Machine Learning Engineer - Applied Science

Apple Inc

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $212,000–$318,400 / yr
Posted: 5 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k

This role $265k

$154k most similar roles pay here $336k

This role pays more than 88% of similar roles. Most pay $184,412–$249,750 — the shaded band above. At the midpoint, this role pays about $265k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1777 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1443 roles with salary data.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Machine Learning Engineer - Applied Science

Apply Now Log in to save

Join the Geo domain team as a senior Machine Learning Engineer where you will leverage innovative ML techniques and large language models to enhance query understanding, document ranking, and answer retrieval for Siri and Spotlight. Your day-to-day involves leading the development of machine learning models to improve search quality across various stages, from prototyping to deployment, while independently identifying high-impact research directions and translating them into practical improvements. You will work closely with product and design teams to shape technical roadmaps and mentor junior engineers in architecting ML systems. Essential skills include deep expertise in information retrieval, natural language processing, and machine learning theory, as well as experience applying advanced techniques at scale. Preferred qualifications include a PhD or significant research contributions, and hands-on experience with LLMs and generative AI in production environments.

Skills

Python TensorFlow PyTorch Kubernetes Docker AWS CI/CD SQL PostgreSQL Elasticsearch Hadoop Spark Scikit-learn NLP Information_Retrieval Learning_to_Rank Embedding_Models Reinforcement_Learning A/B_Testing

What you'll do

Own the ML development cycle from analysis to deployment in production.
Lead the development of models to enhance search quality across retrieval and ranking.
Apply advanced techniques like learning-to-rank, embedding models, and reinforcement learning.
Independently identify high-impact research directions and drive them to production improvements.
Mentor junior engineers and provide technical leadership in ML system architecture.

What we're looking for

8+ years experience in information retrieval, NLP, machine learning, or deep learning.
Deep understanding of ML theory including supervised learning, ranking models, embeddings, and evaluation metrics.
Proven ability to apply advanced ML techniques at scale to improve search relevance and quality.
Comfortable leading experimentation, offline evaluation, and A/B testing for iterative improvements in search quality.
Active monitoring of recent research literature and translating findings into practical system improvements.

Similar roles