Senior ML Engineer — Search & Knowledge Platforms

Apple Inc.; Seattle (WA); On-site; USD 185,000 - 325,000; Full time

Job summary

Apple Inc. is seeking a Staff/Senior Machine Learning Engineer to advance the search and knowledge platforms powering Apple Intelligence, Siri, Safari, and iMessage. You will develop ML systems, robust heuristics, and prompt engineering across a broad tech stack.

You will contribute to product-driven ML design, experiment validation, and cross-functional collaboration, shaping high-impact features at scale.

Qualifications

• Bachelor’s in Computer Science, AI, ML or related field.
• 6+ years shipping Search and ML systems.
• Strong programming skills in Python, Go or similar languages.
• Experience building scalable data pipelines and backend systems.
• Proficiency in data science methodologies and evaluation metrics.
• Experience with prompt engineering.
• Strong product sense translating requirements into tasks.
• Excellent communication backed by data analysis.

Responsibilities

• Identify opportunities to improve search and ranking quality and performance.
• Apply product sense to design engineering solutions aligned with vision.
• Develop scalable ways to measure and compare impact of solutions.
• Leverage data science, ML design, pipelines, and QA for evaluation.
• Navigate new codebases and architectures effectively.
• Communicate findings clearly to cross-functional teams and leadership.
• Adapt approaches between ML modeling, software engineering, and prompt engineering.

Skills

Python

Go

Software design

Data structures

Algorithms

A/B testing

Prompt engineering

Communication skills

Product sense

Education

Bachelor’s degree in CS/AI/ML

Master’s/Ph.D in CS/AI/ML

Tools

NLP libraries

LLM deployment

RAG architectures

Job description

Apple Inc. is seeking a Staff/Senior Machine Learning Engineer to advance the search and knowledge platforms powering Apple Intelligence, Siri, Safari, and iMessage. You will develop ML systems, robust heuristics, and prompt engineering across a broad tech stack.

You will contribute to product-driven ML design, experiment validation, and cross-functional collaboration, shaping high-impact features at scale.