Amazon Senior Applied Scientist Last Mile Safety Tech 

United States, California 

309870858

Key job responsibilities
As a Senior Applied Scientist, you will research, implement and deploy scientific techniques that span the domain of Computer Vision, Machine Learning, and Sensor Fusion. You will tackle challenging situations every day and have the opportunity to work with multiple technical teams at Amazon. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems.
Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale and complexity.
Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
Run A/B experiments, gather data, and perform statistical analysis.
Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
Research and implement innovative machine learning approaches.Present findings and insights to senior leadership and at internal and external top scientific venues.
Be the thought leader in cutting-edge AI research and proactively pursue IP submissions.

- PhD, or Master's degree and 5+ years of applied research experience
- PhD, or Master's degree in Computer Science, Robotics, Machine Learning, Computer Vision, Electrical and Computer Engineering, or a related field
- 5+ years of hands-on experience in predictive modeling and analysis
- 5+ years of building machine learning models for business application involving geospatial data and telematics signals
- 5+ years of experience applying theoretical models in an applied environment
- 5+ years hands-on experience programming in Java, Python, Perl, C/C++ or other similar programming languages
- Strong analytical, communication and data presentation skills

- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Understanding of characteristics of wireless technologies, such as Wi-Fi and Bluetooth
- Understanding of characteristics of sensor and sensing technology in computer vision, inertial sensors, etc
- Peer-reviewed scientific publications in relevant fields such as geospatial data science, telematics, machine learning, or related areas in relevant conferences such as ACM SIGSPATIAL, KDD, ICASSP, IEEE INFOCOM, and ACM MOBICOM.