Machine Learning - Data Scientist - ASE
Apple
Machine Learning - Data Scientist - ASE
Job Description
Imagine what you could do here. At Apple, great new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! Are you passionate about music, movies, and the world of Artificial Intelligence and Machine Learning? So are we! Join our Human-Centered AI team for Apple Products. In this role, you'll represent the user perspective on new features, review and analyze data, and evaluate AI models powering everything from search and recommendations to other innovative features. Collaborate with Data Scientists, Researchers, and Engineers to drive improvements across our platforms. Our team is comprised of very talented individuals who are passionate about LLM and ensuring Apple services are at their best. As part of the Human-Centered AI team, you'll play a central role in enhancing the user experience. Responsibilities include: - Collaborate with Engineering, Products, Research, Operations, and Editorial teams to evaluate algorithms and AI models powering various features, identifying opportunities for improvement. - Build data products (feature datasets, analyses, models, etc.) and scalable tools (typically in Python or Scala) to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management. - Create structured evaluations to assess the quality of AI-generated responses, ensuring they align with company standards and customer expectations. - Create evaluation task design and guidelines; identify a relevant data annotation platform to run evaluations at scale. - Implement metrics to measure the effectiveness and accuracy of models to ensure they meet performance standards. - Establish data quality thresholds and reporting on metrics & insights to inform feature business decisions. - Monitor LLM performance in production environments through human evaluations, identifying trends, and raising alerts when quality degradation occurs. - Perform detailed failure analysis to understand model weaknesses and identify areas for improvement, offering actionable insights to engineers - Maintain high standards for data quality and continuously enhance processes based on both quantitative and qualitative feedback
Locations
- Singapore, Singapore, Singapore 569141
Salary
Estimated Salary Rangemedium confidence
25,000,000 - 60,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- passion for Artificial Intelligence and Machine Learningintermediate
- passion for music and moviesintermediate
- user perspective representationintermediate
- data review and analysisintermediate
- AI model evaluationintermediate
- collaboration with Data Scientistsintermediate
- collaboration with Researchersintermediate
- collaboration with Engineersintermediate
- LLM expertiseintermediate
- data product buildingintermediate
- feature dataset creationintermediate
- data analysisintermediate
- model buildingintermediate
- scalable tool development in Pythonintermediate
- scalable tool development in Scalaintermediate
- hypothesis generationintermediate
- collaborative decision-makingintermediate
- structured evaluation creationintermediate
- AI-generated response quality assessmentintermediate
- evaluation task designintermediate
- guideline creationintermediate
- data annotation platform identificationintermediate
- metric implementation for model effectivenessintermediate
- metric implementation for model accuracyintermediate
- data quality threshold establishmentintermediate
- metric reportingintermediate
- insight reportingintermediate
- LLM performance monitoringintermediate
- human evaluationsintermediate
- trend identificationintermediate
- quality degradation alertingintermediate
- detailed failure analysisintermediate
- model weakness understandingintermediate
- actionable insight provisionintermediate
- data quality maintenanceintermediate
- process enhancementintermediate
- quantitative feedback utilizationintermediate
- qualitative feedback utilizationintermediate
Required Qualifications
- Experience with machine learning concepts, including model evaluation metrics, and data analysis. Proven data analysis expertise using SQL, Python, and Tableau to deliver actionable insights (experience)
- Experience with Large Language Models and evaluation techniques (experience)
- Fluency in English reading, writing and comprehension skills to partner with international teams (experience)
- Fluent in either Chinese, Japanese, Hindi, Korean, French, Spanish, German, to support the language specific market (experience)
- Cultural understanding of one of the above mentioned language markets to accurately represent user experience in early development cycles (experience)
Preferred Qualifications
- Ability to analyze complex issues, and identify potential problems with LLM outputs to improve quality with keen attention to detail (experience)
- Effective collaboration with cross-functional teams to define ML/LLM evaluation requirements (experience)
- Experience crafting, conducting, analyzing, and interpreting experiments and investigations (experience)
- Excellent communication skills (experience)
- Flexibility to work early morning or late night shift patterns required (experience)
Responsibilities
- Our team is comprised of very talented individuals who are passionate about LLM and ensuring Apple services are at their best. As part of the Human-Centered AI team, you'll play a central role in enhancing the user experience.
- Responsibilities include:
- - Collaborate with Engineering, Products, Research, Operations, and Editorial teams to evaluate algorithms and AI models powering various features, identifying opportunities for improvement.
- - Build data products (feature datasets, analyses, models, etc.) and scalable tools (typically in Python or Scala) to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management.
- - Create structured evaluations to assess the quality of AI-generated responses, ensuring they align with company standards and customer expectations.
- - Create evaluation task design and guidelines; identify a relevant data annotation platform to run evaluations at scale.
- - Implement metrics to measure the effectiveness and accuracy of models to ensure they meet performance standards.
- - Establish data quality thresholds and reporting on metrics & insights to inform feature business decisions.
- - Monitor LLM performance in production environments through human evaluations, identifying trends, and raising alerts when quality degradation occurs.
- - Perform detailed failure analysis to understand model weaknesses and identify areas for improvement, offering actionable insights to engineers
- - Maintain high standards for data quality and continuously enhance processes based on both quantitative and qualitative feedback
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning - Data Scientist - ASE @ Apple.
