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Apple Machine Learning Engineer India, Telangana, Hyderabad 351990118
31.03.2025
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. There are massive opportunities for you deliver impactful influences to Apple.
- A Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a closely related field.
- 3+ years of machine learning engineering experience in feature engineering, ML model development & training, model serving, model monitoring and model refresh management.
- Experience with SQL and NoSQL databases.
- Experience developing AI/ML systems at scale in production or in high-impact research environments.
- Strong proficiency in Python and experience with relevant libraries (e.g., scikit-learn, pandas, NumPy).
- Experience with at least one deep learning framework (e.g., TensorFlow, PyTorch).
- Solid understanding of data structures, data modeling, and software architecture principles.
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Good understanding of statistical analysis and data analysis techniques.
- Intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques and their performance characteristics.
- Excellent communication and collaboration skills.
- Strong analytical and problem-solving skills.
- Master's degree Computer Science, Engineering, Mathematics, Statistics, or a closely related field.
- Experience with big data technologies (e.g., Spark, Hadoop) and Cloud platforms (e.g., AWS, Azure, GCP) and their ML services.
- Experience with containerisation technologies (e.g., Docker, Kubernetes).
- Experience with building and deploying machine learning models in production environments at scale.
- Experience in Anomaly detection and forecasting & related methodologies.
- Proven experience with transformer models such as BERT, GPT etc., and a proven understanding of their underlying principles is a plus.
- Proficient in data visualization, with experience in software such as Superset, Streamlit, Tableau, Business Objects, and Looker.
- Development experience with autonomous agents, reinforcement learning, or other agent-based modeling techniques. Experience with building and deploying agentic systems in real-world applications.
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