AI Engineer US shift

Company Description TriNexa is a technology consulting and engineering company focused on transforming ideas into intelligent, production-ready solutions using AI, data engineering, and next-generation technologies. The team designs and builds scalable digital platforms that help businesses compete and grow in a rapidly evolving digital landscape. Core service areas include AI solutions, data engineering, cloud engineering, web and mobile development, DevOps and automation, and data analytics and business intelligence.

TriNexa emphasizes practical innovation, partnering with clients to enable data-driven decision-making and long-term digital transformation. Role Description This is a full-time, remote AI Engineer role on the US shift. The AI Engineer will design, build, and deploy AI models and pipelines, focusing on real-world business use cases across different industries.

Daily responsibilities include researching and prototyping machine learning and deep learning solutions, implementing and optimizing models (including neural networks and NLP systems), and integrating these models into production software environments. The role involves collaborating with cross-functional teams such as product, data engineering, and software development to define requirements, evaluate performance, and improve reliability and scalability of AI systems. The AI Engineer will also contribute to code reviews, documentation, model monitoring, and continuous improvement of the AI engineering toolkit and best practices.

Qualifications Strong foundation in Computer Science and Software Development, including algorithms, data structures, version control, and production-grade coding practices. Hands-on experience with Neural Networks and Pattern Recognition, including training, tuning, and deploying deep learning models for classification, prediction, or recommendation tasks. Practical expertise in Natural Language Processing (NLP), such as text classification, information extraction, embeddings, and working with modern NLP frameworks or large language models.

Proficiency with common AI/ML tools and frameworks (e.g., Python, PyTorch or TensorFlow, scikit-learn, Docker, cloud platforms such as AWS, GCP, or Azure). Bachelor’s or higher degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience. Experience building and deploying models into production environments, including working with APIs, microservices, and CI/CD pipelines.

Strong analytical and problem-solving skills, with the ability to translate business requirements into robust AI solutions. Effective written and verbal communication skills, and the ability to collaborate with distributed, cross-functional teams across time zones. Familiarity with MLOps practices, monitoring and observability for models, and responsible AI considerations (fairness, bias, and explainability) is a plus.