Use deep learning tools (such as TensorFlow, Keras, or PyTorch) to train a variety of neural network architectures (e.g., multilayer perceptron, convolutional networks, transfer learned networks) to develop effective predictive models
Write production-quality software in Python to implement predictive models and business logic in business software
Use cloud resources (e.g., Amazon Web Services) to prepare and process data
Write software to prepare, clean, and sample data for use in developing predictive models
Write queries to extract data from product databases (SQL and MongoDB) and join data from multiple sources
Use data analysis tools to prepare data visualizations (examples include Tableau, Jupyter Notebooks, Python, Pandas, and R)
Relentlessly iterate solutions within a fast-paced start-up environment where ambiguity and minimal structure are the norm
Solve challenging, uncharted engineering problems
Work in an environment that thrives on teamwork and continuous learning opportunities
What We're Looking For
Bachelor’s degree in applied math, computer science, natural sciences or engineering
M.S. or PhD in a related field a bonus
3+ years of experience with machine learning, regression, and optimization techniques
Experience with deep learning architectures and training methods
Fluent in Python, numpy, scipy, pandas, sklearn and deep learning
Proficient in linear algebra and statistics
Familiar with RESTful APIs
Portfolio demonstrating clean and compliant code
Demonstrated strong attention to detail
Familiar with debugging and automated unit/regression testing
Familiar with versioning systems such as Git
Must be a US citizen, green card holder, or a legal permanent resident of the United States