Apple

Designs phones, computers and their operating systems

Engineering Program Manager - Machine Learning Features

Program ManagementPosted on Nov 9

Full-timeHerzliya, IsraelNo salary listedIn-person

About the Job

Requirements

A B.Sc. in Computer Science, Electrical Engineering, or a related STEM field is required.
At least 8 years of relevant experience, including significant engineering program management experience in software or machine learning development, is required.
Hands-on background as a machine learning engineer, researcher, or data scientist is required.
Software experience working with data teams to define data strategy and plans for machine learning programs, with a clear understanding of how data drives model quality, is required.
A solid understanding of the machine learning lifecycle and the technical depth to engage credibly with researchers and engineers is required.
Experience with hardware new-product-introduction cycles, including prototype builds and pre-silicon validation, is required.
Experience using artificial intelligence tools in daily work to improve productivity is required.
The ability to summarize complex status for executive audiences is required.
Experience leading through influence in a matrixed, multinational environment is required.

Responsibilities

Own the delivery plan for machine learning features from research and prototyping through integration, validation, and release.
Partner with data teams to build a data strategy and plan that covers model data needs and program milestones, including data type, scale, coverage, and timing.
Align model milestones with hardware builds, pre-silicon validation using simulation and FPGA, and silicon bring-up, ensuring models are ready at each gate.
Lead integration with software groups, including model handoff, interfaces, integration schedules, and release timing.
Align machine learning teams, MLOps, and data science on priorities, compute capacity, and dependencies.
Track model quality, latency, memory, and power against product targets, and lead trade-off decisions.
Set up model release practices, including readiness gates, versioning, regression tracking, and post-integration monitoring.
Summarize machine learning progress as clear, data-driven recommendations for leadership.

Desired Qualifications

An M.Sc. or Ph.D. in a related field is preferred.
Experience with speech, audio, or computer vision machine learning, such as automatic speech recognition, voice isolation, or video restoration, is preferred.
Familiarity with large-scale data collection and annotation practices, including privacy considerations, is preferred.
Experience with on-device machine learning and optimization for dedicated hardware or neural engines is preferred.
Familiarity with MLOps practices, including data pipelines, distributed GPU training, and continuous integration and continuous delivery for models, is preferred.
Experience with platform software release processes and working with US-based teams is preferred.

Summary

Play a part in shaping the future of human-computer interaction. We're looking for an Engineering Program Manager (EPM) to turn advanced machine learning in speech, audio and computer vision into features that ship to customers. You'll work across ML research, data collection, silicon, FW, and the device and companion SW teams that bring these features to Apple customers.Your work will cover every stage, from the first dataset to the final release.

Minimum Qualifications

B.Sc. in Computer Science, Electrical Engineering, or a related STEM field 8+ years of relevant experience, including significant engineering program management experience in SW or ML development Hands-on background as an ML engineer, researcher or data scientist SW Experience working with data teams to define data strategy and plans for ML programs, with a clear understanding of how data drives model quality Solid understanding of the ML lifecycle, with the technical depth to engage credibly with researchers and engineers Experience with HW NPI cycles (prototype builds, pre-silicon validation) Using AI tools in daily work to improve productivity Excellent communication skills, including summarizing complex status for executive audiences Experience leading through influence in a matrixed, multinational environment

Preferred Qualifications

M.Sc. or Ph.D. in a related field Experience with speech, audio or computer vision ML (e.g., ASR, voice isolation, video restoration) Familiarity with large-scale data collection and annotation practices, including privacy considerations Experience with on-device ML and optimization for dedicated HW or neural engines Familiarity with MLOps practices: data pipelines, distributed GPU training, CI/CD for models Experience with platform SW release processes and working with US-based teams Comfortable with ambiguity, using AI tools in daily work, and calm under pressure

Description

You'll own the plan for taking ML features from research to release. That covers data planning, model training and evaluation, optimization for Apple silicon, integration with SW teams, and release. You'll keep teams aligned, make risk visible early, and help leadership decide when model quality, performance and schedule pull in different directions. You'll be comfortable with how uncertain research is, and disciplined about delivering what ships.

Responsibilities

Own the delivery plan for ML features, from research and prototyping through integration, validation and release Partner with data teams to build the data strategy and plan, making sure it covers what the models need and supports program milestones: what data, at what scale and coverage, and by when Align model milestones with HW builds, pre-silicon validation (simulation and FPGA), and silicon bring-up, ensuring models are ready at each gate Lead integration with SW groups, including model handoff, interfaces, integration schedules and release timing Align ML teams, MLOps and data science on priorities, compute capacity and dependencies Track model quality, latency, memory and power against product targets, and lead trade-off decisions Set up model release practices: readiness gates, versioning, regression tracking and post-integration monitoring Summarize ML progress into clear, data-driven recommendations for leadership.

About the Company

Apple

Designs phones, computers and their operating systems

Apple designs and sells consumer electronics, from iPhone smartphones and Mac computers to tablets and wearable devices. Its operating systems manage apps and built-in functions for communication and work, while iCloud stores files and synchronizes data across devices. Customers buy additional digital services through subscriptions such as Apple Music and Apple TV, and developers distribute software through the App Store. Apple earns money from hardware sales, subscriptions and digital transactions, selling directly to customers and through retailers and mobile carriers around the world. It was founded in 1976 and has its headquarters in Cupertino, California.

Company size: 10,001+
Company stage: IPO
Headquarters: Cupertino, CA
Founded: 1976

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