JobsEmbedded Machine Learning Engineer, Wireless Technologies & Ecosystems
Embedded Machine Learning Engineer, Wireless Technologies & Ecosystems
AppleEmbedded Machine Learning Engineer, Wireless Technologies & Ecosystems
AppleLocation
Seattle, WA
Type
Full-time
Posted
5/8/2026
Compensation
Not listed
Undergraduate with 2+ Years of Experience
Master's with 2+ Years of Experience
Approval 98.9%·Filings 5,543·New hires 2,691·
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·FY 2025Job description
Join Apple's iOS Robotics team within Wireless Technologies and Ecosystems to innovate at the intersection of AI and embedded hardware. As an Embedded Machine Learning Engineer, you will focus on deploying efficient, low-power ML models onto embedded hardware for robotics applications. This role involves transforming advanced ML algorithms into optimized code for custom silicon and microcontrollers. You will tackle challenges related to memory constraints and real-time performance while adhering to Apple's privacy and power efficiency standards.
Requirements
- Bachelor's degree with 3+ years of experience or Master's degree with 2+ years of experience in Computer Science, Electrical Engineering, or a related technical field.
- Proficiency in C/C++ for embedded systems development, including RTOS, microcontrollers, and low-level hardware interactions.
- Proven ability to optimize and deploy ML models for resource-constrained edge devices using techniques like quantization and pruning.
- Experience with ML inference hardware acceleration such as DSPs, NPUs, or ASICs.
- Familiarity with diverse neural network architectures and training methodologies for efficient edge deployment.
- Knowledge of computer vision, NLP, or audio processing in an embedded or robotics context.
- Experience with embedded Linux or other RTOS in a production environment.
- Contributions to open-source embedded ML projects or relevant publications.
- Proficiency with Python for automation and data analysis.
Responsibilities
- Deploy efficient, low-power ML models directly onto embedded hardware.
- Transform advanced ML algorithms into highly optimized, power-efficient code.
- Address complex challenges related to memory constraints and computational budgets.
- Ensure ML models deliver exceptional user experiences while adhering to privacy and power efficiency standards.
- Collaborate with cross-functional teams to enhance the DockKit Framework.
Benefits
- Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.
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