AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI)
Apple
AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI)
Job Description
The Siri and Information Intelligence team is revolutionizing the way hundreds of millions of people access information on their devices, all while keeping user privacy at the forefront. As an Applied ML team, we're pushing the boundaries of Apple Intelligence, result ranking, and innovative search technologies, all while running a low latency production service. Our work fuels intuitive information experiences across some of Apple's most iconic products, including Siri, Spotlight, Safari, Messages, Lookup, and more. Join us in shaping the future of how the world connects with information! We are looking for a senior Machine Learning Engineer with a passion for using machine learning to build intelligent search applications. Our team researches and implements novel query understanding, ranking and response generation techniques, machine learning algorithms and models that power amazing Search experiences across Apple products. In this role you will have the opportunity to develop LLMs and other NLP models for user productivity and improving Siri's ability to answer personal domain questions. Our team owns models which are responsible for answering users' questions using their personal documents with privacy at the forefront, and that integrates with other Siri capabilities to enable powerful user experiences. Role responsibilities include: - Contribute to research, design, implementation, and evaluation of models to enhance quality and performance, and to support key functions for Personal Q&A. - Implement and extend LLM models with fine-tuning and RLXF methodologies. Develop high quality data pipelines to support these methodologies. - Establish target quality metrics and evaluation sets for the team to track and improve. Design novel experiments to validate/refute hypotheses and support team wide decision making. - Collaborate with partner teams to define product requirements and priorities, and to explore opportunities for enhancements to the Personal Q&A stack. - Develop long-term technical vision for Personal Q&A quality; identify problem areas and integrate solutions as part of a larger roadmap.
Locations
- Santa Clara, California, United States 95050
Salary
Estimated Salary Rangemedium confidence
80,000,000 - 150,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- NLPintermediate
- LLM Developmentintermediate
- Fine-tuningintermediate
- RLHFintermediate
- Data Pipelinesintermediate
- Model Evaluationintermediate
- Query Understandingintermediate
- Rankingintermediate
- Response Generationintermediate
- Researchintermediate
- Experiment Designintermediate
- Collaborationintermediate
- Technical Visionintermediate
Required Qualifications
- 8+ years industry experience in Machine Learning, NLP and applying these techniques at scale (experience, 8 years)
- Strong software engineering skills in mainstream programming languages, such as: Python, Go, C/C++ (experience)
- Experience using ML frameworks (pyTorch, JAX, TensorFlow, XGBoost etc.) (experience)
- Strong communication skills (experience)
- Bachelors in Computer Science (degree in computer science)
Preferred Qualifications
- In-depth knowledge and expertise in training, evaluating, and applying Deep learning models, Large Language Models for production systems (experience)
- Extensive experience in building production ML systems and applications in search, recommendation systems, or information retrieval (experience)
- Ability to quickly prototype ideas / solutions, and perform critical analysis (experience)
- Background in: search relevance and ranking, Q&A, personalization, user behavior/response modeling, or data-driven decision-making (experience)
- Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience (experience)
Responsibilities
- In this role you will have the opportunity to develop LLMs and other NLP models for user productivity and improving Siri's ability to answer personal domain questions. Our team owns models which are responsible for answering users' questions using their personal documents with privacy at the forefront, and that integrates with other Siri capabilities to enable powerful user experiences. Role responsibilities include:
- - Contribute to research, design, implementation, and evaluation of models to enhance quality and performance, and to support key functions for Personal Q&A.
- - Implement and extend LLM models with fine-tuning and RLXF methodologies. Develop high quality data pipelines to support these methodologies.
- - Establish target quality metrics and evaluation sets for the team to track and improve. Design novel experiments to validate/refute hypotheses and support team wide decision making.
- - Collaborate with partner teams to define product requirements and priorities, and to explore opportunities for enhancements to the Personal Q&A stack.
- - Develop long-term technical vision for Personal Q&A quality; identify problem areas and integrate solutions as part of a larger roadmap.
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Answer 10 quick questions to check your fit for AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI) @ Apple.
