Machine Learning Engineer
Apple
- Cupertino, California, United States
- Cupertino, California, United States
Über
We are now looking for an extraordinary Machine Learning Research Engineer/Scientist to join our team and develop innovative AIML solutions. We are in early days of what we have set out to do, so you have the opportunity to influence our journey and deliver significant, step function changes along the way. We're looking for someone whose "people skills" complement their technical skills, someone who loves improving things as much as building things, and someone who is passionate about discovering new ways to accelerate the rate at which we can improve our products. If this sounds like you, join our team
Description
In this role, you will
- Engage in research and development to advance state-of-the-art AIML technology and adopt them to power and improve Apple's use-cases.
- Develop time-series foundation models that can be leveraged for forecasting, infrastructure capacity planning, anomaly detection, and other such usecases.
- Take end-to-end ownership of data pipelines and ML models from research stage all the way to scaling and production. Write production grade code that is robust, reusable, testable and maintainable, and engage in code review with peers.
- Collaborate with broader teams across Apple and influence engineering design decisions that ensure high quality of features and technologies shipped. Provide technical leadership to junior members of the team.
Minimum Qualifications
Masters or PhD in Computer Science and Engineering, Machine Learning, Operations Research, or equivalent academic and/or professional experience.
5+ years of hands-on industry experience and a proven track record of shipping ML-powered products or features. Extensive experience with the ML development loop, with expertise in model architectures, data curation, training policies and evaluation.
Proficiency in Python, SQL, PyTorch (and/or one of the deep learning frameworks such as JAX, TensorFlow).
Strong system design skills, coupled with a proven understanding of data structures and algorithms.
Deep understanding of fundamental concepts in statistics, optimization, time series modeling, classical machine learning, and deep learning.
Excellent communication (strong interpersonal, verbal and written skills), and ability to partner effectively with engineering, research, and product stakeholders.
Preferred Qualifications
Experience with developing multi-modal foundation models.
Experience with developing AI agents capable of complex reasoning, planning and tool use in diverse environments.
Experience with deploying production grade distributed data processing (e.g. PySpark) and ML pipelines, and developing large-scale ML infrastructure, such as services, frameworks or tooling.
Sprachkenntnisse
- English
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