Machine Learning Research Engineer, NLP, Input Experience

What you'll do

• Design and implement data, tooling, modeling, and evaluation pipelines using agentic workflows and Apple Foundation Models.
• Develop personalized agent trajectory pipelines for data and evaluation across synthetic personas and languages.
• Collaborate with cross-functional teams to align ML techniques with product goals, privacy requirements, and performance metrics.

What they ask for

• Master’s or PhD in Computer Science, Electrical Engineering, Physics, Statistics, or a related field, or equivalent practical experience.
• Prior experience with technical leadership or engineering management.
• Strong foundation in Data Science and ML Stack; familiarity with the product ML/NLP lifecycle.
• Familiarity with SFT, RLHF, Data Synthesis, Parameter-Efficient Fine-Tuning, and LLM-judge evaluation; excellent communication skills.

Nice to have

• Experience deploying large ML models in real-world products, curating and synthesizing training datasets at scale, or scaling ML pipelines across languages.
• Experience with agentic workflows, tool calling, advanced reasoning, large codebases, or AI-assisted development tools.

Pay

$184,700 and $324,800 (base salary)

Tools

Apple Foundation Models, SFT, RLHF, Data Synthesis, Parameter-Efficient Fine-Tuning, LLM-judge evaluation, Claude, Copilot

AI focus

Develop agentic ML product-development workflows and personalized pipelines for data and evaluation, using foundation models for Apple Intelligence features.