Applied ML Engineer

As an Applied ML Engineer, you will: Help transform research into production solutions that improve customer protection. Responsibilities include: Design, develop, and evaluate AI-driven detection capabilities using SLMs, agents, multimodal models, and emerging machine learning technologies to identify evolving threats and abuse patterns. Partner with research, engineering, and product teams to translate new ideas into production-ready solutions that deliver measurable customer impact at scale. Own key aspects of the experimentation and evaluation process, including defining success metrics, designing studies, analyzing results, and making data-driven recommendations. Drive deep analysis of model behavior, efficacy, coverage, and operational performance, identifying opportunities to improve customer protection and system efficiency. Collaborate across teams to influence technical direction, share learnings, and contribute to a culture of innovation, scientific rigor, and continuous improvement. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research). OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field. These requirements include, but are not limited to the following specialized security screenings: Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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. 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers). Applied experience with modern AI systems, including LLMs, SLMs, agents, multimodal AI, or related technologies Demonstrated ability to drive problems from idea to measurable customer impact. Experimentation, evaluation, and data-driven decision-making skills Curiosity, learning agility, and a passion for exploring emerging technologies to solve real-world customer problems.