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 Apples 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 Apples customers and enrich their lives. You are an ideal candidate if you:Are not afraid of CUDA OOM or NCCL errorsCan dig deep into an ML library to understand how tiny details impact the modelCan understand complex ML systems that include data training pipeline export and inference engine
- Experience in model lifecycle of training evaluation and deployment of models
- Strong understanding of Machine Learning (ML) model architectures (e.g. Transformers CNN) and ML training loop
- Strong proficiency in Python and ML framework such as PyTorch
- Bachelors degree in Computer Science Engineering or related discipline or equivalent industry/project experience
- Collaborative with experience working in large inter-teams projects
- Expertise in ML and LLM optimization such as quantization KV Cache Speculative Decoding
- Familiarity with ML training methodologies such as FSDP DDP and other parallelism
- Experience in an LLM training/eval library such as HuggingFace transformers lm evaluation harness Megatron-LM.
- Experience in optimizing LLM models and deploying LLM models
- Proficiency in a compiled programming language (e.g. Swift C/C Java)
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 Apples cus...
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 Apples 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 Apples customers and enrich their lives. You are an ideal candidate if you:Are not afraid of CUDA OOM or NCCL errorsCan dig deep into an ML library to understand how tiny details impact the modelCan understand complex ML systems that include data training pipeline export and inference engine
- Experience in model lifecycle of training evaluation and deployment of models
- Strong understanding of Machine Learning (ML) model architectures (e.g. Transformers CNN) and ML training loop
- Strong proficiency in Python and ML framework such as PyTorch
- Bachelors degree in Computer Science Engineering or related discipline or equivalent industry/project experience
- Collaborative with experience working in large inter-teams projects
- Expertise in ML and LLM optimization such as quantization KV Cache Speculative Decoding
- Familiarity with ML training methodologies such as FSDP DDP and other parallelism
- Experience in an LLM training/eval library such as HuggingFace transformers lm evaluation harness Megatron-LM.
- Experience in optimizing LLM models and deploying LLM models
- Proficiency in a compiled programming language (e.g. Swift C/C Java)
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