> Markdown version of [/jobs/ext/3289031-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3289031-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Apple Inc. - **Location:** Santa Clara, CA, United States - **Experience:** Experienced - **Salary:** $142,300.0 - **Contract:** Permanent contract - **Skills:** Apple Products, Artificial Neural Networks, C++ (Programming Language), Cyber Security, Computer Programming, Continuous Integration, Information Retrieval, Python (Programming Language), Machine Learning, Tensorflow, Systems Integration, Pytorch, Large Language Models, Siri, Scikit Learn, Information Technology, Optimization Algorithms, HuggingFace, Machine Learning Operations - **Published:** September 1, 2026 - **Apply:** https://www.themuse.com/jobs/apple/machine-learning-engineer-search-knowledge-quality-bcf081 ## About the Role Ph.D. in a related field. Experience with state-of-the-art ML methodologies, including LLM fine-tuning, neural network optimization , RL Strong communication and accountability skills; a hard-working, strong work ethic, and collaboration abilities. Experimental rigor when training/evaluating LLMs for the purpose of benchmarking LLM optimization algorithms. Minimum Qualifications BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field. 3+ years of industry related experience, working in collaborate environments, Experience with programming skills in Python,C/C++, GoLand Experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, AXLearn and Scikit-learn. Familiarity with integrating ML solutions into production systems and existing workflows at scale; experience with CI/CD workflows and ML pipelines . Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences. Strong problem-solving skills and ability to work independently as well as in a team environment. ## Description The Search and Knowledge Quality team is redefining how hundreds of millions of users interact with their devices to access information. We are an Applied Machine Learning team pushing the boundaries of artificial intelligence-from query understanding and information retrieval to response ranking and contextual answer generation. Our team drives innovation by conducting research, building end-to-end solutions, and deploying them at scale to deliver meaningful customer impact across Apple products. In this role, you will leverage and advance state-of-the-art LLM and ML techniques to better understand user queries and intent, improve document ranking, and generate high-quality answers. You will have end-to-end ownership of features within the Siri Search system, from ideation through production deployment. You will collaborate with industry-leading experts and cross-functional teams across multiple geographies, tackling complex challenges at scale., In this role, you will leverage and advance state-of-the-art LLM and ML techniques to better understand user queries and intent, improve document ranking, and generate high-quality answers. You will have end-to-end ownership of features within the Siri Search system, from ideation through production deployment. You will collaborate with industry-leading experts and cross-functional teams across multiple geographies, tackling complex challenges at scale., Design, develop, and implement machine learning models and RAG based agentic solution for NLP, and multimodal applications. Integrate and own ML solutions into production systems and existing workflows at scale. Collaborate with data scientists, software & ML engineers as well as product managers to define requirements and deliverables Independently own deliverables and apply problem-solving skills to identify solutions to problems to take ownership of complex, ambiguous problems and drive cross-functional solutions with minimal guidance. ## Related Videos - [Adding knowledge to open-source LLMs](https://www.wearedevelopers.com/videos/1522-adding-knowledge-to-open-source-llms) - [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) - [Lessons from Steve Jobs - Learnings from the Past for the Future](https://www.wearedevelopers.com/videos/1021-lessons-from-steve-jobs-learnings-from-the-past-for-the-future) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Data Privacy in LLMs: Challenges and Best Practices](https://www.wearedevelopers.com/videos/1218-data-privacy-in-llms-challenges-and-best-practices) ## 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) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)