Databricks AI Engineer

Role & responsibilities

• Programming & Query Languages: Proficient in Python and SQL for data analysis, modeling, and database management.
• Machine Learning & AI Models: Experience with regression, decision trees, SVM, deep learning (CNNs, RNNs, Transformers), and advanced AI (GNNs, RL, GANs, LLMs such as GPT-4, Claude, LLaMA).
• Natural Language & Vision AI: Strong in NLP (NER, sentiment analysis, summarization) and computer vision (YOLO, ResNet, segmentation, OCR).
• Frameworks & Libraries: Hands-on with TensorFlow, PyTorch, Scikit-learn, Keras, Hugging Face Transformers, Spark MLlib.
• Databricks Ecosystem: Expertise in Databricks Notebooks, MLflow, AutoML, Delta Lake, Unity Catalog, Feature Store, Model Serving, and Lakehouse AI.

Preferred candidate profile

• Design and implement scalable AI/ML solutions using Databricks, MLflow, Delta Lake, and Lakehouse AI.
• Develop and deploy machine learning models (classical ML, deep learning, and generative AI) for business applications.
• Collaborate with data scientists and engineers to prepare, clean, and manage large datasets for analysis and modeling.
• Implement NLP and Computer Vision solutions using frameworks like Hugging Face, YOLO, and ResNet.
• Manage model lifecycle including experimentation, versioning, deployment, and monitoring in Databricks.
• Ensure data governance and compliance using Unity Catalog and Feature Store.