This role will have the chance to create and evaluate new retrieval and ranking algorithms models and methods that will impact Apple and the broad AIML community. Role responsibilities include: Lead the design implementation and evaluation of algorithms and models to enhance the quality and performance of personalized retrieval and ranking systems. Use advanced and state-of-the-art NLP deep learning and LLM techniques to understand and match complex queries with relevant content. 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. Collaborate with cross-functional teams across the company to define product requirements and prioritize ranking criteria that optimize user satisfaction. Work continuously on improving the metrics and performance of models the teamhas launched in production by leverage innovative ML techniques.
- 3 years Experience in Machine Learning NLP Large Language Models 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
- Knowledge and expertise in Information Retrieval Ranking or Recommendation Systems
- 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
This role will have the chance to create and evaluate new retrieval and ranking algorithms models and methods that will impact Apple and the broad AIML community. Role responsibilities include: Lead the design implementation and evaluation of algorithms and models to enhance the quality and performa...
This role will have the chance to create and evaluate new retrieval and ranking algorithms models and methods that will impact Apple and the broad AIML community. Role responsibilities include: Lead the design implementation and evaluation of algorithms and models to enhance the quality and performance of personalized retrieval and ranking systems. Use advanced and state-of-the-art NLP deep learning and LLM techniques to understand and match complex queries with relevant content. 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. Collaborate with cross-functional teams across the company to define product requirements and prioritize ranking criteria that optimize user satisfaction. Work continuously on improving the metrics and performance of models the teamhas launched in production by leverage innovative ML techniques.
- 3 years Experience in Machine Learning NLP Large Language Models 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
- Knowledge and expertise in Information Retrieval Ranking or Recommendation Systems
- 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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