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AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI)
Apple
AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI)
Job Description
The Siri and Information Intelligence team is revolutionizing the way hundreds of millions of people access information on their devices, all while keeping user privacy at the forefront. As an Applied ML team, we're pushing the boundaries of Apple Intelligence, result ranking, and innovative search technologies, all while running a low latency production service. Our work fuels intuitive information experiences across some of Apple's most iconic products, including Siri, Spotlight, Safari, Messages, Lookup, and more. Join us in shaping the future of how the world connects with information! We are looking for a senior Machine Learning Engineer with a passion for using machine learning to build intelligent search applications. Our team researches and implements novel query understanding, ranking and response generation techniques, machine learning algorithms and models that power amazing Search experiences across Apple products. In this role you will have the opportunity to develop LLMs and other NLP models for user productivity and improving Siri's ability to answer personal domain questions. Our team owns models which are responsible for answering users' questions using their personal documents with privacy at the forefront, and that integrates with other Siri capabilities to enable powerful user experiences. Role responsibilities include: - Contribute to research, design, implementation, and evaluation of models to enhance quality and performance, and to support key functions for Personal Q&A. - Implement and extend LLM models with fine-tuning and RLXF methodologies. Develop high quality data pipelines to support these methodologies. - Establish target quality metrics and evaluation sets for the team to track and improve. Design novel experiments to validate/refute hypotheses and support team wide decision making. - Collaborate with partner teams to define product requirements and priorities, and to explore opportunities for enhancements to the Personal Q&A stack. - Develop long-term technical vision for Personal Q&A quality; identify problem areas and integrate solutions as part of a larger roadmap.
Locations
- Santa Clara, California, United States 95050
Salary
Estimated Salary Rangemedium confidence
80,000,000 - 150,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- NLPintermediate
- LLM Developmentintermediate
- Fine-tuningintermediate
- RLHFintermediate
- Data Pipelinesintermediate
- Model Evaluationintermediate
- Query Understandingintermediate
- Rankingintermediate
- Response Generationintermediate
- Researchintermediate
- Experiment Designintermediate
- Collaborationintermediate
- Technical Visionintermediate
Required Qualifications
- 8+ years industry experience in Machine Learning, NLP and applying these techniques at scale (experience, 8 years)
- Strong software engineering skills in mainstream programming languages, such as: Python, Go, C/C++ (experience)
- Experience using ML frameworks (pyTorch, JAX, TensorFlow, XGBoost etc.) (experience)
- Strong communication skills (experience)
- Bachelors in Computer Science (degree in computer science)
Preferred Qualifications
- In-depth knowledge and expertise in training, evaluating, and applying Deep learning models, Large Language Models for production systems (experience)
- Extensive experience in building production ML systems and applications in search, recommendation systems, or information retrieval (experience)
- Ability to quickly prototype ideas / solutions, and perform critical analysis (experience)
- Background in: search relevance and ranking, Q&A, personalization, user behavior/response modeling, or data-driven decision-making (experience)
- Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience (experience)
Responsibilities
- In this role you will have the opportunity to develop LLMs and other NLP models for user productivity and improving Siri's ability to answer personal domain questions. Our team owns models which are responsible for answering users' questions using their personal documents with privacy at the forefront, and that integrates with other Siri capabilities to enable powerful user experiences. Role responsibilities include:
- - Contribute to research, design, implementation, and evaluation of models to enhance quality and performance, and to support key functions for Personal Q&A.
- - Implement and extend LLM models with fine-tuning and RLXF methodologies. Develop high quality data pipelines to support these methodologies.
- - Establish target quality metrics and evaluation sets for the team to track and improve. Design novel experiments to validate/refute hypotheses and support team wide decision making.
- - Collaborate with partner teams to define product requirements and priorities, and to explore opportunities for enhancements to the Personal Q&A stack.
- - Develop long-term technical vision for Personal Q&A quality; identify problem areas and integrate solutions as part of a larger roadmap.
Tags & Categories
Answer 10 quick questions to check your fit for AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI) @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs