Amazon Applied Scientist Jobs (NOW HIRING)

Amazon Optics owns the design, delivery, and operation of the unified physical security platform that protects Amazon's global infrastructure. We consolidate alarm management, device monitoring, and video surveillance data to deliver real-time situational awareness and actionable insights for security professionals. We work on complex challenges spanning automated threat detection, signal processing, and AI-driven security evaluation, and we are looking for talented people who want to help protect Amazon's people, assets, and operations at scale.
You will join a diverse team of software engineers, data scientists, security specialists, and operations managers

You will collaborate with teams across Amazon to deliver the highest standards for physical security while enabling our customers to scale their security operations efficiently. You will experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Come work for the Optics Incident Response Tech team, specializing in the detection, triage, and resolution of physical security incidents across Amazon's global footprint. We are looking for an Applied Scientist who is passionate about applying artificial intelligence and machine learning to physical security operations

You will build services and tools that leverage AI/ML to automate false alarm resolution, enable intelligent signal processing, and deliver predictive insights from security event data. You will be part of a team building Large Language Model (LLM)-based services focused on enabling security teams to interact with alarm, access control, and video surveillance data in real time. The team works in close collaboration with other Optics services including Signals, Access Control Management, Video Surveillance and Analytics to power automated mitigations that protect Amazon's global infrastructure.

If you are excited about transforming physical security operations through applied science, we would love to talk to you.
Key job 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
About the team
Our team and customers are distributed across the globe with most of our team members on the East Coast heavily concentrated in the DMV area and JFK and some members in the Seattle area.
Diverse Experiences
Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply

If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why Amazon Security?
At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.
Inclusive Team Culture
In Amazon Security, it's in our nature to learn and be curious

Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.
Training & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony

Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.