Machine Learning and Artificial Intelligence PhD Internship

What you'll do

• Research and develop new machine learning methods, theories, and state-of-the-art technologies.
• Design and implement innovative solutions for complex machine learning problems.
• Apply machine learning techniques to solve ambitious problems in areas like LLMs, diffusion models, and reinforcement learning.
• Challenge existing metrics and protocols to advance the field of artificial intelligence.
• Integrate research prototypes into production applications as part of applied ML engineering.
• Conduct experiments and investigations to evaluate interactive systems and human interactions.
• Prepare and present technical work to leadership at the end of the internship.
• Submit research findings for publication in peer-reviewed academic conferences.

What we're looking for

• Must be pursuing a doctoral (PhD) degree in Computer Science, Computer Engineering, Data Science, Applied Mathematics, or a related field.
• Must return to school after the internship or have the internship as the final requirement for graduation.
• Proficiency with object-oriented programming languages such as Python, Swift, Objective C, or Java.
• Experience with machine learning libraries including TensorFlow, PyTorch, CoreFlow, and Sklearn.
• Practical knowledge of building and adapting algorithms for machine learning, speech, multimodal sensing, and related areas.
• Excellent mathematical skills in linear algebra and statistics.
• Demonstrated expertise in fields such as statistics, econometrics, operations research, causal inference, or optimization.
• Experience with research-focused tasks including publishing academic research in peer-reviewed venues.