Software Development Trainee

• Work on challenging AI/ML projects addressing fraud prevention, credit risk assessment, and real-time data-driven decision-making
• Help develop and enhance an agentic AI platform that automates workflows and assists decision-making
• Develop platforms and tools to process, enrich, and optimize core company data
• Design, implement, and evaluate machine learning models
• Work with big data technologies for data ingestion, processing, and analysis
• Partner with experienced engineers and researchers to solve technical challenges and contribute to innovative projects
• Present research findings and project outcomes to the team and stakeholders

• Currently pursuing a Bachelor's degree in Computer Science, Machine Learning, Software Engineering, or related field
• Will have completed at least the Sophomore year of school at the start of the internship
• Proficient in coding, including Python, Java, or Go
• Proficient in automated testing and system monitoring
• Solid understanding of machine learning algorithms, techniques, and best practices
• Experience with data analysis, manipulation, and visualization
• Experience with cloud computing platforms such as AWS, Azure, or GCP preferred
• Familiarity with DevOps practices and tools preferred
• Contributions to open-source projects or publications in relevant conferences preferred
• Familiarity with data ingestion, cleaning, processing, enrichment, SQL, data warehouses, ELT, AI/ML, anomaly detection, and related tools preferred
• Strong desire to solve customer and business problems through thoughtful and effective solutions
• Desire to learn robust design solutions for small to medium-scale problems or system components
• Ability to clearly communicate technical ideas and collaborate effectively with team members
• Highly motivated, curious, and eager to explore new technologies and apply them to enhance productivity and deliverables
• Enthusiasm for working with big data technologies, AI/ML, risk engineering, and cloud infrastructure

• 13-week paid internship program
• Mentorship
• Professional development
• Weekly learning experiences
• Remote, hybrid, and onsite options
• Potential for full-time employment or extended roles during the school year for high-performing interns