Machine Learning Intern

Summary: GenPark is an agentic discovery platform for global commerce that focuses on marketing in the agent-first era. They are seeking a Machine Learning Intern to assist in designing, training, and evaluating machine learning models for their platform, contributing to production-ready pipelines and collaborating with product and engineering teams. Responsibilities: - Assist in designing, training, and evaluating machine learning and deep learning models that power GenPark’s agentic discovery platform - Perform data exploration, feature engineering, model experimentation, and performance tuning under the guidance of senior engineers and researchers - Help prototype and deploy models for recommendation, personalization, and behavioral prediction, contributing to production-ready pipelines - Document methods, participate in code reviews, collaborate with product and engineering teams, and present findings to stakeholders Required 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 Preferred Qualifications: - 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 Required Skills: Computer Science, Algorithms, Machine Learning, Deep Learning, PyTorch, TensorFlow, Statistics, Python, NumPy, pandas, scikit-learn, Git, Recommender Systems, Spark, Distributed Systems Benefits: Hybrid work arrangement that allows some work from home