AI Engineer

Company Description Altivum® Inc. is a veteran-founded technology firm focused on building intelligent, cloud-native architectures with AI integrated at the core of operations. The company’s mission is to engineer artificial intelligence systems that help people and organizations adapt, excel, and make better data-driven decisions. Altivum® emphasizes robust, scalable solutions that seamlessly embed AI into real-world workflows. Team members collaborate closely with clients to design systems that are both technically advanced and practical to deploy. Joining Altivum® offers opportunities to work on impactful AI initiatives in a mission-driven environment. Role Description The AI Engineer will design, build, and maintain AI-driven systems and services that support Altivum®’s cloud-native architectures. Day-to-day responsibilities include developing and training machine learning models, implementing neural network architectures, and optimizing algorithms for performance and scalability. The role involves collaborating with cross-functional teams to integrate AI components into production software, conducting experiments, evaluating model effectiveness, and iterating based on data and feedback. The AI Engineer will also contribute to technical documentation, code reviews, and best practices for model deployment and monitoring. This is a full-time, on-site role located in the Greater Clarksville Area. Qualifications Strong foundation in computer science and software development, including data structures, algorithms. Experience with machine learning and pattern recognition, including model design, training, evaluation, and optimization. Practical knowledge of neural networks and deep learning frameworks (e.g., TensorFlow, PyTorch, Keras) for building and deploying AI models. Hands-on experience with Natural Language Processing (NLP), such as text classification, entity recognition, and language modeling. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) for AI deployment. Ability to work collaboratively in an on-site environment, communicate complex technical concepts clearly, and document solutions effectively. Experience with MLOps practices, version control (e.g., Git), and monitoring tools is beneficial. Show more Show less