On-Device ML Engineering Manager (ML Authoring & Conversion Tools)
Apple
On-Device ML Engineering Manager (ML Authoring & Conversion Tools)
Job Description
This is a fantastic opportunity to join the Machine Learning team at Apple, in a leadership role. The On-Device Machine Learning team at Apple enables the Research to Production lifecycle of innovative machine learning models that power magical user experiences on Apple’s hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that field, collaborating with research, SW engineering, HW engineering, and products. This team builds critical infrastructure, beginning with onboarding the latest machine learning architectures to embedded devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to implement these models as efficiently as possible, and the benchmarking, analysis, and debugging toolchain needed to improve on new model iterations. This infrastructure underpins most of Apple’s critical machine learning workflows across many of our products, including Camera, Siri, Health, Vision, and is a significant part of Apple Intelligence. We are seeking an Engineering Manager to oversee the team which builds the Authoring and Conversion toolchain. This is one of the key functional areas in our platform, responsible for developing the foundational authoring and conversion APIs that enable the authoring and import of ML models into Apple’s ML deployment platform. The team works with foundational and applied machine learning researchers and engineers to onboard the newest architectures. More specifically, the team owns the Python authoring toolchain and APIs, the MLIR front-end compiler and intermediate representations, and the integration with ML research frameworks. As the manager in this role, you will support a dynamic team of engineers, with skills that range from machine learning and frameworks like PyTorch and MLX, to deep compiler expertise in MLIR and LLVM. You will partner with other leaders across the organization and company to both develop our platform as well as support clients internally and externally. The role requires a deep technical understanding of ML research→production workflows, ML compilations, runtimes, and on-device optimization techniques (such as quantization, distillation, etc.).
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
- Machine Learningintermediate
- Research to Production lifecycleintermediate
- On-Device Machine Learningintermediate
- Software Engineeringintermediate
- Hardware Engineeringintermediate
- Machine Learning Architecturesintermediate
- Optimization Toolkitsintermediate
- Machine Learning Compilersintermediate
- Machine Learning Runtimesintermediate
- Benchmarkingintermediate
- Analysisintermediate
- Debuggingintermediate
- Authoring and Conversion Toolchainintermediate
- Authoring APIsintermediate
- Conversion APIsintermediate
- ML Model Importintermediate
- Python Authoring Toolchainintermediate
- MLIR Front-end Compilerintermediate
- Intermediate Representationsintermediate
- Integration with ML Research Frameworksintermediate
- PyTorchintermediate
- MLXintermediate
- Compiler Expertiseintermediate
- MLIRintermediate
- LLVMintermediate
- ML Research to Production Workflowsintermediate
- ML Compilationsintermediate
- ML Runtimesintermediate
- On-Device Optimization Techniquesintermediate
- Quantizationintermediate
- Distillationintermediate
- Engineering Managementintermediate
- Team Leadershipintermediate
Required Qualifications
- BS/MS/PhD in Computer Science or Electrical Engineering. (degree in computer science or electrical engineering)
- Two or more years of strong and validated management experience. (experience)
- Knowledge of ML development and workflows, including at least one authoring framework experience (e.g., PyTorch). (experience)
- Excellent social skills. (experience)
- Track record of creating clean software architectures, intuitive designs, and high-performance extensible software. (experience)
- Solid programming skills in Python, C++ or Swift. (experience)
Preferred Qualifications
- Familiarity with Apple framework and API design patterns (experience)
- Experience with on-device ML frameworks (Core ML, Win ML, ONNX, TF Lite or ExecuTorch) (experience)
- Experience with MLIR / LLVM compiler technologies (experience)
Responsibilities
- As the manager in this role, you will support a dynamic team of engineers, with skills that range from machine learning and frameworks like PyTorch and MLX, to deep compiler expertise in MLIR and LLVM. You will partner with other leaders across the organization and company to both develop our platform as well as support clients internally and externally. The role requires a deep technical understanding of ML research→production workflows, ML compilations, runtimes, and on-device optimization techniques (such as quantization, distillation, etc.).
- Lead the team building the authoring/conversion technologies to quickly onboard new ML models to our ML platform, including contributions to internal and external ML authoring frameworks, like MLX and PyTorch.
- Attracting, hiring, and guiding the career of ML and software engineers.
- Partnering with multi-functional partners to push the state-of-the-art of on-device ML functionality and performance.
- Planning and implementing multi-year roadmaps for both internal architectures and public facing functionality.
- Engaging with and supporting 1st and 3rd party developers ML powered use cases.
- Understand different ML operations, architectures, and graph representations in different authoring frameworks and stay on top of the latest innovations in this space.
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Answer 10 quick questions to check your fit for On-Device ML Engineering Manager (ML Authoring & Conversion Tools) @ Apple.
