Apple Services GenAI & ML Frameworks team aims at bridging foundation model capabilities with real-world production systems. The work spans LLM continual pretraining, posttraining, agentic reinforcement learning, agentic system optimization etc.. This role is part of the cross-LOB effort to support various GenAI use cases across ASE, and specializes in improving LLM domain knowledge, tool use, reasoning, and system integration-working closely with product, infra, and foundation model teams to bring cutting-edge models into user-facing features at scale.

Description:

We are seeking a strong candidate who can operate end-to-end across model development and production integration-someone 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).

The 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.

Preferred Qualifications:

PhD in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

Minimum Qualifications:

BS/MS in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

Proficient programming skills in Python

Hands-on experience working with deep learning toolkits such as Jax, Tensorflow or Py Torch

Proven track record in training or deployment of large models or building large-scale distributed systems

Deep understanding of Deep Learning and Large Language Models (LLMs)

Natural Language Processing:

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Pay & Benefits:

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $220,900, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.