Machine Learning Infrastructure Engineer
Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI
Apple is looking for Machine Learning/Deep Learning infrastructure engineers to develop infrastructure for various ML/DL applications. Your work will enable researchers and engineers to build production ML/DL models at scale. Join Apple and help us leave the world better than we found it! WHAT YOU’LL DO - Develop highly scalable and reliable machine learning infrastructure that can perform model training and evaluation on a massive scale. - Build vital tools and infrastructure to monitor and understand the performance of complex systems. - Support the team to deploy models in a mission critical environment.
- Strong background in building scalable and fault-tolerant distributed systems. Ideal candidates have past experience in building applications such as data pipelines, data caching/storage systems, and/or RPC services.
- Strong programming background, with extensive experience in Python. Experience with C++ is a plus.
- Substantial experience with multiple technologies from the following list: Arrow, Bazel, Docker, Kibana, MPI, MySQL, Redis, Spark, Zookeeper.
- Ability to build full-stack web applications/services for internal tooling.
- Previous experience with developing machine learning infrastructure or experience in using GPUs is a plus.
You’ll join a phenomenal team of hardworking engineers and researchers with deep experience in robotics, machine learning, and software engineering. We hope you’re excited about the values that drive us: - Passion for the mission: We’re here to make something great. We take on whatever work is right for the product and strive for the best possible results. - Modesty: The right answer is more important than being right. We search for solutions as a team and value clear-eyed feedback. - Lean habits: You can’t grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make great decisions.
Education & Experience
Bachelors, Masters, or PhD Degree in Computer Science or equivalent professional experience.