Senior Machine Learning Engineer, Apple Cloud AI

Apple is a place where extraordinary people gather to do their best work. Together we build products and experiences people love. The Apple Services Engineering (ASE) organization builds and operates the systems and infrastructure that power Apples services at Apple AI platform within ASE enables teams across Apple to build train optimize and deploy AI systems at scale. Our team builds the optimization and intelligence layer for frontier AI making frontier class of models work better cheaper and faster through managed serverless capabilities that span the full AI lifecycle: data and feature engineering embeddings and retrieval model training and fine-tuning inference optimization and routing prompt optimization evaluation and governance. n

We are looking for an ML engineer who is excited about building managed platform services at the intersection of ML distributed systems and production engineering.n

As a member of the team your responsibilities will include:nnDesign build and optimize large-scale ML platform services used by teams across ApplenBuild the embedding and retrieval path end to end - fine-tuning encoder models encoding corpora at scale building and serving vector indexes and evaluating retrieval quality so improvements are measurable rather than assertednBuild and operate the feature store teams use for training and serving keeping both paths consistent off a single feature definitionnDevelop optimization capabilities that reduce cost and improve quality across ML workloads - including model routing caching serving configuration inference optimization and training efficiencynBuild managed self-service experiences so customers can go from data to production AI with minimal frictionnBuild managed training - supervised fine-tuning reinforcement learning and distillation - so teams can customize models without running their own training infrastructurenBuild governance and compliance capabilities - lineage policy enforcement cost observability and access controlnPartner with customer teams across Apple to understand their ML workloads and deliver production solutionsnOperate production services with on-call responsibilitiesnn

3 years of experience building production ML systems or ML infrastructurenStrong programming skills in Python and/or Rust/JavanUnderstanding of end-to-end machine learning workflows - from data preparation through training evaluation and deploymentnExperience with distributed systems and large-scale data processingnExperience with model serving inference optimization or ML pipeline engineeringnExperience building APIs and services that other engineers consumenStrong collaboration and communication skillsnComfortable navigating ambiguity in fast-moving areasnBS MS or PhD in Computer Science or equivalent practical experience

Experience with LLM inference optimization (batching quantization KV caching tensor parallelism)nExperience with model serving frameworks (vLLM TensorRT Ray Serve or similar)nExperience with embedding models and retrieval systems - fine-tuning encoders on graded or contrastive objectives pooling strategies dimensionality reduction for serving cost vector databases and retrieval evaluation (NDCG recall graded relevance)nExperience with fine-tuning and alignment workflows (SFT DPO LoRA RLHF RLVR GRPO reward modeling)nExperience with feature engineering and feature serving platforms (e.g. Feast Tecton Hopsworks) distributed data processing frameworks (e.g. Spark Flink Ray) offline stores (e.g. Iceberg Delta Lance) and online stores (e.g. Redis Cassandra DynamoDB)nExperience with Ray Kubernetes and cloud GPU infrastructure (AWS GCP)nExperience with ML governance lineage or compliance systems