- Company Description Gen
- Park is an agentic discovery platform for global commerce that brings marketing into the agent-first era.
- The company builds Intelligent Brand Agents and User Agents that continuously learn from behavior and context to connect products, content, and experiences with the right consumers.
- By orchestrating personalized AI content, interactive agents, and immersive video, Gen
- Park helps brands discover, engage, and convert global Gen Z audiences more efficiently.
- Gen
- Park operates at the intersection of AI, commerce, and digital media, offering a fast-paced environment for those interested in scalable machine learning systems.
- Team members work on cutting-edge personalization technologies that directly impact how brands reach and serve modern consumers.
Role Description This is a full-time Machine Learning Intern role based in San Jose, CA, with a hybrid work arrangement that allows some work from home. The intern will assist in designing, training, and evaluating machine learning and deep learning models that power GenPark’s agentic discovery platform.
Day-to-day tasks include data exploration, feature engineering, model experimentation, and performance tuning under the guidance of senior engineers and researchers. The intern will help prototype and deploy models for recommendation, personalization, and behavioral prediction, contributing to production-ready pipelines.
Responsibilities also include documenting methods, participating in code reviews, collaborating with product and engineering teams, and presenting findings to stakeholders.
Qualifications
- Strong foundation in Computer Science and Algorithms, including data structures, complexity analysis, and problem-solving skills.
- Practical knowledge of Machine Learning and Deep Learning, with experience in building and training models using frameworks such as PyTorch or TensorFlow.
- Background in Statistics, including probability, hypothesis testing, and basic experimental design for model evaluation.
- Currently pursuing or recently completed a degree in Computer Science, Data Science, Electrical Engineering, or a related technical field.
- Proficiency in Python and common ML libraries (e.g., NumPy, pandas, scikit-learn), and familiarity with version control tools such as Git.
- Ability to work in a hybrid environment, collaborate with cross-functional teams, and communicate technical concepts clearly to non-technical partners.
- Experience with recommender systems, personalization, or large-scale data processing (e.g., Spark, distributed systems) is a plus.
- Interest in AI applications for digital media, marketing technology, and consumer behavior analytics is highly beneficial.