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Machine Learning - Data Scientist - ASE
Apple
Machine Learning - Data Scientist - ASE
Job Description
Imagine what you could do here. At Apple, great new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! Are you passionate about music, movies, and the world of Artificial Intelligence and Machine Learning? So are we! Join our Human-Centered AI team for Apple Products. In this role, you'll represent the user perspective on new features, review and analyze data, and evaluate AI models powering everything from search and recommendations to other innovative features. Collaborate with Data Scientists, Researchers, and Engineers to drive improvements across our platforms. Our team is comprised of very talented individuals who are passionate about LLM and ensuring Apple services are at their best. As part of the Human-Centered AI team, you'll play a central role in enhancing the user experience. Responsibilities include: - Collaborate with Engineering, Products, Research, Operations, and Editorial teams to evaluate algorithms and AI models powering various features, identifying opportunities for improvement. - Build data products (feature datasets, analyses, models, etc.) and scalable tools (typically in Python or Scala) to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management. - Create structured evaluations to assess the quality of AI-generated responses, ensuring they align with company standards and customer expectations. - Create evaluation task design and guidelines; identify a relevant data annotation platform to run evaluations at scale. - Implement metrics to measure the effectiveness and accuracy of models to ensure they meet performance standards. - Establish data quality thresholds and reporting on metrics & insights to inform feature business decisions. - Monitor LLM performance in production environments through human evaluations, identifying trends, and raising alerts when quality degradation occurs. - Perform detailed failure analysis to understand model weaknesses and identify areas for improvement, offering actionable insights to engineers - Maintain high standards for data quality and continuously enhance processes based on both quantitative and qualitative feedback
Locations
- Singapore, Singapore, Singapore 569141
Salary
Estimated Salary Rangemedium confidence
25,000,000 - 60,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- passion for Artificial Intelligence and Machine Learningintermediate
- passion for music and moviesintermediate
- user perspective representationintermediate
- data review and analysisintermediate
- AI model evaluationintermediate
- collaboration with Data Scientistsintermediate
- collaboration with Researchersintermediate
- collaboration with Engineersintermediate
- LLM expertiseintermediate
- data product buildingintermediate
- feature dataset creationintermediate
- data analysisintermediate
- model buildingintermediate
- scalable tool development in Pythonintermediate
- scalable tool development in Scalaintermediate
- hypothesis generationintermediate
- collaborative decision-makingintermediate
- structured evaluation creationintermediate
- AI-generated response quality assessmentintermediate
- evaluation task designintermediate
- guideline creationintermediate
- data annotation platform identificationintermediate
- metric implementation for model effectivenessintermediate
- metric implementation for model accuracyintermediate
- data quality threshold establishmentintermediate
- metric reportingintermediate
- insight reportingintermediate
- LLM performance monitoringintermediate
- human evaluationsintermediate
- trend identificationintermediate
- quality degradation alertingintermediate
- detailed failure analysisintermediate
- model weakness understandingintermediate
- actionable insight provisionintermediate
- data quality maintenanceintermediate
- process enhancementintermediate
- quantitative feedback utilizationintermediate
- qualitative feedback utilizationintermediate
Required Qualifications
- Experience with machine learning concepts, including model evaluation metrics, and data analysis. Proven data analysis expertise using SQL, Python, and Tableau to deliver actionable insights (experience)
- Experience with Large Language Models and evaluation techniques (experience)
- Fluency in English reading, writing and comprehension skills to partner with international teams (experience)
- Fluent in either Chinese, Japanese, Hindi, Korean, French, Spanish, German, to support the language specific market (experience)
- Cultural understanding of one of the above mentioned language markets to accurately represent user experience in early development cycles (experience)
Preferred Qualifications
- Ability to analyze complex issues, and identify potential problems with LLM outputs to improve quality with keen attention to detail (experience)
- Effective collaboration with cross-functional teams to define ML/LLM evaluation requirements (experience)
- Experience crafting, conducting, analyzing, and interpreting experiments and investigations (experience)
- Excellent communication skills (experience)
- Flexibility to work early morning or late night shift patterns required (experience)
Responsibilities
- Our team is comprised of very talented individuals who are passionate about LLM and ensuring Apple services are at their best. As part of the Human-Centered AI team, you'll play a central role in enhancing the user experience.
- Responsibilities include:
- - Collaborate with Engineering, Products, Research, Operations, and Editorial teams to evaluate algorithms and AI models powering various features, identifying opportunities for improvement.
- - Build data products (feature datasets, analyses, models, etc.) and scalable tools (typically in Python or Scala) to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management.
- - Create structured evaluations to assess the quality of AI-generated responses, ensuring they align with company standards and customer expectations.
- - Create evaluation task design and guidelines; identify a relevant data annotation platform to run evaluations at scale.
- - Implement metrics to measure the effectiveness and accuracy of models to ensure they meet performance standards.
- - Establish data quality thresholds and reporting on metrics & insights to inform feature business decisions.
- - Monitor LLM performance in production environments through human evaluations, identifying trends, and raising alerts when quality degradation occurs.
- - Perform detailed failure analysis to understand model weaknesses and identify areas for improvement, offering actionable insights to engineers
- - Maintain high standards for data quality and continuously enhance processes based on both quantitative and qualitative feedback
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning - Data Scientist - ASE @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs