AIML - Machine Learning Research Engineer, Data and Machine Learning Innovation

Apple • Cupertino, CA

6d

About The Position

As a Research Engineer you will play a critical role to advance Apple Foundation
Models to the next level. You will help turn research breakthroughs into
tangible values and deliver state-of-the-art model capabilities to support Apple
Intelligence. You will drive innovations with data intelligence from variety of
sources, combined with applied research in the areas of LLMs, Visual
Understanding, Agentic & Reasoning models, and image & video generation to
delight Apple’s customers

DESCRIPTION

In this role, you will focus on: Modeling: design and build models, feature
engineering that help achieve desired outcome in multiple modalities across
pre-train, mid-train and post-train stages Evaluation: be able to go deep and
perform model & data analysis to hill climb on general as well as specific model
capabilities Optimization: implement scalable data pipelines, optimize models
with data intelligence for performance and efficiency, and ensure they are
production ready Data: be obsessed with data quality, work with large amounts of
data and build effective data processing steps that are proven to drive results
Learn and collaborate: work closely with software engineers, data scientists and
program managers to understand complex user-facing feature challenges. Take part
in to share frontier knowledge in the field and maintain high-quality
engineering practices

Requirements

• Master or PhDs Degree in Computer Science, Machine Learning, Data Science or a related field.
• Demonstrated proficiency in ML frameworks like PyTorch or Tensorflow.
• Proven track record in Deep Learning research or industry.
• Strong foundation in Computer Science and software engineering with excellent problem-solving & analytical skills.
• Demonstrated critical thinking and ability to drive clarity from ambiguity.

Nice To Haves

• In-depth hands-on experience with transformer models and deep reinforcement learning.
• Familiarity with pre-training and fine-tuning multi-modal LLMs.
• Ability to work collaboratively with cross-functional teams as a good communicator with clear and concise, active listening and empathy skills.
• Self-motivated and curious, stay on top of the relevant frontier technologies.
• Have demonstrated creative and critical thinking with an innate drive to improve how things work.
• Have a high tolerance for ambiguity.

Responsibilities

• Modeling: design and build models, feature engineering that help achieve desired outcome in multiple modalities across pre-train, mid-train and post-train stages
• Evaluation: be able to go deep and perform model & data analysis to hill climb on general as well as specific model capabilities
• Optimization: implement scalable data pipelines, optimize models with data intelligence for performance and efficiency, and ensure they are production ready
• Data: be obsessed with data quality, work with large amounts of data and build effective data processing steps that are proven to drive results
• Learn and collaborate: work closely with software engineers, data scientists and program managers to understand complex user-facing feature challenges. Take part in to share frontier knowledge in the field and maintain high-quality engineering practices

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees