Gali Deutsch

About Gali Deutsch

Innovative AI Software Engineer driving personalization solutions to enhance user experiences at Audible and Amazon through scalable, cloud-native architectures. 5+ years of experience building modular, high-performance infrastructures, from full-stack development to AI-powered applications. Specializes in designing intelligent ranking systems, developing predictive algorithms, and A/B testing. Proficient in Python, Java, AWS, GCP, SQL, TypeScript, JavaScript, React, and Node.js, and key machine learning technologies such as Scikit-learn, Pandas, NumPy, Spark, and NLTK. Passionate about leveraging big data and advancing AI technologies to solve complex, real-world problems. Graduated with an MSc in Artificial Intelligence from Florida Atlantic University, with a focus in Machine Learning and Natural Language Processing.

Experience

1. Software Development Engineer

   Audible

   Mar 2023 — Present · Newark, NJ, US

   Architects and implements data-driven ranking systems as an integral member of the Content Discovery Team, optimizing audiobook recommendations on Amazon and contributing to growth for both Amazon and Audible. Transforms product promotion through advanced recommendation systems, leading to improved content discovery and measurable increases in user engagement and conversion rates across digital platforms.• Leads cross-functional high-visibility feature launches, presenting solutions to business partners and establishing team standards. Drives strategic planning and execution of key milestones, managing stakeholders to deliver impactful results. • Mentors junior engineers by providing technical guidance, leading coding workshops, sharing best practices, and supporting professional growth through regular feedback, career development, and knowledge sharing.• Designs and implements robust, scalable cloud-native architectures on AWS, improving reliability and performance within Amazon and Audible ecosystems. Spearheads technical solutions that enhance team productivity and expand system capabilities, ensuring infrastructure supports growth. Reduces recommendation latency, optimizing user experience during peak traffic events, such as Prime Day and the holiday season.• Collaborates with data scientists on A/B testing across Amazon and Audible platforms, targeting specific customer segments and leveraging advanced traffic lane segmentation to validate recommendation strategies. • Conducts data analyses to evaluate potential input feature effectiveness by developing predictive algorithms that identify user interaction patterns, enabling precise targeting in digital content discovery.• Manages on-call engineering, ensuring production stability and large-scale data pipeline performance. Minimizes critical incident resolution time by proactively monitoring, optimizing CI/CD pipelines, and mitigating risks.

Education

• Israel Tech Challenge <itc>

  Full-Stack Coding Bootcamp

  2018 — 2018

• Florida Atlantic University

  Master of Science - MS

  2020 — 2022

• University of Central Florida

  BA

  2012 — 2015