Artificial Intelligence Engineer

Company Description DataObserve is a technology company focused on building data-driven products and solutions that help organizations make better decisions. The team works with modern analytics, machine learning, and automation technologies to transform complex data into actionable insights. DataObserve values collaboration, innovation, and practical problem-solving in a fast-paced environment. Team members are encouraged to experiment, learn continuously, and contribute ideas that directly impact products and customers.Role Description The Artificial Intelligence Engineer will design, develop, and deploy AI models and systems that support DataObserve’s data-driven solutions. Day-to-day responsibilities include building and training machine learning and deep learning models, implementing pattern recognition and NLP algorithms, and integrating AI components into production-grade software. The role involves collaborating with data scientists, software engineers, and product teams to define requirements, evaluate model performance, and optimize solutions for scalability and reliability. The engineer will also document technical designs, maintain existing AI pipelines, and stay current with emerging AI frameworks and tools. This is a full-time, on-site role based in Sugar Land, TX.Qualifications Strong foundation in Computer Science and Software Development, including data structures, algorithms, and version control.Experience with Pattern Recognition and Neural Networks, including model training, evaluation, and optimization.Practical skills in Natural Language Processing (NLP), such as text preprocessing, language models, and classification or generation tasks.Proficiency in programming languages commonly used in AI (e.g., Python), and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).Ability to work with large datasets, build reproducible experiments, and develop AI solutions that can be deployed in production environments.Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.Strong problem-solving skills, attention to detail, and the ability to collaborate effectively with multidisciplinary teams on-site.