AI Machine Learning Engineer

REQUIRED: TO BE CONSIDERED FOR THIS POSITION YOU MUST HAVE AN ACTIVE TS/SCI W/ FULL SCOPE POLYGRAPH SECURITY CLEARANCE (U.S. CITIZENSHIP REQUIRED) - 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. - 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. Responsibilities - 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 Compensation - We are committed to providing fair and competitive compensation. - The salary range for this position is $78,000 to $250,000 per year. - This range reflects the compensation offered across the locations where we hire. - The exact salary will be determined based on the candidate's work location, specific role, skill set, and level of expertise. Benefits - We offer a comprehensive benefits package, including: Health Coverage - Medical, dental, and vision insurance Additional Insurance - Basic Life/AD&D, Voluntary Life/AD&D, Short and Long-Term Disability, Accident, Critical Illness, Hospitalization Indemnity, and Pet Insurance Retirement Plan - 401(k) plan with company match Paid Time Off - Generous PTO, paid holidays, parental leave, and more Wellness - Access to wellness programs and mental health support Professional Development - Opportunities for growth, including tuition reimbursement Additional Perks - Flexible work arrangements, including remote work options - Flexible Spending Accounts (FSAs) - Employee referral programs - Bonus opportunities - Technology allowance - A diverse, inclusive, and supportive workplace culture