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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer, Proactive - **Company:** Apple Inc. - **Location:** Cupertino, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Python (Programming Language), Machine Learning, Recommender Systems, Elearning, Tensorflow, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Model Validation, Question Answering, Information Technology - **Published:** July 11, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3316927706&tx=IT878TYI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field * 10 years of work experience in machine learning, deep learning or related field * Experience in modeling user behavior including personalization, online learning and recommendation systems * Experience working with machine 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, * PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. * At least 2 years 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 * At least 10 years of experience leading complex cross-functional projects and influencing research direction * At least 10 years of experience with large-scale model training, optimization, and deployment * Consistent track record of researching, inventing and/or shipping advanced machine learning models * Outstanding communication and interpersonal skills with ability to work with cross-functional teams ## 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. This role will have the following responsibilities: - Conduct research and development on state-of-the-art deep learning and large language models for various tasks and applications in Apple's AI-powered products - Developing, fine-tuning, and evaluating domain-specific Large Language Models for various NLP tasks including summarization, question answering, search relevance/ranking, entity linking and query understanding problems - Conducting applied research to transfer the cutting edge research in generative AI to production ready technologies - Understanding product requirements, translate them into modeling tasks and engineering tasks - Stay up to date with the latest advancements and research in deep learning and large language models ## Related Videos - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Adding knowledge to open-source LLMs](https://www.wearedevelopers.com/videos/1522-adding-knowledge-to-open-source-llms) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [The Prompt Engineer ✍️](https://www.wearedevelopers.com/magazine/216-the-prompt-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Prompt Engineering is a Job of the Past](https://www.wearedevelopers.com/magazine/342-prompt-engineering-is-a-job-of-the-past)