Senior ML Infrastructure Engineer Training Algorithms, SIML

Are you passionate about Generative AI Are you interested in working on groundbreaking generative modeling technologies to enrich billions of people We are the Intelligence System Experience (ISE) team within Apples software organization. The team operates at the intersection of multimodal machine learning and system experiences. Our multidisciplinary ML teams focus on a broad spectrum of areas including Visual Generative Foundation Models Multimodal Understanding Visual Understanding of People Text Handwriting and Scenes Personalization Knowledge Extraction Conversation Analysis Behavioral Modeling for Proactive Suggestions and Privacy-Preserving Learning. These innovations form the foundation of the seamless intelligent experiences our users enjoy every are seeking engineers experienced in building infrastructure for training adapting and deploying large-scale generative this role you will be working with closely with a cross functional team of algorithm design and infrastructure engineers to benchmark prototype and steer algorithmic choices to best fit our training u0026 deployment infrastructure.

In this role you will be technically hands on with deep subject matter expertise in ML infrastructure. nnResponsibilities Include: n- Training optimizations u0026 profiling targeting vision/language pre-trainingnn- Researching training recipes for effective scheduling of multimodal training workloadsnn- Experimentation u0026 tooling for post-training ablations including reward modeling distillation and prompt optimizationnn- Coordinating with post-training algorithm owners for analyzing quality / performance tradeoffs of downstream capabilitiesnn- Ablations involving optimization aware fine-tuning

Bachelors Masters or PhD in Electrical Engineering/Computer Science or a related field (mathematics physics or computer engineering) with a focus on machine learning; or comparable professional experiencennExperienced in training / adapting LLM and Diffusion modelsnnAdvanced Fluency in PyTorch nnExcellent programming skills and experience contributing software to large projectsnnExperience with distributed training of large models

Strong ML FundamentalsnExperience working with large cross-functional and diverse teams.