Location: Manhattan, NY
Type: Full-time Internship (Onsite – 5 days per week)
Department: AI & Data Science
About the Role
As a Seasonal DS Intern in the core Research Team at Forty5Park, you will play a hands-on role in advancing generative AI and intelligent systems within the real estate domain. You’ll support efforts related to Large Language Models (LLMs), Multimodal LLMs, and Multi-Component Platforms (MCP) to help shape the next generation of AI-powered products and capabilities.
You’ll contribute to building scalable AI systems that power the the Forty5Park Platform, enabling seamless integration and rapid development of generative and agentic applications in real estate. You’ll collaborate with Data Engineering and Platform Engineering teams to deliver reliable, high-performance solutions — while gaining end-to-end experience in AI development and deployment.
You’ll also have the opportunity to work alongside and support senior AI talent on live projects, assisting with model experimentation, fine-tuning, evaluation, and implementation of next-generation AI architectures in real-world environments.
Key Responsibilities
- Work hands-on with generative AI models and multimodal LLMs to design and deploy innovative solutions within the LLM Suite platform.
- Bridge research and engineering, contributing to the development of scalable AI and automation tools.
- Design and implement production-ready microservices and APIs that accelerate AI solution delivery.
- Collaborate with Data Engineering and Platform Engineering teams to enhance performance, scalability, and integration workflows.
- Assist senior engineers and researchers in developing, testing, and deploying cutting-edge AI systems.
- Contribute to a culture of experimentation, collaboration, and continuous learning within the AI organization.
Required Qualifications, Capabilities, and Skills
- Currently enrolled in or recently completed a PhD program in a quantitative or technical discipline (e.g., Computer Science, Computer Engineering, AI/ML, or related field).
- Equivalent project experience or advanced applied AI work will also be considered.
- Strong foundation in machine learning theory, with expertise in NLP, Reinforcement Learning (RL), and/or Computer Vision.