Job description

As a Senior Machine Learning Engineer on our team, you will be responsible for the definition, design, and quality of increasingly sophisticated AI features that ship to a global audience. You will drive the development of workflows that facilitate efficient data synthesis, data curation, prompt engineering, and model evaluation. Finally, you will contribute to a company-wide effort to build robust modeling processes that optimize our ability to iterate rapidly and continuously deliver improvements to our customers. Key responsibilities: * Own the model quality of shipping and unreleased Apple Intelligence features * Prioritize and drive modeling efforts across multiple fronts * Analyze user feedback to understand shortcomings of our models and evaluation data * Define robust evaluation mechanisms to drive data curation, metric calibration, and model hill-climbing * Research state-of-the-art SFT/PEFT/RLHF/distillation techniques for improving model quality and robustness * Implement pipelines, experiments, and simulations to assess the value of modeling changes MS or PhD in Computer Science or related field, or equivalent practical experience History of shipping AI features built on language models Experience building and maintaining model pipelines end-to-end, from data curation/synthesis and LLM judges to post-training Strong Python programming skills, with experience developing production-quality Python modules Excellent written and verbal communication skills History of driving cross-functional collaborations and leading technical efforts Expertise deploying models on-device, reasoning about latency, activation size, quantization, and distillation Background in linguistics, fluency in multiple languages, or experience scaling NLP features for global audiences

Requirements

Must-haves

Own the model quality of shipping and unreleased Apple Intelligence features
Prioritize and drive modeling efforts across multiple fronts
Analyze user feedback to understand shortcomings of our models and evaluation data
Define robust evaluation mechanisms to drive data curation, metric calibration, and model hill-climbing
Research state-of-the-art SFT/PEFT/RLHF/distillation techniques for improving model quality and robustness
Implement pipelines, experiments, and simulations to assess the value of modeling changes
MS or PhD in Computer Science or related field, or equivalent practical experience
History of shipping AI features built on language models
Experience building and maintaining model pipelines end-to-end, from data curation/synthesis and LLM judges to post-training
Strong Python programming skills, with experience developing production-quality Python modules
Excellent written and verbal communication skills
History of driving cross-functional collaborations and leading technical efforts
Expertise deploying models on-device, reasoning about latency, activation size, quantization, and distillation
Background in linguistics, fluency in multiple languages, or experience scaling NLP features for global audiences

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaillmpython

Platform: apple
Effort: medium