Job description

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for highly motivated machine learning engineers and researchers having strong machine learning and deep learning fundamentals with hands-on experience in fine-tuning deep learning and large language models. 2+ years of experience working with Deep learning or LLM model development for various NLP tasks and RAG applications including prompt engineering, training data collection and generation, model fine-tuning and model evaluation. Experience working with Python and at least one of the deep learning frameworks such as TensorFlow, PyTorch, or JAX. Master’s in Computer Science, Artificial Intelligence, Machine Learning, or a related field. PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 4+ years of experience with large-scale model training, optimization, and deployment One or more scientific publications in various conferences and journals Outstanding communication and interpersonal skills with ability to work with cross-functional teams. 1+ year of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more of the following areas: Supervised Fine-tuning (SFT) with Rejection Sampling Preference-based fine-tuning techniques (e.g RLHF, Reward model, DPO, PPO, GRPO etc.) Parameter efficient fine-tuning techniques (e.g LoRA) Hallucination reduction and factual accuracy improvements Designing and implementing safety guardrails

Requirements

Must-haves

Experience working with Python and at least one of the deep learning frameworks such as TensorFlow, PyTorch, or JAX.
Master’s in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
4+ years of experience with large-scale model training, optimization, and deployment
One or more scientific publications in various conferences and journals
Outstanding communication and interpersonal skills with ability to work with cross-functional teams.
1+ year of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more of the following areas:
Supervised Fine-tuning (SFT) with Rejection Sampling
Preference-based fine-tuning techniques (e.g RLHF, Reward model, DPO, PPO, GRPO etc.)
Parameter efficient fine-tuning techniques (e.g LoRA)
Hallucination reduction and factual accuracy improvements
Designing and implementing safety guardrails

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningllmpython

Platform: apple
Effort: medium