3 дня назад
Senior Machine Learning Engineer (Recommendation Systems)
187 040 - 438 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Machine Learning Engineer (Recommendation Systems) (LLMs, multimodal learning, reinforcement learning): Building cross-scenario foundation models and generative recommendation systems across retrieval, ranking, and re-ranking with an accent on unified modeling, multimodal understanding, and efficient inference. Focus on integrating LLMs and VLMs, optimizing model training and inference, and designing intelligent recommenders that balance system efficiency with user experience.
Location: San Jose, United States; fully in-person up to 5 days per week
Salary: $187,040–$438,000 annually, with potential discretionary bonuses, incentives, and restricted stock units.
Company
USDS Joint Venture develops privacy and cybersecurity safeguards for U.S. user data, applications, algorithms, and content ecosystems operated by TikTok.
What you will do
- Build and optimize cross-scenario shared foundation models for unified modeling and efficient inference.
- Advance event-sequence-driven generative recommendation with multimodal understanding and generative capabilities.
- Apply LLM technologies across retrieval, ranking, and re-ranking, including model training and inference optimization.
- Integrate LLMs and VLMs with recommendation systems to develop adaptive, evolving recommenders.
- Research end-to-end generative recommendation and system co-design methods that balance efficiency and user experience.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.
- 3+ years of experience in machine learning, deep learning, or information retrieval.
- Proficiency in Python and familiarity with mainstream deep learning frameworks such as PyTorch.
- Strong interest in intelligent recommendation systems and a self-driven research mindset.
Nice to have
- PhD in Computer Science, Machine Learning, or a related field.
- Experience developing large-scale recommendation systems or training large models, with notable technical achievements.
- Research experience or publications in LLMs, multimodal learning, reinforcement learning, or generative recommendation.
- Familiarity with pre-training and post-training processes for LLMs or foundation models.
Culture & Benefits
- Research-oriented environment that encourages proposing hypotheses and validating ideas.
- Opportunity for code and research papers to contribute to new recommendation-system paradigms.
- Medical, dental, and vision insurance from day one, plus a 401(k) plan with company match.
- Paid parental leave, disability coverage, life insurance, and wellbeing benefits.
- 10 paid holidays, 10 paid sick days, and 17 days of paid personal time.
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