ML Systems Engineering Manager
Apple
ML Systems Engineering Manager
Job Description
Our team is building next generation systems and tools supporting the research and development of machine learning models, and their integration into the products Apple customers love. We're a fast moving, highly skilled team designing and building a collection of tools and systems used by Apple’s MLEs and data scientists to build, test and deploy their products. Our systems have to scale, stay highly available, and "just work”. That's a tall order, and we're looking for a talented and passionate ML Systems Engineering Manager who love dealing with such challenges. Our team designs and builds ML systems and tools that support applied ML teams throughout their product development cycle. Using our systems, MLEs and data scientists perform data acquisition and synthesis, training, evaluation, and serving. In this role, you will be responsible for managing engineers who develop solutions to support model training, such as building reliable and scalable systems to run data processing pipelines, data generation engines, model evaluation infrastructure, and model inference systems. You will be successful and feel fulfilled if you enjoy tackling challenging problems, have a strong sense of shared ownership, and thrive in a collaborative team setting.
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
60,000,000 - 120,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- managing engineersintermediate
- building reliable and scalable systemsintermediate
- data processing pipelinesintermediate
- data generation enginesintermediate
- model evaluation infrastructureintermediate
- model inference systemsintermediate
- tackling challenging problemsintermediate
- strong sense of shared ownershipintermediate
- collaborative team settingintermediate
Required Qualifications
- 5+ years industry experience as a Machine Learning Engineer or Software Engineer working on deploying large-scale systems. (experience, 5 years)
- 2-3 years management experience (experience, 3 years)
- Strong understanding in data centric systems, distributed systems, reliability, and cloud services. (experience)
- Hands-on experience in designing and coding large scale systems. (experience)
- Proven experience with applied machine learning, data engineering, or similar. (experience)
- MS in Computer Science or related experience. (experience)
Preferred Qualifications
- Experience with developer tools or developer productivity systems. (experience)
- Experience with open source or inner source (experience)
Responsibilities
- Our team designs and builds ML systems and tools that support applied ML teams throughout their product development cycle. Using our systems, MLEs and data scientists perform data acquisition and synthesis, training, evaluation, and serving. In this role, you will be responsible for managing engineers who develop solutions to support model training, such as building reliable and scalable systems to run data processing pipelines, data generation engines, model evaluation infrastructure, and model inference systems. You will be successful and feel fulfilled if you enjoy tackling challenging problems, have a strong sense of shared ownership, and thrive in a collaborative team setting.
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ML Systems Engineering Manager
Apple
ML Systems Engineering Manager
Job Description
Our team is building next generation systems and tools supporting the research and development of machine learning models, and their integration into the products Apple customers love. We're a fast moving, highly skilled team designing and building a collection of tools and systems used by Apple’s MLEs and data scientists to build, test and deploy their products. Our systems have to scale, stay highly available, and "just work”. That's a tall order, and we're looking for a talented and passionate ML Systems Engineering Manager who love dealing with such challenges. Our team designs and builds ML systems and tools that support applied ML teams throughout their product development cycle. Using our systems, MLEs and data scientists perform data acquisition and synthesis, training, evaluation, and serving. In this role, you will be responsible for managing engineers who develop solutions to support model training, such as building reliable and scalable systems to run data processing pipelines, data generation engines, model evaluation infrastructure, and model inference systems. You will be successful and feel fulfilled if you enjoy tackling challenging problems, have a strong sense of shared ownership, and thrive in a collaborative team setting.
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
60,000,000 - 120,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- managing engineersintermediate
- building reliable and scalable systemsintermediate
- data processing pipelinesintermediate
- data generation enginesintermediate
- model evaluation infrastructureintermediate
- model inference systemsintermediate
- tackling challenging problemsintermediate
- strong sense of shared ownershipintermediate
- collaborative team settingintermediate
Required Qualifications
- 5+ years industry experience as a Machine Learning Engineer or Software Engineer working on deploying large-scale systems. (experience, 5 years)
- 2-3 years management experience (experience, 3 years)
- Strong understanding in data centric systems, distributed systems, reliability, and cloud services. (experience)
- Hands-on experience in designing and coding large scale systems. (experience)
- Proven experience with applied machine learning, data engineering, or similar. (experience)
- MS in Computer Science or related experience. (experience)
Preferred Qualifications
- Experience with developer tools or developer productivity systems. (experience)
- Experience with open source or inner source (experience)
Responsibilities
- Our team designs and builds ML systems and tools that support applied ML teams throughout their product development cycle. Using our systems, MLEs and data scientists perform data acquisition and synthesis, training, evaluation, and serving. In this role, you will be responsible for managing engineers who develop solutions to support model training, such as building reliable and scalable systems to run data processing pipelines, data generation engines, model evaluation infrastructure, and model inference systems. You will be successful and feel fulfilled if you enjoy tackling challenging problems, have a strong sense of shared ownership, and thrive in a collaborative team setting.
Tags & Categories
Answer 10 quick questions to check your fit for ML Systems Engineering Manager @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs