Applied Scientist, Optics

Responsibilities

• Design and develop ML 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 enable 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 multi-modal fusion (combining video and sensor data), few-shot learning for rare security events, and reinforcement learning for dynamic response prioritization
• Advise team members on ML best practices, 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 (Signals, Access Control Management, Analytics) 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 experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

• Experience using Unix/Linux
• Experience in professional software development

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 optional Supplemental life plans), EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage, 401(k) matching, paid time off, parental leave.

Learn more about our benefits at (Use the "Apply for this Job" box below)..

• USA, MD, Annapolis Junction -  -  USD annually
• USA, NY, New York -  -  USD annually
• USA, VA, Herndon -  -  USD annually

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