Proactive Intelligence, Applied Research Scientist — Agentic Systems and Generative Modeling
Apple
Proactive Intelligence, Applied Research Scientist — Agentic Systems and Generative Modeling
Job Description
AI represents a big opportunity to elevate Apple’s products and experiences for billions of people globally. We are looking for Applied Research Scientists with a background and interest in Agentic Systems. You will be leveraging state-of-the-art Generative models to ship extraordinary products, services, and customer experiences for the iPhone, Mac, Apple Watch, iPad and more. The mission of Proactive Intelligence is to improve Apple platforms by better understanding, anticipating and adapting to user behavior by using machine learning to build phenomenal features that are built right into Apple platforms. Our team provides an opportunity to be part of an incredible research and engineering organization within Apple. The ideal candidate for this role will have industry experience working on a range of modeling problems, including Sequential Decision Making, Reinforcement Learning, Autonomous Systems, Learning from Human Preferences and Training Large Language Models (LLMs). Working knowledge of large-scale data processing especially with structured data, probabilistic modeling and statistics will broaden your role and effectiveness in this position. As an Applied Research Scientist on our team, you will design and implement ML algorithms that process data in different Apple products. You will train Generative AI models and Agentic systems using deep reinforcement learning to solve hard problems. Where necessary, you will also work on integrating ML/RL frameworks into our products to train large-scale agents and leverage cloud services to enable scalable and distributed training/simulation of agent behaviors. You will communicate advanced ideas to a focused team of researchers in the spirit of developing innovative tools and metrics that change the way we look at problems. You will work closely with other cross-functional teams to align messaging, contribute to roadmaps and contribute software back into different repos for proper integration with core systems. You will write clean, maintainable and production code with appropriate documentation and tests. You will contribute to architecture decisions, design reviews and peer code reviews!
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
40,000,000 - 80,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- background in Agentic Systemsintermediate
- leveraging Generative modelsintermediate
- Sequential Decision Makingintermediate
- Reinforcement Learningintermediate
- Autonomous Systemsintermediate
- Learning from Human Preferencesintermediate
- Training Large Language Models (LLMs)intermediate
- large-scale data processingintermediate
- probabilistic modelingintermediate
- statisticsintermediate
- design and implement ML algorithmsintermediate
- train Generative AI modelsintermediate
- deep reinforcement learningintermediate
- integrating ML/RL frameworksintermediate
- leverage cloud servicesintermediate
- scalable and distributed training/simulationintermediate
- communicate advanced ideasintermediate
- developing innovative tools and metricsintermediate
- work closely with cross-functional teamsintermediate
- align messagingintermediate
- contribute to roadmapsintermediate
- contribute software to reposintermediate
- write clean, maintainable and production codeintermediate
- appropriate documentation and testsintermediate
- contribute to architecture decisionsintermediate
- design reviewsintermediate
- peer code reviewsintermediate
Required Qualifications
- Strong programming skills in Python and/or C++ with 3+ years of experience in using these languages for machine learning (ML) modeling and applied research (experience, 3 years)
- M.S. or PhD in Computer Science, or a related fields such as Electrical Engineering, Robotics, Statistics, Applied Mathematics or equivalent experience. A minimum of 3 years of experience in applied ML and/or product development. (experience, 3 years)
- Fundamental knowledge of ML concepts and hands-on experience in building deep-learning systems (experience)
- Strong software engineering skills to create scalable and robust infrastructure for machine-learning data, modeling and evaluation systems (experience)
- Proven ability to train and debug machine-learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework (experience)
Preferred Qualifications
- Familiarity with researching current ML literature and math including optimization methods and modeling techniques (experience)
- Passionate about building extraordinary autonomous systems with Generative AI (experience)
- Creative, collaborative and project focused with an ability to work hands-on in multi-functional teams (experience)
- Proficiency in using ML toolkits such as PyTorch, TensorFlow, SkLearn etc. (experience)
Responsibilities
- As an Applied Research Scientist on our team, you will design and implement ML algorithms that process data in different Apple products. You will train Generative AI models and Agentic systems using deep reinforcement learning to solve hard problems. Where necessary, you will also work on integrating ML/RL frameworks into our products to train large-scale agents and leverage cloud services to enable scalable and distributed training/simulation of agent behaviors. You will communicate advanced ideas to a focused team of researchers in the spirit of developing innovative tools and metrics that change the way we look at problems. You will work closely with other cross-functional teams to align messaging, contribute to roadmaps and contribute software back into different repos for proper integration with core systems. You will write clean, maintainable and production code with appropriate documentation and tests. You will contribute to architecture decisions, design reviews and peer code reviews!
