Amazon.com Services LLC
Technology
AppliedScientist,WHS
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Applied Scientist, WHS at Amazon.com Services LLC. Skills: Computer vision, Machine learning, Deep learning, Model deployment. Design computer vision models. Develop computer vision models”
What You'll Achieve.
Reduce safety incidents globally; Improve people's lives
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
3+ years building models, PhD or Master's degree, 4+ years CS, CE, ML, Experience in patents or publications, Experience programming Java, C++, Python, Experience algorithms and data structures, Experience parsing, Experience numerical optimization, Experience data mining, Experience parallel and distributed computing, Experience high-performance computing
Nice to Have
Experience using Unix/Linux, Experience professional software development, Experience training and deploying ML systems, Experience machine learning technologies, Experience Reinforcement Learning, Experience Deep Learning, Experience Computer Vision, Experience Natural Language Processing
What You'll Do.
Design computer vision models
Develop computer vision models
Deploy computer vision models
Design machine learning models
Develop machine learning models
Deploy machine learning models
Develop model architectures
Run experiments on datasets
Collaborate with software engineers
Optimize for inference latency
Optimize for accuracy
Optimize for reliability
Analyze operational data
Identify safety risk patterns
Translate findings into improvements
Stay current with research
Evaluate research applicability
Communicate technical approaches
Contribute to scientific culture
How You'll Work.
Team & Collaboration
Cross-functional teams; Partner with engineers; Partner with safety experts
Communication Scope
Technical documentation; Presentations; Design reviews
Full Job Description
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. Key job 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 About the team Amazon's Workplace Health & S
Applying for this Applied Scientist, WHS role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
ANONYMOUS · UNFILTERED
What do employees actually say about Amazon.com Services LLC?
Real rants from real employees. Read before you apply.