ML Engineering Intern

**Location:** Los Angeles, CA **Job Type:** Internship **Compensation:** Paid internship; compensation to be discussed based on experience and availability. About the Role We are looking for an ML Engineering Intern to join our team and help build machine learning features that can be integrated into real-world software products. In this role, you will work at the intersection of machine learning and software engineering. You will help prepare data, train and evaluate models, build supporting pipelines, and collaborate with engineers to turn ML experiments into reliable product features. Responsibilities * Develop, test, and evaluate machine learning models * Prepare and process datasets for training and experimentation * Build scripts and pipelines for model training and evaluation * Assist with deploying machine learning models into applications * Work with APIs, backend services, and data pipelines * Monitor and improve model performance * Collaborate with software engineers on ML-powered product features * Research and experiment with new models, frameworks, and techniques * Document experiments, results, and technical decisions * Support testing, debugging, and optimization of ML systems Qualifications * Currently pursuing or recently completed a degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field * Strong familiarity with Python * Basic understanding of machine learning algorithms and model evaluation * Experience with libraries such as PyTorch, TensorFlow, Scikit-learn, or similar tools * Familiarity with data processing using Pandas, NumPy, or related libraries * Basic understanding of APIs and software development principles * Strong analytical and problem-solving skills * Ability to learn quickly and work collaboratively Preferred Qualifications * Experience with LLMs, embeddings, NLP, recommendation systems, or computer vision * Familiarity with model deployment and inference pipelines * Experience with SQL and database technologies * Exposure to Docker, cloud platforms, or MLOps tools * Familiarity with Git and version control * Personal ML projects, research, GitHub contributions, or previous internship experience are a plus What We Value We value practical problem-solving, experimentation, strong engineering fundamentals, and curiosity about modern machine learning technologies. Candidates with hands-on ML projects or software development experience are encouraged to apply.