2 of 2 DemandTrendContract Generative AI Jobs in Surrey

of artificial intelligence? Do you thrive on solving complex challenges and developing cutting-edge solutions. We are seeking a talented Natural Language Processing (NLP) Engineer to join a AI Research Team and contribute to ground-breaking innovations in AI. What You’ll Do: Conduct cutting-edge research to tackle real-world AI challenges. Develop high-quality … to ensure reproducible and impactful research. Review state-of-the-art research papers and create prototype solutions that redefine what’s possible. Publish your findings in top-tier AI conferences and journals, showcasing your work to the global research community Who You Are: A PhD holder in ML/AI, Computer Science/Engineering, or a … related field. A strong foundation in Mathematics, Machine Learning, NLP, and Deep Learning. Hands-on experience in one or more of these areas: Generative AI, Parameter-efficient Fine-tuning, Model Compression, Foundation Models, Large Language Models (LLMs), Data/Model Privacy, or Prompting Methods. First-author publications in prestigious ML/AI conferences/ More ❯

Role and Responsibilities As a forward-thinking company at the forefront of innovation, we seek an individual passionate about pushing the boundaries of AI: Conduct cutting-edge research to develop state-of-the-art solutions or propose novel research challenges based on real-world case studies in AI. Develop high-quality code with detailed documentation to support reproducible … research in local and international AI communities. Review state-of-the-art research papers and develop prototype solutions. Publish findings in top-tier conferences and journals, such as NeurIPS, ICML, ICLR, EMNLP, CVPR, ICCV, ECCV, AAAI, ACL, IEEE TPAMI, IEEE TNNLS, IJCV, and JMLR. Skills and Qualifications Pursuing or completed PhD in ML/AI, Computer … and computer science (algorithms, data structures, parallel/distributed computing). Strong fundamentals in Machine Learning, Computer Vision, and Deep Learning. Hands-on experience in areas such as Generative AI, Foundation Models, Parameter-Efficient Fine-Tuning (PEFT), Data/Model Privacy, or Model Optimization for Multi-Task Learning. First-author publications in top ML/AI More ❯