Applied Scientist, WHS Data-Tech
About The Position
We're looking for an Applied Scientist to develop computer vision and machine learning models that keep Amazon's workforce safe. Your research and models will be deployed across hundreds of operations facilities globally, helping to reduce safety incidents for over 1.5 million people. You'll join a team where science meets real-world impact. You'll design and train models for tasks like activity recognition, anomaly detection, object detection, and risk prediction using video, image, and sensor data from Amazon's operational environments. You'll work closely with software engineers to take your models from experimentation through production deployment at scale. If you're excited about applying advanced ML research to a problem that genuinely improves people's lives, and you thrive in an environment where your work ships to production, not just to a paper, this is the role for you. About the team Amazon's Workplace Health & Safety (WHS) organization is responsible for keeping over 1.5 million employees safe across our global retail operations. Within WHS, our technology team builds the science and engineering capabilities that power Amazon's safety strategy at scale. We're a cross-functional group of applied scientists, software engineers, data engineers, and technical program managers developing computer vision systems, generative AI applications, sensor and IoT solutions, and analytics platforms - all aimed at reducing workplace injuries. As an applied scientist here, you'll partner directly with engineers who build the production infrastructure for your models, and with safety domain experts who ground your work in real operational needs. Our culture values scientific rigor, fast iteration, and shipping models that create measurable safety outcomes.
Requirements
- 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
Nice To Haves
- Experience using Unix/Linux
- Experience in professional software development
- Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in development or technical support
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
- PhD, or a PhD or equivalent research experience and experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience with video and image processing and compression algorithms and standards, computer vision and/or machine learning
Responsibilities
- Design, develop, and deploy computer vision and machine learning models for workplace safety applications (e.g., activity recognition, anomaly detection, pose estimation, object detection)
- Develop and iterate on model architectures using deep learning frameworks, running experiments on large-scale video, image, and sensor datasets
- Collaborate with software engineers to productionize models - optimizing for inference latency, accuracy, and reliability in edge and cloud environments
- Analyze operational data to identify patterns and signals indicating safety risks, and translate findings into actionable model improvements
- Stay current with the latest research in computer vision, deep learning, and related fields, and evaluate applicability to safety use cases
- Communicate findings and technical approaches clearly to both technical and non-technical stakeholders through documents, presentations, and design reviews
- Contribute to the team's scientific culture through code reviews, knowledge sharing, and mentorship
Benefits
- sign-on payments
- restricted stock units (RSUs)
- 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
- parental leave
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Principal
