Strong knowledge of machine learning algorithms and techniques
Familiarity with data preprocessing and feature engineering
Experience with libraries such as TensorFlow, PyTorch, scikit-learn and XGBoost etc.
Ability to deploy and manage ML models in production
Develop and implement machine learning models, including advanced use of Natural Language Processing (NLP) and Large Language Models (LLMs) for text analysis and conversational AI.
Create end-to-end ML pipelines, ensuring automation of training, deployment, testing, and monitoring.
Collaborate with cross-functional teams to translate business requirements into scalable AI solutions, ensuring compliance with security and privacy standards.
Optimize and fine-tune ML models for performance, scalability, and cost efficiency.
Good-to-Have
Proven success in building conversational AI agents, integrating LLMs, and deploying custom ML models on GCP.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full time