health, dental, vision, prescription, basic life & AD&D insurance, supplemental life plans, employee assistance program, mental‑health support, medical advice line, flexible spending accounts, adoption and surrogacy reimbursement, 401(k) matching, paid time off, and parental leave.

Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.