AI Engineer (Intern / Early Contributor)

About the Role

As an AI Engineer Intern, you'll work on cutting-edge machine learning models and AI-powered features that enhance our payment platform. From fraud detection and risk assessment to personalized user experiences and automated support, you'll help build the intelligence layer of our fintech ecosystem.

You'll collaborate with our engineering and product teams, contribute to real-world AI applications, and gain hands-on experience deploying machine learning models at scale. This is a part-time, equity-based role perfect for someone eager to apply AI/ML in a high-impact fintech environment.

What You'll Do

• Build and train machine learning models for fraud detection and risk assessment
• Develop AI-powered features for transaction analysis and anomaly detection
• Implement natural language processing for customer support automation
• Create recommendation systems for personalized financial services
• Optimize model performance and deploy ML pipelines to production
• Collaborate with backend engineers to integrate AI features into our platform
• Analyze user behavior data to improve predictive models
• Research and experiment with new AI/ML techniques relevant to fintech

You'll Thrive Here If You

• Have experience with Python and ML libraries (TensorFlow, PyTorch, scikit-learn)
• Understand machine learning fundamentals and model training workflows
• Are familiar with data preprocessing, feature engineering, and model evaluation
• Have worked on personal or academic ML projects
• Can translate business problems into ML solutions
• Enjoy experimenting with algorithms and optimizing performance
• Are passionate about AI applications in fintech and financial inclusion
• Can commit to part-time hours with flexibility as projects evolve

Bonus Points

• Experience with fraud detection, anomaly detection, or risk modeling
• Knowledge of NLP and large language models (LLMs)
• Familiarity with MLOps tools and model deployment (Docker, Kubernetes, MLflow)
• Understanding of cloud ML services (AWS SageMaker, Google Vertex AI, Azure ML)
• Experience with time-series forecasting or recommendation systems
• Previous work in fintech, payments, or financial services
• Contributions to open-source ML projects or published research
• Understanding of data privacy and security in AI systems