Machine Learning Engineer Graduate (E-Commerce Recommendation Foundation) - 2027 Start

1. Participate in the full training lifecycle of Recommendation Foundation Models, including pre-training, mid-training, and post-training.
2. Design and train multimodal semantic tokenizers for recommendation items, leveraging multimodal foundation models to encode rich item content into discrete semantic tokens and raise the performance ceiling of Recommendation Foundation Models.
3. Develop LLM-native recommendation by incorporating recommendation tasks directly into large language model training and leveraging world knowledge to improve recommendation quality.
4. Build the next generation of recommendation systems powered by Recommendation Foundation Models, spanning retrieval, ranking, and end-to-end generative recommendation., We are conducting a confidential search for a Principal Machine Learning Engineer to serve as the senior technical authority for ML systems within a technology organization based i… + 2 days ago

Individuals who are completing or have recently completed a Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics or a related discipline.

• Solid foundation in machine learning and deep learning, with strong interest in LLMs and generative recommendation.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch.

• Self-driven, with a strong research mindset and solid engineering skills. Preferred Qualifications:

• Experience with pre-training, mid-training, or post-training of LLMs or Foundation Models.
• Research or project experience in generative recommendation, LLM-native recommendation, or multimodal semantic tokenization.
• Publications on LLM-related topics at top-tier machine learning or natural language processing conferences, such as NeurIPS, ICML, ICLR, ACL, EMNLP, or NAACL, or strong achievements in major technical competitions.

We believe the future of recommendation is not only about predicting clicks, but about understanding the relationships between people and content and generating new connections. We value original exploration and encourage research thinking and engineering practice equally. Every team member can propose hypotheses and validate ideas in an open environment; your code and publications may help shape the next generation of recommendation systems. We are looking for people with a general-intelligence mindset to redefine recommendation with us. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Aquent Talent

• Redmond, WA
• $60.00-65.00 per hour Join a pioneering technology leader at the forefront of innovation, dedicated to pushing the boundaries of artificial intelligence and robotics. Our mission is to develop groundbre…