AIML - Machine Learning Engineer - Semi-supervised learning

Key Skills

Aartificial intelligence, Analytical and Problem solving, Debugging, Deep Learning, Design, Effective communication skills, JAX framework, Large scale data processing, Machine learning techniques, Python Programming, PyTorch, TensorFlow

Job Description

Apple is seeking highly qualified candidate for Siri Data Centric ML team. We work on making Siri a ubiquitous voice assistant available across variety of devices and languages spoken around the world, in a privacy aware way. We focus on self-supervised, semi-supervised and active learning to implement our innovation. As a member of the team, you will work on some of the most ambitious technical problems, develop new machine learning solutions that will impact future Apple products, and collaborate with the best teams to integrate your ideas into products.

Key Qualifications

• In-depth expertise in scalable machine learning technologies
• Expertise in one or more of automatic speech recognition, semi-supervised learning or active learning
• Familiarity with large-scale data processing and distributed systems like Spark
• Outstanding written and verbal communication, with the ability to work well in multi-functional teams
• Excellent programming skills in Python
• Knowledge of common deep learning frameworks like Tensorflow, PyTorch, JAX

Description

You will research and develop innovative ML strategies for data effective and privacy aware training of next generation ASR models. You will collaborate with researchers to develop advanced machine learning (ML) technologies and agile model building processes which are easier to scale using the best automation practices. This position requires passion for improving the ML training and evaluation infrastructure for improved research efficiency, and faster modeling iterations. You must have a make this happen demeanor and willingness to also work hands-on in building tools, testing, data collection, running experiments as well as work with innovative machine learning techniques.

Education & Experience

• MS or Ph.D in Computer Science, Artificial Intelligence, Machine Learning or related field.