Reflexive Concepts is seeking an Artificial Intelligence/Machine Learning (AI/ML) Engineer to join our team!  The Artificial Intelligence/Machine Learning (AI/ML) Engineer designs, creates, tests, and productizes AI/ML algorithms to solve business challenges. The AI/ML models they create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. The AI/ML Engineer should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation. The AI/ML Engineer needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. The AI/ML Engineer may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI-related matters, so must have exceptional analytical, problem-solving and communication skills. Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus. Requirements: 10 years experience deploying machine learning algorithms is required. A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university is required. 7 additional years machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree. Demonstrated abilities in software engineering and AI/ML model test and evaluation. Capabilities: Select appropriate data sets Perform statistical analysis Run machine learning algorithms Use results to improve models Train and retrain systems when needed Experience in working with various ML libraries and packages Run standard test and evaluation protocols Provide system integration oversight Oversee Test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements Research and implement a broad range of AI and ML algorithms and tools Design or Select appropriate data and knowledge representation methods Recognize software architecture, data modelling, and data structures Transform and convert data science prototypes into scalable solutions Verify data and model output quality Identify differences in data distribution that affect model performance Develop criteria for test and evaluation to include explainability and resiliency Deep understanding of AI logic, semantics, ontologies, and knowledge representation Demonstrated ability to design, evaluate, and productize AI/ML models on a range of commercial cloud-based architectures Design ML algorithms according to customer requirements Research, experiment with, and implement suitable ML algorithms and tools Broaden current AIML frameworks and machine learning libraries