ML Engineer / Architect / Data Scientist — Biometric Algorithms

At Apple, we work every single day to craft products that enrich people’s lives. We are seeking a highly motivated and skilled ML Engineer / Architect / Data Scientist to join our Biometric Algorithms team. In this role, you will be responsible for developing innovative algorithms for embedded biometric sensors and leveraging machine learning to enhance their performance and security.

Description

You will join a team that owns core algorithms driving Touch ID experience for users all around the globe. You will work closely with HW teams, contribute to the advancement of our biometric technologies and play a key role in productizing these algorithms for real-world applications.

Minimum Qualifications

Strong foundation in mathematical modeling principles. Proven experience in machine learning and deep learning techniques. Solid understanding of statistical analysis methods. High proficiency in Python: ability to design and build data/ML infrastructure. Ability to independently learn, explore and experiment, cut through ambiguity and work with uncertainty, innovate down to the details. Excellent written and verbal communication skills. English proficiency.

Preferred Qualifications

MSc in Mathematics / Statistics and 3+ years of relevant industry experience. Ability to apply traditional image processing techniques. Sound understanding of Physics and Computer Science. Apple is an Equal Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities. Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants.

Responsibilities

Translate problems into tractable mathematical models with appropriate parametrization. Act as a solution architect. Prototype and innovate biometric algorithms, applying machine learning and deep learning to improve upon existing solutions using our vast biometric data. Conduct robust statistical analysis to evaluate and project biometric performance across our diverse user base and hardware platforms. Design or help building appropriate and efficient data/compute infrastructure to facilitate all of the above. Collaborate with other team members on the productization of your algorithms, ensuring seamless integration into embedded systems. Stay up-to-date with the latest advancements in machine learning, deep learning and biometric technologies. Document research findings, algorithm design and its results clearly and concisely.