Apple
On-device ML Infrastructure Engineer (ML Performance Insights)
Apple, Seattle, Washington, us, 98127
On-device ML Infrastructure Engineer (ML Performance Insights)
Seattle, Washington, United States Software and Services Description
This role provides a great opportunity to help scale and extend an on-device ML benchmarking service that is used across Apple, in support of a range of devices from small wearables up to the largest Apple Silicon Macs.In this role, you will be an integral member of a talented team that is building the first end-to-end developer experience for ML development that, by taking advantage of Apples vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. The role further offers a learning platform to dig into the latest research about on-device machine learning, an exciting ML frontier! Possible example areas include model visualization, efficient inference algorithms, model compression, on-device fine-tuning, federated learning and/or ML compilers/run-time. Responsibilities
Provide deep insights of on-device ML model performance, as well as explore optimizations where appropriate. Drive new capabilities for ML benchmarking service. Play a key role in maintaining the health and performance of the service, including debugging failures and addressing user questions / requests. Collaborate extensively with ML and hardware teams across Apple. Minimum Qualifications
Strong ML fundamentals across training, evaluation and inference, and knowledge of modern model architectures such as Transformers, CNNs or Stable Diffusion; Programming and software design skills (proficiency in Python and/or C/C++); A passion for edge / on-device ML; Understanding about performance modeling, analysis and profiling of computer systems, and how to optimize code run time and throughput for a given platform; Collaboration, product-focus and excellent interpersonal skills. Preferred Qualifications
Masters or PhDs in Computer Science or relevant disciplines; On-device ML frameworks such as CoreML, TFLite or ExecuTorch; Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.) is a strong plus; Experience in software architecture, APIs, high performance extensible software and scalable software systems; Understanding of how to optimize code run time and throughput for a given platform; Interest and experience in power and/or hardware accelerators is a plus; Back-end system skills including containers (docker), cloud orchestration (Kubernetes), database (SQL, Postgres). At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apples discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apples Employee Stock Purchase Plan. Youll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . #J-18808-Ljbffr
Seattle, Washington, United States Software and Services Description
This role provides a great opportunity to help scale and extend an on-device ML benchmarking service that is used across Apple, in support of a range of devices from small wearables up to the largest Apple Silicon Macs.In this role, you will be an integral member of a talented team that is building the first end-to-end developer experience for ML development that, by taking advantage of Apples vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. The role further offers a learning platform to dig into the latest research about on-device machine learning, an exciting ML frontier! Possible example areas include model visualization, efficient inference algorithms, model compression, on-device fine-tuning, federated learning and/or ML compilers/run-time. Responsibilities
Provide deep insights of on-device ML model performance, as well as explore optimizations where appropriate. Drive new capabilities for ML benchmarking service. Play a key role in maintaining the health and performance of the service, including debugging failures and addressing user questions / requests. Collaborate extensively with ML and hardware teams across Apple. Minimum Qualifications
Strong ML fundamentals across training, evaluation and inference, and knowledge of modern model architectures such as Transformers, CNNs or Stable Diffusion; Programming and software design skills (proficiency in Python and/or C/C++); A passion for edge / on-device ML; Understanding about performance modeling, analysis and profiling of computer systems, and how to optimize code run time and throughput for a given platform; Collaboration, product-focus and excellent interpersonal skills. Preferred Qualifications
Masters or PhDs in Computer Science or relevant disciplines; On-device ML frameworks such as CoreML, TFLite or ExecuTorch; Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.) is a strong plus; Experience in software architecture, APIs, high performance extensible software and scalable software systems; Understanding of how to optimize code run time and throughput for a given platform; Interest and experience in power and/or hardware accelerators is a plus; Back-end system skills including containers (docker), cloud orchestration (Kubernetes), database (SQL, Postgres). At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apples discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apples Employee Stock Purchase Plan. Youll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . #J-18808-Ljbffr