AIML - Machine Learning Engineer, MIND at Apple

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Jun, 26

Salary

0.0

Posted On

12 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, Machine Learning, Deep Learning, Computer Vision, Model Training, Inference Optimizations, Data Pipelines, Prototyping, Error Analysis, Object Detection, Facial Recognition, Temporal Machine Learning, HW/SW Co-design

Industry

Computers and Electronics Manufacturing

Description

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will have an opportunity to be part of an ML innovation organization within Apple that has its roots in the computer vision research community. The team is well positioned for strategic contributions in the short-term (on well-known Apple products) and in the long-term (on highly ambitious, high-risk, high-reward projects). This role has a strong focus on shipping ML-based features and products. You'll innovate in the entire end-to-end ML production pipeline. This includes but is not limited to; crafting creative approaches to datasets, model training, and on-device inference optimizations. Our ideal team member is fearless when it comes to trying new things and is willing to iterate on ideas. We value team members who can quickly prototype, iterating all the way to high-quality implementations. DESCRIPTION As a member of this team, you will use your background to: - Develop features and models to improve the capabilities of systems that use machine learning - Scale up model training, build data pipelines, and tuning to improve system performance - Review and implement pioneering machine learning algorithms - Build software that improves rate of experimentation MINIMUM QUALIFICATIONS Proficient in Python and deep learning frameworks like PyTorch. Experience with training ML models including deep learning based models. Able to define metrics, evaluate ML models, and perform error analysis. Familiar with recent advances in deep learning. Bachelor's, Master's, or PhD or equivalent experience in Computer Science or a related field. PREFERRED QUALIFICATIONS Experience with modeling vision problems in the areas of object detection, facial recognition, and/or temporal machine learning. Experience with building efficient ML models through HW/SW co-design. Experience crafting and defining datasets and metrics for novel tasks. Experience with shipping ML features and products. Excellent problem-solving and analytical skills with a thorough approach. Most importantly: a strong curiosity, willingness to dive deep into unfamiliar problems, and an eagerness to learn and grow in a fast-evolving field.

Responsibilities

The role involves developing machine learning features and models, scaling up model training, building data pipelines, and tuning systems for improved performance. Responsibilities also include reviewing and implementing pioneering ML algorithms and building software to enhance the rate of experimentation.