This role will have the chance to work closely on Natural Language response generation models make improvements and perform scalable evaluation that will impact Apple Users and broader AIML community. Role responsibilities include:- Contribute on research design implementation and evaluation of algorithms and models to enhance the quality and performance of personalized response generation models.- Use advanced NLP deep learning and LLM techniques to generate grounded responses for user intent.- Analyze loss patterns in the current search and assistant stack and come up with insights algorithms and techniques to resolve quality gaps with the goal of improving the top-line product metrics.- Develop a long-term technical vision; propose a roadmap for team setting clear objectives.- Collaborate with teams across the company to define product requirements and prioritize ranking criteria that optimize user satisfaction.- Establish metrics and continuously improve performance of models by applying innovative ML techniques.
4 years Experience in Machine Learning NLP and applying these techniques at scale
Strong software engineering skills in mainstream programming languages such as: Python Go C/C
Strong communication skills
Bachelors in Computer Science and industry work experience
In-depth knowledge and expertise in applying Deep learning models Large Language Models and their evaluations
Extensive experience in building production quality systems or applications in search recommendation systems or information retrieval
Experience using ML frameworks (pyTorch JAX TensorFlow XGBoost etc.)
Ability to quickly prototype ideas / solutions and perform critical analysis
Background in: personalization user behavior modeling and data-driven decision-making
Advance degree (Masters or Ph.D.) in Computer Science Statistics or related field or equivalent industry work experience
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