Machine Learning Researcher (ML Research)

Quick Facts

• Role: AIML - ML Researcher (Foundation Models)

• Focus: Deep learning research across the training lifecycle for frontier foundation models optimized for Apple silicon

Description

You will work on foundation model research and development, spanning pre-training and mid-training approaches that bridge general capability and task-specific performance. The work targets frontier challenges in reward modeling (resisting reward hacking), handling sparse/delayed rewards in agentic settings, and aligning models reliably from open-ended creative tasks to precise action-taking workflows. Projects include end-to-end voice interactions, natural language processing, and combining learning with knowledge.

Responsibilities

• Conduct deep learning research on foundation models across end-to-end training stages (pre-training and mid-training)

• Develop approaches for reward modeling, reinforcement learning challenges, and reliable model alignment

• Work on model capabilities for voice and natural language tasks, including integrating learning with knowledge

Requirements

• Demonstrated expertise in deep learning with a publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, COLM, ACL, NAACL, EMNLP, CVPR, ICCV, ECCV, KDD, ICASSP, InterSpeech) or a track record applying deep learning to products

• Proficient programming skills in Python and one deep learning toolkit (JAX, PyTorch, or TensorFlow)

• Ability to work collaboratively in a team environment

• PhD (or equivalent practical experience) in Computer Science or a related technical field

Benefits

Work with a close-knit, fast-growing team of world-class engineers and scientists on fundamental, product-relevant deep learning problems.