Machine Learning Engineer

As a Machine Learning Engineer, you will work on building intelligent systems to democratize AI across a wide range of solutions within Apple. You will drive the development and deployment of innovative AI models and systems that directly impact the capabilities and performance of Apple s products and services. You will implement robust, scalable ML infrastructure, including data storage, processing, and model serving components, to support seamless integration of AI/ML models into production environments. You will develop novel feature engineering, data augmentation, prompt engineering and fine-tuning frameworks that achieve optimal performance on specific tasks and domains. You will design and implement automated ML pipelines for data preprocessing, feature engineering, model training, hyper-parameter tuning, and model evaluation, enabling rapid experimentation and iteration. You will also implement advanced model compression and optimization techniques to reduce the resource footprint of language models while preserving their performance.Have continuous focus to Brainstorm and Design various POCs using AI/ML Services for new or existing enterprise problems.YOU SHOULD BE ABLE TO:- Understand a business challenge- Collaborate with business and other multi-functional teams- Design a statistical or deep learning solution to find the needed answer to it.- Develop it by yourself or guide another person to do it.- Deliver the outcome into production, (v) Keep a good governance of your work.There are meaningful opportunities for you deliver impactful influences to Apple. 4+ years of ML engineering experience in feature engineering, model training, model serving, model monitoring and model refresh management Experience developing AI/ML systems at scale in production or in high-impact research environments Passionate about computer vision, natural language processing, especially in LLMs and Generative AI systems Knowledge with the common frameworks and tools such as PyPorch or TensorFlow Experience with transformer models such as BERT, GPT etc. and understanding of their underlying principles is a plus Strong coding, analytical, software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment Experience in handling performance, application and security log management Applied knowledge of statistical data analysis, predictive modeling classification, Time Series techniques, sampling methods, multivariate analysis, hypothesis testing, and drift analysis. Proficiency in programming languages and tools like Python, R, Git, Airflow, Notebooks. Experience with data visualization tools like matplotlib, d3.js., Tableau would be a plus Education & Experience Bachelor s Degree or Equivalent experience