AIML - Machine Learning Research

Apple Inc

Confirmed live 3 days ago High trust

Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $142,300–$263,300 / yr
Posted: 46 days ago
Freshness: Confirmed live 3 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $231k

This role $203k

$126k $294k

below market most similar roles pay here above market

This role pays less than 77% of similar roles. Most pay $207,837–$254,750 — the blue band above. At the midpoint, this role pays about $203k versus about $231k 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 3535 open roles on FindRole.

Listed pay typically runs $166,600–$277,600 across 2738 roles with salary data.

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At a glance

TL;DR · AIML - Machine Learning Research

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AIML - Machine Learning Research joins the Applied ML team to enhance features across products like Siri, Spotlight, and Messages. You will conduct large-scale machine learning and deep learning research to improve Open Domain Question Answering and Summarization. Your daily work involves developing sophisticated large language models to understand user queries, retrieve and rank documents, and synthesize information from structured knowledge graphs and unstructured web data. You will design and develop advanced Reinforcement Learning technologies, including RLHF, RLAIF, and Reward Modeling, for the post-training of generative models. Key responsibilities include building RL pipelines, training agents, and managing the end-to-end ML lifecycle. You will utilize your expertise in natural language processing and conversational AI to translate theoretical advances into production-ready technologies for Apple Intelligence.

Skills

Large Language Models (LLMs) RLHF RLAIF SFT Reward Modeling Generative AI Machine Learning Deep Learning Chain-of-thought Agentic AI Model Training Deployment ML Lifecycle

What you'll do

Design and develop advanced Reinforcement Learning technologies for the post-training of generative models.
Develop and fine-tune domain-specific Large Language Models for various Apple Intelligence products.
Improve Open Domain Question Answering using structured knowledge graphs and unstructured web data.
Research and develop state-of-the-art LLMs for summarizing personal data like emails and messages.
Manage the end-to-end ML lifecycle including algorithm design, data collection, training, evaluation, and deployment.
Translate theoretical research advances into deployable, production-ready systems and technologies.
Develop novel RL algorithms and integrate the latest research best practices into the team workflow.

What we're looking for

MS or Ph.D. in Computer Science, Machine Learning with a specialty in reinforcement learning, or a related field.
1+ years of ML experience in search, natural language processing/understanding, and conversational AI.
Proven experience in LLM post-training, including SFT, RLHF, RLAIF, Reward Modeling, Chain-of-thought, and agentic LLM.
Hands-on experience building RL pipelines and training agents in simulation or real-world environments.
Experienced researcher in areas of machine learning, including natural language or speech.
Deep expertise in reinforcement learning-based post-training on LLM models, reward modeling, RLHF, RLAIF, Chain-of-thought, and agentic AI R&D (preferred).
Experienced researcher with publications in areas of machine learning, including natural language processing (preferred).
Deep understanding of cutting edge RL algorithms, large language models, and LLM pre-training/post-training (preferred).