Proactive Intelligence, Applied ML Research Scientist

Key Skills

Algorithms, Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, TensorFlow

Job Description

At Apple, novel research ideas have a way of becoming extraordinary products, services, and customer experiences quickly. Here is your opportunity to be part of an incredible research and engineering team building the next-generation of sophisticated algorithms for the iPhone, Mac, Apple Watch, iPad and more. The vision for the Proactive Intelligence organization is to improve Apple platforms by better understanding, anticipating, and adapting to user behavior by using machine learning to build phenomenal features that are built right into Apple platforms. We are looking for inquisitive and creative applied research scientists with expertise in ML and a particular focus on Natural Language Processing (NLP), Program Synthesis, Sequence Modeling, Privacy-Preserving ML (PPML), and Distributed Machine Learning. Working knowledge of large-scale data processing especially with structured data, probabilistic modeling, statistics and embedded programming will broaden your role and effectiveness in this position.

Key Qualifications

• Strong background in Deep Learning and classical Machine Learning, including one or more of the following areas of expertise: sequence modeling/NLP, program synthesis, generative models, processing structured data such as relational graphs, privacy-preserving machine learning, and distributed algorithms.
• Track record of coming up with new ML ideas, as shown by publications, patents or open-source projects
• Experience with one or more Deep Learning packages including but not limited to TensorFlow and PyTorch
• Proficiency in Python programming
• Background that fuses research, engineering, and product thinking, as demonstrated by practical experience of shipping algorithms for measurement, evaluation, control and processing to improve products.

Description

We're looking for sensible and creative scientists with a strong background in ML. Your passion for leading powerful technologies will be essential to your project and a key component to our team of world-class engineers and designers who are driven to create the next big thing using machine learning. Join us to enhance the lives of hundreds of millions of people around the world! You will contribute to advanced algorithms that transform data and relational graphs into interpretable information that feed into elegant applications that delight, connect, and encourage Apple users all around the world to be more productive. The emphasis will be to work on the edge of creative technologies and highly impactful ML problems that will help improve our users' experience. More specifically, you will: Design and implement ML algorithms that process data in different Apple products. Deploy those algorithms and establish scalable, efficient, automated processes for large-scale data analyses, model development and model validation. Communicate advanced ideas to a focused team. Develop innovative tools and metrics that change the way we look at problems. Join a thriving Machine Learning community at Apple (https://machinelearning.apple.com) Work multi-functionally and with the Proactive Intelligence leadership team, to devise data insights and reporting standard methodologies that guide the development of current and new intelligent experiences across iPhone, iPad, HomePod, Mac, Watch and TV!

Education & Experience

Ph.D. degree in CS (preferred), or other STEM fields such as EE or Statistics with 3 years of proven experience or M.S. in CS with 5 years of demonstrated ability in research and development of machine learning algorithms.

Pay & Benefits

• At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $170,700 and $300,200, and your base pay will depend on your skills, qualifications, experience, and location.