Description
We’re representing a Machine Learning and Computer Vision scientist who is currently working for a recently acquired AI startup and is open to new challenges.
Highlights
- Trained deep learning computer vision models in Tensorflow, primarily for object detection and semantic segmentation, including training data curation and preparation
- Designed Dockerized deep learning cloud microservices for image annotation and anonymization
- Implemented production systems in Python to deploy deep models and more traditional data science algorithms operating on both image and lidar point cloud data
- Sole investigator on internal and customer-facing projects involving machine learning with an emphasis on natural language processing applications: topic extraction, sentiment analysis, automated prioritization of messages
Education
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Ph.D. in Mathematics
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BS in Physics
Technical skills
- Machine learning and natural language processing with an emphasis on deep learning
- Emphasis on Tensorflow, PyTorch, Caffe
- Export of deep learning models for Tensorflow Serving
- Deployment of GPU-accelerated models to AWS using Nvidia-docker
- Metasploit and Kali Linux penetration testing toolkits
- Scripting in Python and Ruby
- Statistics and data analysis with Python, MATLAB, and R
- SQL and NoSQL databases, including PostgreSQL, Amazon Redshift, MongoDB
- Web applications powered by Ruby, Rails, Django, Flask