Software Engineer, Applied ML

Our team is at the forefront of customer experiences that happen when devices come close to each other. Part of the Location and Motion organization within Apple, we use all available technologies to provide spatially-aware technology to our users in a way that feels seamless and magical. Our algorithms help you find your items and friends, check the battery status of your AirPods, unlock your Mac, and setup your new wireless accessories. We also help your loved ones know you made it home safely and help protect you against unwanted tracking. We are looking for candidates with outstanding coding skills, passion for location technologies, and experience in system design and wireless applications. If this description fits you, please read on., Our team is looking for a highly-motivated engineer with excellent software development, quantitative reasoning, and communication skills. Candidates need to be very familiar with modern object-oriented programming languages such as C++ or Swift, as well as having an understanding of common design patterns, debugging techniques, and performant code. Experience with wireless sensing, probabilistic estimation, statistical reasoning, embedded platforms, the iOS ecosystem and large codebases are welcome backgrounds.

We are a team motivated by shipping software and getting technology in to the hands of our users. Team members need to be familiar with the entire software development lifecycle: taking an idea from concept, to prototype, to production. Great candidates will be comfortable communicating and promoting their ideas, and eager to learn from others.

We have a passion for quality and we regularly focus on the development and improvement of iOS applications and tools for continuous integration, data analysis and visualization. Candidates should be excited about not only building critical pieces of software but also the infrastructure around it. We make a serious commitment to software quality, engineering productivity, and automation. We are out to find an engineer that shares those values., * Machine Learning algorithms: Strong grasp of supervised/unsupervised learning, regression, classification, clustering, and model evaluation techniques.

• Data processing: Skilled in working with large, noisy datasets.
• Experience with libraries like NumPy, pandas, scikit-learn, and PyTorch or TensorFlow.
• Hands-on experience with applied probability, statistics, and empirical and/or ML algorithms. Classical estimation, signal processing, and/or training supervised ML models are relevant.
• Bachelor’s or graduate degree in Computer Science, Computer Engineering, Mathematics, or a related field.

Preferred Qualifications

• Having worked as an ML practitioner in an industrial setting
• Laser focus on customer impact and product experience.
• Deep Learning: Experience with CNNs, RNNs/LSTMs, Transformers, etc. depending on the application domain.
• Some professional background in location and/or other wireless sensing technologies, including for example, GPS/GNSS, WiFi, indoor localization, and/or discrete localization.
• Excellent communication, verbally and in writing. You can succeed in a collaborative environment, and are comfortable with what will sometimes feel like a high degree of uncertainty.
• You can innovate within tight memory, CPU, and schedule constraints, and deliver on time. These constraints motivate you, and ignite your creativity.