Artificial Intelligence Engineer

Company Description

Digal Solutions is a pioneering company specializing in tech-driven security, surveillance, and manpower solutions with over 15 years of experience. The company offers cutting-edge technology solutions, including AI-enabled drone surveillance, IoT device development, and industrial automation for critical industrial and infrastructure projects. They are trusted by prominent organizations across sectors such as infrastructure, energy, manufacturing, and government institutions. Combining advanced R&D in drones, IoT, and AI with expertise in field services, Digal Solutions delivers innovative, scalable solutions for safer and smarter industrial environments.

Role Description

This is a full-time on-site role as an Artificial Intelligence Engineer, based in Bhubaneswar. The role involves the application of AI technologies, including designing, developing, and optimizing models with a focus on neural networks, pattern recognition, and NLP. The engineer will also work closely with development teams to integrate AI algorithms into software applications and contribute to the advancement of AI-driven solutions for surveillance, IoT, and industrial automation. Regular collaboration with cross-functional teams to understand technical requirements and deploy systems will be a critical part of the role.

Qualifications

• Proficiency in designing and implementing Pattern Recognition and Neural Networks to develop intelligent systems.
• Strong grounding in Computer Science and Software Development principles with experience in coding and debugging.
• Expertise in Natural Language Processing (NLP) methodologies and related AI technologies.
• Problem-solving skills and ability to work on cross-functional engineering projects.
• Knowledge of AI applications for industrial sectors, such as surveillance and automation, is an advantage.
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related fields.
• Familiarity with frameworks such as TensorFlow, PyTorch, or similar libraries.