Machine Learning Infrastructure and Data Engineer
Apple
Machine Learning Infrastructure and Data Engineer
Job Description
The Video Computer Vision organization is working on exciting technologies for future Apple products. Our team delivers computer vision and machine learning algorithms that power many Apple technologies human understanding and human intelligence algorithms with applications for digital humans, health and AI. In this role, you will work closely with our team of experts in computer graphics, computer vision and machine learning to develop robust ML infrastructure for solving large-scale data challenges to help deliver new algorithms for Apple products and bring high impact to millions of users. Join us as an ML Infrastructure Engineer and become the architect behind the data pipelines that power tomorrow's breakthrough AI/ML innovations. You'll be the critical link between ambitious algorithmic vision and real-world implementation—building the robust, scalable infrastructure that turns cutting-edge research into production-ready systems. We don't just use tools—we build them. You'll have complete ownership of the infrastructure that fuels our ML algorithms from conception to deployment, designing and orchestrating distributed compute systems that process massive datasets at scales few engineers ever encounter. Working shoulder-to-shoulder with AIML researchers and engineers in a small, agile team, you'll drive the creation of scalable infrastructure for ground truth data delivery, orchestrate massive distributed compute tasks across petabyte-scale datasets, develop novel validation frameworks, and help define strategic data collection approaches that push the boundaries of what's achievable. Your contributions won't just support algorithms—they'll directly shape product direction, unlock entirely new AI/ML capabilities, and define what's possible at Apple.
Locations
- Sunnyvale, California, United States 94085
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
- computer visionintermediate
- machine learningintermediate
- computer graphicsintermediate
- ML infrastructureintermediate
- data pipelinesintermediate
- distributed compute systemsintermediate
- orchestrating distributed compute tasksintermediate
- validation frameworksintermediate
- data collectionintermediate
Required Qualifications
- BS and a minimum of 3 years relevant industry experience (experience, 3 years)
- Experience processing large, complex, unstructured data. (experience)
- Software engineering skills with extensive experience in Python. (experience)
- Self-motivated, with an ability to drive projects from concept to production, balancing requirements with technical quality and development timelines. (experience)
Preferred Qualifications
- MS or PhD computer science or related discipline, or 5+ years of related industry experience. (experience, 5 years)
- Excellent communication and experience working with multi-functional teams. (experience)
- Passion for delivering high quality software to end-users. (experience)
- Experience with machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment. (experience)
Responsibilities
- Join us as an ML Infrastructure Engineer and become the architect behind the data pipelines that power tomorrow's breakthrough AI/ML innovations. You'll be the critical link between ambitious algorithmic vision and real-world implementation—building the robust, scalable infrastructure that turns cutting-edge research into production-ready systems. We don't just use tools—we build them. You'll have complete ownership of the infrastructure that fuels our ML algorithms from conception to deployment, designing and orchestrating distributed compute systems that process massive datasets at scales few engineers ever encounter. Working shoulder-to-shoulder with AIML researchers and engineers in a small, agile team, you'll drive the creation of scalable infrastructure for ground truth data delivery, orchestrate massive distributed compute tasks across petabyte-scale datasets, develop novel validation frameworks, and help define strategic data collection approaches that push the boundaries of what's achievable. Your contributions won't just support algorithms—they'll directly shape product direction, unlock entirely new AI/ML capabilities, and define what's possible at Apple.
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Answer 10 quick questions to check your fit for Machine Learning Infrastructure and Data Engineer @ Apple.
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Machine Learning Infrastructure and Data Engineer
Apple
Machine Learning Infrastructure and Data Engineer
Job Description
The Video Computer Vision organization is working on exciting technologies for future Apple products. Our team delivers computer vision and machine learning algorithms that power many Apple technologies human understanding and human intelligence algorithms with applications for digital humans, health and AI. In this role, you will work closely with our team of experts in computer graphics, computer vision and machine learning to develop robust ML infrastructure for solving large-scale data challenges to help deliver new algorithms for Apple products and bring high impact to millions of users. Join us as an ML Infrastructure Engineer and become the architect behind the data pipelines that power tomorrow's breakthrough AI/ML innovations. You'll be the critical link between ambitious algorithmic vision and real-world implementation—building the robust, scalable infrastructure that turns cutting-edge research into production-ready systems. We don't just use tools—we build them. You'll have complete ownership of the infrastructure that fuels our ML algorithms from conception to deployment, designing and orchestrating distributed compute systems that process massive datasets at scales few engineers ever encounter. Working shoulder-to-shoulder with AIML researchers and engineers in a small, agile team, you'll drive the creation of scalable infrastructure for ground truth data delivery, orchestrate massive distributed compute tasks across petabyte-scale datasets, develop novel validation frameworks, and help define strategic data collection approaches that push the boundaries of what's achievable. Your contributions won't just support algorithms—they'll directly shape product direction, unlock entirely new AI/ML capabilities, and define what's possible at Apple.
Locations
- Sunnyvale, California, United States 94085
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
- computer visionintermediate
- machine learningintermediate
- computer graphicsintermediate
- ML infrastructureintermediate
- data pipelinesintermediate
- distributed compute systemsintermediate
- orchestrating distributed compute tasksintermediate
- validation frameworksintermediate
- data collectionintermediate
Required Qualifications
- BS and a minimum of 3 years relevant industry experience (experience, 3 years)
- Experience processing large, complex, unstructured data. (experience)
- Software engineering skills with extensive experience in Python. (experience)
- Self-motivated, with an ability to drive projects from concept to production, balancing requirements with technical quality and development timelines. (experience)
Preferred Qualifications
- MS or PhD computer science or related discipline, or 5+ years of related industry experience. (experience, 5 years)
- Excellent communication and experience working with multi-functional teams. (experience)
- Passion for delivering high quality software to end-users. (experience)
- Experience with machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment. (experience)
Responsibilities
- Join us as an ML Infrastructure Engineer and become the architect behind the data pipelines that power tomorrow's breakthrough AI/ML innovations. You'll be the critical link between ambitious algorithmic vision and real-world implementation—building the robust, scalable infrastructure that turns cutting-edge research into production-ready systems. We don't just use tools—we build them. You'll have complete ownership of the infrastructure that fuels our ML algorithms from conception to deployment, designing and orchestrating distributed compute systems that process massive datasets at scales few engineers ever encounter. Working shoulder-to-shoulder with AIML researchers and engineers in a small, agile team, you'll drive the creation of scalable infrastructure for ground truth data delivery, orchestrate massive distributed compute tasks across petabyte-scale datasets, develop novel validation frameworks, and help define strategic data collection approaches that push the boundaries of what's achievable. Your contributions won't just support algorithms—they'll directly shape product direction, unlock entirely new AI/ML capabilities, and define what's possible at Apple.
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning Infrastructure and Data Engineer @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs