Generative AI Engineer
TalentportUnited States
Posted December 11, 2025
Full Time
About the Company
Talentport specializes in sourcing top-tier remote talent for small and medium enterprises, focusing on software engineering, digital marketing, and creative design roles. Candidates undergo rigorous screening and testing in communication and technical skills, ensuring only the top 3% are presented to clients. The firm’s disciplined selection process delivers results-oriented professionals who drive growth and reduce manpower costs by up to 70%. Talentport’s commitment to quality and cost efficiency sets it apart as a trusted partner for companies seeking high-impact remote talent.
Job Description
The Generative AI Engineer will be responsible for researching and analyzing the latest research papers in Generative AI, designing and developing state-of-the-art Generative AI models, and implementing them using various frameworks.
Requirements
- Master's or Ph.D. degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Mathematics, Physics, or related fields
- Deep knowledge/experience in the Generative AI domain
- Advanced Python programming: Practical experience with deep learning frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
- Deep learning fundamentals: Understanding of neural networks, Transformers, and attention mechanisms
- Generative AI model implementation experience: Development/implementation experience with at least one Generative AI model (LLM, diffusion models, GANs, etc.)
- Design and implementation experience of algorithms based on the latest research papers in Computer Vision or Natural Language Processing
- Research project experience with independent algorithm development and publication in academic conferences/journals
- Experience applying research outcomes to actual products and achieving performance improvements
- Experience analyzing specific technical challenges in real projects and proposing/implementing concrete solutions
- Ability to address complex technical problems with creative approaches
