Job Description

Locations

• Cupertino, California, United States 95014

Salary

Skills Required

• Machine Learning Systems Engineeringintermediate
• generative AI technologyintermediate
• model trainingintermediate
• model evaluationintermediate
• generative AI researchintermediate
• model optimizationintermediate
• model inferenceintermediate
• Apple Siliconintermediate
• production-level codingintermediate
• model deploymentintermediate
• CUDA troubleshootingintermediate
• NCCL troubleshootingintermediate
• ML library analysisintermediate
• ML systems understandingintermediate
• data managementintermediate
• training pipelineintermediate
• model exportintermediate
• inference engineintermediate

Required Qualifications

• Experience in model lifecycle of training, evaluation, and deployment of models (experience)
• Strong understanding of Machine Learning (ML) model architectures (e.g. Transformers, CNN) and ML training loop (experience)
• Strong proficiency in Python and ML framework such as PyTorch (experience)
• Bachelor's degree in Computer Science, Engineering, or related discipline, or equivalent industry/project experience (experience)

Preferred Qualifications

• Collaborative with experience working in large inter-teams projects (experience)
• Expertise in ML and LLM optimization such as quantization, KV Cache, Speculative Decoding (experience)
• Familiarity with ML training methodologies such as FSDP, DDP, and other parallelism (experience)
• Experience in an LLM training/eval library such as HuggingFace transformers, lm evaluation harness, Megatron-LM. (experience)
• Experience in optimizing LLM models and deploying LLM models (experience)
• Proficiency in a compiled programming language (e.g. Swift, C/C++, Java) (experience)

Responsibilities

• As a Machine Learning Systems Engineer, you will work closely with Siri modeling teams and other cross-functional teams to optimize model training and inference. You will be working across the ML stack at Apple, finding opportunities to make models performant, train quicker, and run faster on Apple's custom Apple Silicon. You will be joining a team that spans data, modeling, evaluation, deployment and working with engineers across ML infrastructure, inference, and framework teams. You will write production-level code to train and deploy models that will impact Apple's customers and enrich their lives. You are an ideal candidate if you:
• <li>Are not afraid of CUDA OOM or NCCL errors
• <li>Can dig deep into an ML library to understand how tiny details impact the model
• <li>Can understand complex ML systems that include data, training pipeline, export, and inference engine

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