Responsibilities include, but not limited to:

• Build and maintain data/solution pipelines that feed machine learning models
• Work in a technical team through development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics using machine learning and artificial intelligence
• Design and optimize data structures in data management systems (Hadoop, Snowflake, and Cloud platforms) to enable AI/ML solutions.
• Build custom software components and analytics applications
• Create/ Maintain CI/CD pipelines of machine learning solutions in the cloud

Education Qualifications:

• Technical Degree required. Computer Science or Statistics background highly desired

Minimum Qualifications:

• Experience in building and executing end-to-end ML systems automating training, testing and deploying Machine Learning models
• Familiarity with machine learning frameworks (TensorFlow, PyTorch, scikit-learn, etc.)
• Familiarity with software architecture (data structures, data schemas, etc.).
• Software development skills and the desire to work on cutting edge development in a Cloud environment
• Strong scripting and programming skills in one of the following, Python or Java
• Experience with continuous integration/continuous delivery (CI/CD) tools (Jenkins, Git, Docker, Kubernetes)
• Experience developing Machine Learning or A.I. solutions with either Python, AWS, AZURE, GCP
• 3+ years building scalable ETL pipelines
• 3+ years of experience with big data processing and/or developing applications and data sources
• 3+ years of strong working knowledge of databases (Oracle, MS SQL, Snowflake, or BigQuery)
• Outstanding analytical thinking, interpersonal, oral and written communication skills
• Proficiency in the Microsoft Office suite
• Ability to prioritize and meet critical project timelines in a fast-paced environment
• Self-motivated and team oriented

Preferred:

• Deep knowledge of math, probability, statistics and algorithms Demonstrated ability to study and transform data science prototypes into production solutions
• Knowledge of computer vision and/or signal processing including techniques for classification and feature extraction.