Machine Learning Scientist Apple Services Engineering, GenAI & ML Frameworks
San Francisco, CA - USA
Job Summary
We are seeking a strong candidate who can operate end-to-end across model development and production integrationsomeone equally strong in (1) LLM training (domain-adaptive continual pretraining post-training preference optimization / RL such as GRPO-style methods) (2) agentic systems (tool schemas multi-turn reliability rubric- or verifier-based learning loops) and (3) deployment-aware optimization (latency/cost/reliability tradeoffs evaluation harnesses and iterative improvement from production signals). nnThe ideal candidate has a track record of turning LLM research into shipped capabilities can partner effectively with product infra and foundation model teams and can lead ambiguous cross-LOB initiatives from problem definition through execution and scaling. Experience building robust tooling around synthetic data generation eval and training pipelines for LLMs is strongly preferred since this role is expected to raise the bar on both research velocity and production readiness.
BS/MS in a quantitative field including Computer Science Maths Statistics Physics programming skills in PythonnHands-on experience working with deep learning toolkits such as Jax Tensorflow or PyTorchnProven track record in training or deployment of large models or building large-scale distributed systemsnDeep understanding of Deep Learning and Large Language Models (LLMs)nNatural Language Processing
PhD in a quantitative field including Computer Science Maths Statistics Physics etc.
Required Experience:
IC
About Company
Ask Siri to name the most successful company in the world and it might respond: Apple. And it's not just out of familial pride. Apple consistently ranks highly in profit, revenue, market capitalization, and consumer cachet. In 2018, the company became the first reach a trillion dollar ... View more