Staff Data Science Engineer, Siri Runtime Systems and Interaction

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.

Do you want to make Siri and Apple products more intelligent for our users? The Siri Attention and Invocation team is the front door to Siri. We make sure all our Apple costumers can invoke Siri how and when they want to.

Description

As part of Siri Attention and Invocation team, we collaborate to deliver the next revolution in human-computer interaction, to inspire and create groundbreaking technology for large scale systems, spoken language, big data, and artificial intelligence, to overcome real-world challenges through innovation and user-centered systems that focus on improving the daily life of millions of our customers.

We are seeking an exceptional Staff Data Science Engineer to join our team and drive strategic data science initiatives across the organization.

Minimum Qualifications

Education: MS or PhD in Computer Science, Statistics, Mathematics, or related field (or equivalent experience)

Experience: 5+ years in data science, machine learning, or related fields

Technical Skills:

Expert proficiency in Python and/or R

Deep understanding of machine learning algorithms and statistical methods

Strong SQL skills and experience with big data technologies (Spark, Hadoop, etc.)

Leadership: Proven track record of leading technical projects and mentoring teams

Communication: Excellent ability to explain complex technical concepts to non-technical stakeholders

Preferred Qualifications

Proficiency with cloud platforms (AWS, Google Cloud Platform, or Azure)

Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)

Familiar with workflow orchestrators like Airflow or Kubeflow

Experience deploying models to production environments