Artificial Intelligence/Machine Learning Engineer 3 - (Python, Java, Machine Learning)

Akina, Inc is seeking an Artificial Intelligence/Machine Learning Engineer 3 to support the VISTA project and related AI/ML work. The role designs, evaluates, productizes, integrates, and improves AI/ML algorithms and models, while providing system integration oversight and potentially leading geographically diverse teams.

Responsibilities:

• Designs, creates, tests, and productizes AI/ML algorithms to solve business challenges
• Creates AI/ML models capable of learning and making predictions as defined by the business logic developed to meet customer requirements
• Is proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation
• Needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance
• Designs and creates scalable solutions for optimal performance through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback
• May be responsible for leading geographically diverse teams
• Will often serve as a primary POC for AI-related matters
• Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus
• Demonstrated abilities in software engineering and AI/ML model test and evaluation
• 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