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On-Device ML Engineering Manager (ML Authoring & Conversion Tools)
Apple
On-Device ML Engineering Manager (ML Authoring & Conversion Tools)
Job Description
This is a fantastic opportunity to join the Machine Learning team at Apple, in a leadership role. The On-Device Machine Learning team at Apple enables the Research to Production lifecycle of innovative machine learning models that power magical user experiences on Apple’s hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that field, collaborating with research, SW engineering, HW engineering, and products. This team builds critical infrastructure, beginning with onboarding the latest machine learning architectures to embedded devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to implement these models as efficiently as possible, and the benchmarking, analysis, and debugging toolchain needed to improve on new model iterations. This infrastructure underpins most of Apple’s critical machine learning workflows across many of our products, including Camera, Siri, Health, Vision, and is a significant part of Apple Intelligence. We are seeking an Engineering Manager to oversee the team which builds the Authoring and Conversion toolchain. This is one of the key functional areas in our platform, responsible for developing the foundational authoring and conversion APIs that enable the authoring and import of ML models into Apple’s ML deployment platform. The team works with foundational and applied machine learning researchers and engineers to onboard the newest architectures. More specifically, the team owns the Python authoring toolchain and APIs, the MLIR front-end compiler and intermediate representations, and the integration with ML research frameworks. As the manager in this role, you will support a dynamic team of engineers, with skills that range from machine learning and frameworks like PyTorch and MLX, to deep compiler expertise in MLIR and LLVM. You will partner with other leaders across the organization and company to both develop our platform as well as support clients internally and externally. The role requires a deep technical understanding of ML research→production workflows, ML compilations, runtimes, and on-device optimization techniques (such as quantization, distillation, etc.).
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
- Machine Learningintermediate
- Research to Production lifecycleintermediate
- On-Device Machine Learningintermediate
- Software Engineeringintermediate
- Hardware Engineeringintermediate
- Machine Learning Architecturesintermediate
- Optimization Toolkitsintermediate
- Machine Learning Compilersintermediate
- Machine Learning Runtimesintermediate
- Benchmarkingintermediate
- Analysisintermediate
- Debuggingintermediate
- Authoring and Conversion Toolchainintermediate
- Authoring APIsintermediate
- Conversion APIsintermediate
- ML Model Importintermediate
- Python Authoring Toolchainintermediate
- MLIR Front-end Compilerintermediate
- Intermediate Representationsintermediate
- Integration with ML Research Frameworksintermediate
- PyTorchintermediate
- MLXintermediate
- Compiler Expertiseintermediate
- MLIRintermediate
- LLVMintermediate
- ML Research to Production Workflowsintermediate
- ML Compilationsintermediate
- ML Runtimesintermediate
- On-Device Optimization Techniquesintermediate
- Quantizationintermediate
- Distillationintermediate
- Engineering Managementintermediate
- Team Leadershipintermediate
Required Qualifications
- BS/MS/PhD in Computer Science or Electrical Engineering. (degree in computer science or electrical engineering)
- Two or more years of strong and validated management experience. (experience)
- Knowledge of ML development and workflows, including at least one authoring framework experience (e.g., PyTorch). (experience)
- Excellent social skills. (experience)
- Track record of creating clean software architectures, intuitive designs, and high-performance extensible software. (experience)
- Solid programming skills in Python, C++ or Swift. (experience)
Preferred Qualifications
- Familiarity with Apple framework and API design patterns (experience)
- Experience with on-device ML frameworks (Core ML, Win ML, ONNX, TF Lite or ExecuTorch) (experience)
- Experience with MLIR / LLVM compiler technologies (experience)
Responsibilities
- As the manager in this role, you will support a dynamic team of engineers, with skills that range from machine learning and frameworks like PyTorch and MLX, to deep compiler expertise in MLIR and LLVM. You will partner with other leaders across the organization and company to both develop our platform as well as support clients internally and externally. The role requires a deep technical understanding of ML research→production workflows, ML compilations, runtimes, and on-device optimization techniques (such as quantization, distillation, etc.).
- Lead the team building the authoring/conversion technologies to quickly onboard new ML models to our ML platform, including contributions to internal and external ML authoring frameworks, like MLX and PyTorch.
- Attracting, hiring, and guiding the career of ML and software engineers.
- Partnering with multi-functional partners to push the state-of-the-art of on-device ML functionality and performance.
- Planning and implementing multi-year roadmaps for both internal architectures and public facing functionality.
- Engaging with and supporting 1st and 3rd party developers ML powered use cases.
- Understand different ML operations, architectures, and graph representations in different authoring frameworks and stay on top of the latest innovations in this space.
Tags & Categories
Answer 10 quick questions to check your fit for On-Device ML Engineering Manager (ML Authoring & Conversion Tools) @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs