Description
As a Fintech company where Machine Learning (ML) is a key driver of growth, our operations highly rely on machine learning models, from business decisions to customer experiences. 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 realise 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.
Responsibilities:
- 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
Requirements:
- 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 behavioural 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