PhD, or Master's degree or Bachelor’s degree with 8+ years of CS, CE, ML or related field experience
8+ years experience of software development working in large-scale distributed technology environments
3+ years of experience with machine learning and neural deep learning methods, modeling tools such as scikit-learn, numpy, scipy, Tensorflow, MxNet, Spark MLLib, etc., and applying AI/ML methods for business applications such as recommender systems, user modeling, knowledge graphs, ranking, reinforcement learning, etc.
Strong analytical, strategic thinking, problem-solving and communication skills
End-to-end hands on experience in building large scale data processing systems, large scale machine learning systems, and big data/cloud technologies (e.g. AWS, Google Cloud, Azure)
Expert level proficiency in Java, Python, Web Technologies, Design & Architecture
Knowledge of building AI native applications
Guides the applicability of AI to customer problems through a deep understanding of the value and limitations of AI technologies.
Understands evaluation tools to validate and measure the accuracy of solutions.
High-level understanding of how AI models work, the different types of AI models that exist, and their pros and cons.
Understanding of the latest tools and technologies that apply AI to real-world applications.
Self-motivated attitude with the ability to multitask and thrive in a timeline-driven and fast changing environment
Ability to take a project from scoping requirements through actual launch of the project.
Knowledge of current trends and best practices in the modern SaaS technology landscape, state-of-the-art machine learning techniques
Experience in Scrum, Agile Process, Unit Testing & Test-Driven Development.
Great business acumen with a passion to solve for the customer