Tags & Categories
Answer 10 quick questions to check your fit for Proactive Intelligence, Applied Research Scientist — Agentic Systems and Generative Modeling @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs
Proactive Intelligence, Applied Research Scientist — Agentic Systems and Generative Modeling
Apple
Proactive Intelligence, Applied Research Scientist — Agentic Systems and Generative Modeling
Job Description
AI represents a big opportunity to elevate Apple’s products and experiences for billions of people globally. We are looking for Applied Research Scientists with a background and interest in Agentic Systems. You will be leveraging state-of-the-art Generative models to ship extraordinary products, services, and customer experiences for the iPhone, Mac, Apple Watch, iPad and more. The mission of Proactive Intelligence is to improve Apple platforms by better understanding, anticipating and adapting to user behavior by using machine learning to build phenomenal features that are built right into Apple platforms. Our team provides an opportunity to be part of an incredible research and engineering organization within Apple. The ideal candidate for this role will have industry experience working on a range of modeling problems, including Sequential Decision Making, Reinforcement Learning, Autonomous Systems, Learning from Human Preferences and Training Large Language Models (LLMs). Working knowledge of large-scale data processing especially with structured data, probabilistic modeling and statistics will broaden your role and effectiveness in this position. As an Applied Research Scientist on our team, you will design and implement ML algorithms that process data in different Apple products. You will train Generative AI models and Agentic systems using deep reinforcement learning to solve hard problems. Where necessary, you will also work on integrating ML/RL frameworks into our products to train large-scale agents and leverage cloud services to enable scalable and distributed training/simulation of agent behaviors. You will communicate advanced ideas to a focused team of researchers in the spirit of developing innovative tools and metrics that change the way we look at problems. You will work closely with other cross-functional teams to align messaging, contribute to roadmaps and contribute software back into different repos for proper integration with core systems. You will write clean, maintainable and production code with appropriate documentation and tests. You will contribute to architecture decisions, design reviews and peer code reviews!
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
40,000,000 - 80,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- background in Agentic Systemsintermediate
- leveraging Generative modelsintermediate
- Sequential Decision Makingintermediate
- Reinforcement Learningintermediate
- Autonomous Systemsintermediate
- Learning from Human Preferencesintermediate
- Training Large Language Models (LLMs)intermediate
- large-scale data processingintermediate
- probabilistic modelingintermediate
- statisticsintermediate
- design and implement ML algorithmsintermediate
- train Generative AI modelsintermediate
- deep reinforcement learningintermediate
- integrating ML/RL frameworksintermediate
- leverage cloud servicesintermediate
- scalable and distributed training/simulationintermediate
- communicate advanced ideasintermediate
- developing innovative tools and metricsintermediate
- work closely with cross-functional teamsintermediate
- align messagingintermediate
- contribute to roadmapsintermediate
- contribute software to reposintermediate
- write clean, maintainable and production codeintermediate
- appropriate documentation and testsintermediate
- contribute to architecture decisionsintermediate
- design reviewsintermediate
- peer code reviewsintermediate
Required Qualifications
- Strong programming skills in Python and/or C++ with 3+ years of experience in using these languages for machine learning (ML) modeling and applied research (experience, 3 years)
- M.S. or PhD in Computer Science, or a related fields such as Electrical Engineering, Robotics, Statistics, Applied Mathematics or equivalent experience. A minimum of 3 years of experience in applied ML and/or product development. (experience, 3 years)
- Fundamental knowledge of ML concepts and hands-on experience in building deep-learning systems (experience)
- Strong software engineering skills to create scalable and robust infrastructure for machine-learning data, modeling and evaluation systems (experience)
- Proven ability to train and debug machine-learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework (experience)
Preferred Qualifications
- Familiarity with researching current ML literature and math including optimization methods and modeling techniques (experience)
- Passionate about building extraordinary autonomous systems with Generative AI (experience)
- Creative, collaborative and project focused with an ability to work hands-on in multi-functional teams (experience)
- Proficiency in using ML toolkits such as PyTorch, TensorFlow, SkLearn etc. (experience)
Responsibilities
- As an Applied Research Scientist on our team, you will design and implement ML algorithms that process data in different Apple products. You will train Generative AI models and Agentic systems using deep reinforcement learning to solve hard problems. Where necessary, you will also work on integrating ML/RL frameworks into our products to train large-scale agents and leverage cloud services to enable scalable and distributed training/simulation of agent behaviors. You will communicate advanced ideas to a focused team of researchers in the spirit of developing innovative tools and metrics that change the way we look at problems. You will work closely with other cross-functional teams to align messaging, contribute to roadmaps and contribute software back into different repos for proper integration with core systems. You will write clean, maintainable and production code with appropriate documentation and tests. You will contribute to architecture decisions, design reviews and peer code reviews!
Tags & Categories
Answer 10 quick questions to check your fit for Proactive Intelligence, Applied Research Scientist — Agentic Systems and Generative Modeling @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs