Machine Learning Engineer Intern

4w4 weeks ago

Adobe

San Jose, US · Internship · $90,000 – $110,000

About this role

Adobe is looking for a Machine Learning intern to apply AI and machine learning techniques to big-data problems. The role helps Adobe better understand, lead and optimize customer experiences using predictive models, experimental design methods, and optimization techniques. Projects include real-time online media optimization, sales operation analytics, and customer lifetime value prediction.

The intern will develop predictive models on large-scale datasets to address business problems with statistical modeling, machine learning, and analytics techniques. They will implement scalable, efficient, and interpretable modeling algorithms for production systems. Collaboration with product management and engineering groups will develop new products and features.

All 2026 Adobe interns will be co-located hybrid, working between assigned office and home. Interns base in the office where their manager and team are located for collaboration and best employee experience. Managers determine office frequency to meet priorities.

Adobe is committed to creating exceptional employee experiences where everyone is respected with equal opportunity. New ideas can come from everywhere, and the next big idea could be yours. Join a mission to hire the very best and empower impact through innovative AI-powered platforms.

Requirements

Currently enrolled full time pursuing Bachelor's, Master’s or PhD in Computer Science, Computer Engineering, or equivalent with expected graduation December 2026 – June 2027
Good understanding of statistical modeling, machine learning, deep learning, or data analytics concepts
Proficient in one or more programming languages such as Python, Java and C
Familiar with one or more machine learning or statistical modeling tools such as R, Matlab and scikit-learn
Strong analytical and quantitative problem-solving ability
Ability to participate in a full-time internship between May-September

Responsibilities

Develop predictive models on large-scale datasets to address various business problems with statistical modeling, machine learning, and analytics techniques
Develop and implement scalable, efficient, and interpretable modeling algorithms that work with large-scale data in production systems
Collaborate with product management and engineering groups to develop new products and features
Apply predictive models to projects like real-time online media optimization and sales operation analytics
Use experimental design methods for customer churn scoring and management
Build optimization techniques for customer understanding and product recommendation
Conduct customer lifetime value prediction using machine learning

Benefits

Co-located hybrid work between office and home
Based in office with manager and team for collaboration and support
Exceptional employee experiences with equal opportunity
Passionate environment empowering people to create and transform customer interactions