AIML - Senior Machine Learning Infrastructure Engineer -ML Compute, ML Platform & Technology

We are the team who build and maintain compute infrastructure to run ML workloads at Apple that include training, inferencing, fine tuning etc.. We are looking for an experienced software engineer who is excited by the opportunity to solve unique, large scale, highly complex technical problems to make ML workloads more stable, more reliable, more efficient and more cost effective. You will collaborate with a wide range of internal teams, listening intently to understand their challenges and true underlying needs. We are looking for candidates who share a passion for tackling complexity and building platforms that can scale through multiple orders of magnitude. Key responsibilities: - Scope, architect, and deliver innovative high-quality solutions - Effectively communicate complex features and systems in detail - Collaborate with teams across Apple on ML workloads such training, inferencing, fine tuning etc. - Understand industry & company-wide trends to help assess & develop new technologies - Code using Go, Python - Conduct code reviews - Help onboard new team members, provide mentorship and enable successful ramp up on your team's code bases Minimum Qualifications Bachelors in Computer Science, engineering, or a related field 4+ years of hands-on experience in building scalable backend systems for training and evaluation of machine learning/deep learning models Proficient in relevant programming languages, like Python or Go Strong expertise in distributed systems, reliability and scalability, containerization, and cloud platforms. Proficient in cloud computing and data processing infrastructure and tools: Kubernetes, Ray, Beam, Flink Ability to clearly and concisely communicate technical and architectural problems, while working with partners to iteratively find solutions Preferred Qualifications Advance degrees in Computer Science, engineering, or a related field Proficient in working with and debugging accelerators, like: GPU, TPU, AWS Trainium Proficient in ML training and deployment frameworks, like: JAX, Tensorflow, PyTorch, TensorRT, vLLM