LLM Post-training Research Intern

Company Description Waybox builds AI-native in-car hardware and software designed to transform the driving experience. The company’s core product, MILES, is a multimodal companion that can see, hear, and respond to drivers in real time. By combining practical assistance with emotionally intelligent support, MILES offers a human-centered presence that helps people feel safer, more focused, and more connected on the road. Waybox focuses on cutting-edge AI, thoughtful product design, and responsible innovation to bring intelligent driving companions to everyday vehicles.

Role Description The Model Post-Train Intern will support the refinement and deployment of AI models used in the MILES in-car companion system. This full-time, hybrid role is based in the San Francisco Bay Area, with a blend of on-site collaboration and some work-from-home flexibility. Day-to-day responsibilities may include evaluating and testing trained models, analyzing performance metrics, assisting with model optimization and fine-tuning, and helping prepare models for real-world integration into hardware and software systems. The intern will work closely with machine learning engineers and product teams to improve model reliability, responsiveness, and safety. Additional tasks may involve documenting experiments, contributing to data pipelines, and supporting internal tools used to monitor and maintain model performance.

Qualifications

• Strong foundation in machine learning and AI concepts, including model training, evaluation, and optimization.
• Proficiency with common ML tools and frameworks (e.g., Python, PyTorch, TensorFlow, data analysis libraries).
• Ability to work with datasets, perform experiments, and interpret quantitative performance metrics.
• Clear written and verbal communication skills for documenting findings and collaborating with cross-functional teams.
• Comfort working in a hybrid environment in the San Francisco Bay Area, with effective time management and self-direction.
• Enrollment in or completion of a degree in Computer Science, Data Science, Electrical Engineering, or a related technical field.
• Interest in automotive technology, human-centered AI, and building real-world AI products is highly beneficial.
• Prior internship or project experience with applied ML, model deployment, or edge/embedded AI is a plus.