Machine Learning Intern

POSITION SUMMARY

As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer experiences. Therefore, building and deploying state-of-the-art machine learning systems to drive impact via our data capabilities is key. To guarantee the success of machine learning systems, we need to provide a detailed formulation, extensive experimentation, and to transform ML models into high-performance production-level code, including not only implementing sophisticated machine learning algorithms but also robustness monitoring and system logging/alarming. 

 We seek talented and motivated students and recent graduates with a strong background in machine learning, deep learning, language models and generative AI, programming, and data analysis to join our 12-week Machine Learning Internship Program. You will work on real-world projects, collaborate with experienced professionals, gain valuable experience in the fintech industry, and realize business and social impact. This role requires hybrid work from our Mountain View office, with 2 days a week in person. This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program. 

WHAT YOU'LL DO 

• Train and fine-tune large-scale Foundation Models to support various fintech product use cases
• Work with a large dataset, including structured and unstructured data
• Help in ensuring improvements in our current ML systems via model, data, or experimentation upgrades
• Gain hands-on experience with a wide array of technologies, including PyTorch, AWS, Kafka, Databricks, etc

WHAT WE'RE LOOKING FOR

• Actively pursuing a Master's or PhD in Computer Science, Information Technology, or a related field
• Located in Mountain View, or have the ability to relocate there, for the duration of the internship 
• Strong understanding of statistical models, familiarity, and in-depth understanding of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large-scale models, Sequence Transformer models 
• Interest in multimodal or multitask learning across structured, sequential, and behavioral data
• Familiarity with AI tools, harness engineering, agentic workflow, etc.
• Hands-on programming experience in Python and ML frameworks such as PyTorch
• Equipped with good verbal and written communication skills
• A background demonstrating strong problem-solving skills
• Committed to taking ownership of projects, conducting thorough investigations, and driving initiatives to conclusion