Software Engineer, Applied ML

Apple • Cupertino, CA

12h

About The Position

Apple’s location technologies team develops intelligent systems that understand location context and personalize user experiences, including suggested locations in Maps, Journaling Suggestions for outings and trips, and curated Memories in Photos. The team is seeking a seasoned engineer to help define the direction of this work and improve the intelligence, performance, and impact of its software.

The engineer will drive feature development and strategy as part of a team of software engineers and researchers identifying behavioral patterns. The role involves collaborating with teams across sensing, Siri, and apps, and partnering with engineering, product, and research leadership to create a multi-year technical roadmap, translate ambiguous product goals into technical strategy, and make architectural and investment trade-offs.

The role will design, build, and evaluate production machine-learning systems that infer device patterns from data such as GPS, Wi-Fi, and accelerometers, as well as higher-level semantic signals, using a combination of estimation techniques and machine learning. The engineer will test and refine systems, monitor metrics, iterate on quality, identify new opportunities for location intelligence across Apple products, and mentor engineers.

Requirements

• Experience building and shipping production software, including technical leadership of multi-engineer projects.
• Experience shipping production software for mobile and/or other resource-constrained devices.
• Ability to create, analyze, and modify software functionality, ideally in C++, Objective-C, or Swift codebases.
• Skill working with large, noisy datasets and experience with libraries such as NumPy, pandas, scikit-learn, and PyTorch or TensorFlow.
• Hands-on experience with applied probability, statistics, and empirical and/or machine-learning algorithms; relevant areas include classical estimation, signal processing, and training supervised machine-learning models.
• Bachelor’s or graduate degree in Computer Science, Computer Engineering, Mathematics, or a related field.

Nice To Haves

• Track record of setting technical strategy and roadmaps for machine-learning-driven product features and influencing decisions across organizations without direct authority.
• Strong grasp of supervised and unsupervised learning, regression, classification, clustering, and model evaluation techniques.
• Experience as a machine-learning practitioner in an industrial setting.
• Experience mentoring and developing engineers and building alignment among technical and non-technical stakeholders.
• Focus on customer impact and product experience.
• Professional background in location and/or wireless sensing technologies, such as GPS/GNSS, Wi-Fi, indoor localization, and/or discrete localization.
• Excellent verbal and written communication skills, including the ability to present strategy and technical trade-offs clearly to senior leadership.
• Ability to succeed collaboratively and operate amid uncertainty.
• Ability to innovate within tight memory, CPU, and schedule constraints and deliver on time.

Responsibilities

• Drive the direction of feature development and strategy for location technologies.
• Collaborate with software engineers and researchers to identify behavioral patterns and shape new and enhanced user experiences.
• Work closely with teams across sensing, Siri, and apps.
• Partner with engineering, product, and research leadership to set a multi-year technical roadmap.
• Translate ambiguous product goals into clear technical strategy and make related architectural and investment trade-offs.
• Design, build, and evaluate production machine-learning systems that infer device patterns from GPS, Wi-Fi, accelerometer, and semantic data using estimation techniques and machine learning.
• Test and refine systems, track metrics, and iterate to improve quality.
• Identify opportunities for location intelligence across Apple products.
• Mentor engineers and help raise the technical bar for the team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior