Machine Learning Engineer

Key Responsibilities: • Design, develop, and enhance machine learning and AI models to support intelligent troubleshooting and automation. • Implement and optimize Large Language Model (LLM)-based solutions to improve system understanding, predictions, and responses. • Collaborate with data scientists, software engineers, and product teams to integrate AI models into existing systems. • Analyze, preprocess, and transform large datasets to improve model performance and accuracy. • Work with and integrate various APIs to enhance data flow, model functionality, and system interoperability. • Continuously evaluate and improve model accuracy, scalability, and robustness based on feedback and real-world data. • Research and apply emerging ML/AI technologies and frameworks to enhance the current AI model capabilities. Required Skills & Qualifications: • 4–5+ years of professional experience in Machine Learning, AI, or Data Science (flexible based on expertise). • Strong understanding of Large Language Models (LLMs) and their practical applications. • Proficiency in Python and familiarity with ML libraries such as TensorFlow, PyTorch, or scikit-learn. • Experience working with API integrations and automation pipelines. • Familiarity with data preprocessing, feature engineering, and model evaluation techniques. • Strong problem-solving and analytical skills, with an ability to work independently in a fully remote environment. • Excellent communication skills and the ability to collaborate effectively across teams. Preferred Qualifications: • Background in Applied Research (AR) or Language Modeling (LM). • Experience working with troubleshooting or diagnostic systems powered by AI. • Exposure to cloud platforms (AWS, Azure, GCP) and MLOps practices.