Senior Applied AI Engineer - Security for AI

Develop and execute cutting-edge research projects in machine learning and artificial intelligence for cybersecurity, with a focus on cloud security challenges and opportunities. Serve as an expert within team on changes in industry/market trends, products, industry advances, and opportunities in applied technologies across a broad range of applied research areas. Communicate the results and impact of your research and development to senior leadership and external audiences through publications, presentations, and demos. Drive high-stakes negotiations across teams to ensure cutting edge technology is being applied to products in a practical way that meets key business objectives. Write production-ready code to successfully deliver research project into AI product. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science, Artificial Intelligence, Mathematics, Physics, or related field AND 6+ year(s) related industry experience (e.g., statistics, predictive analytics, research) OR Doctorate in Computer Science, Artificial Intelligence, Mathematics, Physics, or related field AND 5+ years related industry experience 5+ years of hands-on experience in programming language such as C#, Python. Ability to problem solve architecture design and coding problems Understanding of statistics, machine learning algorithms and data visualization. Knowledge in large language model, deep learning, transformer models, data engineering, cloud stack technologies, information fusion, large-scale machine learning models. Prior experience in AI product development is preferred not required Experience in working with cross-functional teams, such as product managers, designers, researchers, engineers, and stakeholders, with strong communication, collaboration, and leadership skills, for translating research into a production service. Ability to deal with ambiguity at work; identify research areas independently; shape the direction of research to product in a practical way