Foundation Models Engineer: Advanced LLMs & Reasoning

Socket.dev; Cary (NC); On-site; USD 150,000 - 230,000; Full time

Job summary

Apple is seeking researchers and engineers to shape the next generation of LLMs, turning models into intelligent assistants across Apple products. You will tackle post-training challenges, data generation and safety, and work with product teams to translate user requirements into capable model features.

The role emphasizes collaboration, rigorous evaluation, and privacy-forward design as you advance model capabilities in a highly interdisciplinary environment.

Qualifications

• Expertise in deep learning with a focus on LLMs, post-training, or reinforcement learning.
• Proficient programming skills in Python and a major deep learning framework such as JAX or PyTorch.
• Masters/PhD, or equivalent practical experience, in Computer Science, Machine Learning, or a related technical field.

Responsibilities

• Design and iterate on end-to-end post-training strategies (including Reinforcement Learning) to unlock model capacities toward achieving specific model behaviors.
• Pioneer novel algorithms for preference optimization, model steering, and safety.
• Drive our data strategy by researching methods for high-quality human and synthetic data generation, automated data filtering, and curriculum learning to improve instruction following and reasoning.
• Design robust evaluation methodologies to measure model helpfulness, factuality, and utility, moving beyond static benchmarks to accurately capture real-world performance.
• Partner closely with pre-training teams to inform architecture choices, and with product teams to translate user requirements into model capabilities.

Skills

Deep learning (LLMs)

Python

JAX or PyTorch

Education

Masters/PhD in CS/ML or equivalent

Tools

JAX

PyTorch

Job description

Apple is seeking researchers and engineers to shape the next generation of LLMs, turning models into intelligent assistants across Apple products. You will tackle post-training challenges, data generation and safety, and work with product teams to translate user requirements into capable model features.

The role emphasizes collaboration, rigorous evaluation, and privacy-forward design as you advance model capabilities in a highly interdisciplinary environment.