AI Engineer (Finance)An AI Engineer implements and scales data science models leveraging big data tools and programming frameworks. The AI Engineer is responsible for taking AI models using machine learning algorithms and deep learning neural networks and helping scale them out to production level models that can accommodate terabytes of real-time data. The AI Engineer applies different tools and techniques to allow for processing data and develops and maintains AI systems. This position requires access to confidential supervisory information and/or FOMC information, which is limited to "Protected Individuals" as defined in the U.S. federal immigration law. Protected Individuals include, but are not limited to, U.S. citizens, U.S. nationals, and U.S. permanent residents who either are not yet eligible to apply for naturalization or who have applied for naturalization within the requisite timeframe. Candidates who are not U.S. citizens or U.S. permanent residents may be eligible for the information access required for this position and sponsorship for a work visa, and subsequently for permanent residence, if they sign a declaration of intent to become a U.S. citizen and meet other eligibility requirements. In addition, all candidates must undergo an enhanced background check and comply with all applicable information handling rules, and all non-U.S. citizens must sign a declaration of intent to become a U.S. citizen and pursue a path to citizenship. Essential Accountabilities Supports development of predictive models using machine learning, econometric modeling, and data mining techniques (text mining and natural language processing) to measure, monitor and predict various measures of financial risk. Contributes to analytic projects through all stages of development, but is primarily responsible for end-user product development, deployment, monitoring, and maintenance of production models and tools. Works closely with data scientists, business intelligence architects, and business-line partners to improve existing machine learning models. Has intermediate level programming skills to transform large and moderately complex datasets in a manner that is optimized for models in production. Visualizes and reports out on data sets, integrity and completeness using a variety of methods to promote understanding of key insights and actionable takeaways for both technical and non-technical audiences. Delivers presentations, create analytical reports and executive summaries of data findings. Intermediate knowledge of the latest trends in technology and translates those into opportunities to enhance our customer's technology needs. Education and Experience Bachelor's degree in Computer Science or related data-driven field 3+ years of related work experience Intermediate level experience in application of advanced quantitative techniques in Data Science, Statistics or other quantitative field Understanding of and ability to build in the technology landscape including open source, commercial on-premises, and cloud-based tools Knowledge of banking and financial markets Intermediate level experience with cloud-based architecture and AI tools Intermediate experience with Linux-based systems Intermediate level experience in machine learning technology, especially in the field of Deep Learning / Deep Neural Networks and Natural Language Processing or Optical Character Recognition (for example, TensorFlow, Pytorch, Sci-kit Learn, Spacy) Intermediate level experience in Hadoop, Spark, Storm or related paradigms Intermediate level experience in engineering SaaS applications to operationalize and scale machine learning models Intermediate experience working with large data sets Intermediate experience with statistical programming using packages such as Python, R, SAS, or Matlab. Experience with Java, C++, or Scala a plus Intermediate experience with DevOps and automation tools like Git, GitLab, Kubernetes, Docker, DVC, Metaflow Communication skills - both written and verbal. Ability to deliver presentations and draft publication-quality reports The Federal Reserve Bank of Cleveland is an Equal Opportunity Employer. We are dedicated to sustaining an environment in which diversity is valued and differences are strengths. It is the Bank's policy to provide equal employment opportunity for all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, gender identity or expression, genetic information or sexual orientation. Physical Demands and General Working Conditions Employees typically sit most of the day, work with a computer and may answer/respond to phone calls. Physical movement consists of walking for meetings, breaks, etc. Ability to lift items weighing approximately 20 pounds on a limited basis is required. Employees may be required to travel by car/air.