Company Description

Nitid AI specializes in leveraging Explainable AI to solve complex technological problems and optimize industrial processes with a focus on sustainability. Our AI-driven solutions aim to enhance operational efficiency and contribute to a greener future by making decisions transparent, actionable, and impactful.

Collaborations and Ecosystem

Nitid AI thrives at the intersection of global innovation and local expertise. With strong ties to the AI and entrepreneurial ecosystem at MIT in Boston, we remain at the forefront of the latest advancements in artificial intelligence.

In addition to our international collaborations, we are deeply embedded in the Basque Country's technological landscape. Our headquarters are located in the iconic Bizkaia Accelerator Tower (BAT) in Bilbao, complemented by our state-of-the-art AI Lab at the University of Deusto. These strategic locations provide us with unparalleled access to the vibrant network of Basque tech companies, fostering innovation and collaboration to drive impactful AI solutions.

Role Description

This is a full-time on-site role for a Deep Learning Engineer at Nitid AI, located in the heart of the vibrant city of Bilbao, along the stunning Bay of Biscay on the northern coast of Spain.

The Deep Learning Engineer will be responsible for developing and implementing cutting-edge deep learning algorithms, designing and training neural networks, optimizing models for performance, building efficient preprocessing pipelines, crafting robust coding and algorithm design strategies, and collaborating with cross-functional teams to integrate AI solutions into various complex projects.

Qualifications

• Deep learning, neural network design, and model optimization skills
• Proficiency in machine learning frameworks like TensorFlow, PyTorch, or Keras
• Strong programming skills in Python
• Advanced knowledge of mathematics, statistics, and algorithms
• Ability to work collaboratively in a team environment
• Excellent problem-solving and analytical abilities
• Master's or Ph.D. in Computer Science, Engineering, or related field