AI Engineer

AI Engineer

About the Role

We are transforming the future with cutting-edge artificial intelligence solutions for real-world challenges. As an AI Engineer, you’ll be instrumental in designing, developing, and deploying intelligent algorithms and systems, collaborating with a cross-functional team of data scientists, product managers, and engineers. In this dynamic role, you will work on projects spanning natural language processing, computer vision, machine learning, and deep learning. Your work will directly impact the product roadmap and help Pebble deliver best-in-class AI-powered products and experiences to our global user base. If you are passionate about solving complex problems and innovating with advanced technology, we encourage you to join our mission-driven team.

Responsibilities

• Design, implement, and optimize AI models for a variety of applications.
   
• Collaborate with data scientists, product managers, and engineers on end-to-end project delivery.
   
• Develop robust, scalable, and efficient machine learning pipelines.
   
• Evaluate and improve the performance of AI systems through testing and iteration.
   
• Research and integrate state-of-the-art techniques in deep learning, NLP, and computer vision.
   
• Deploy AI models into production environments using best engineering practices.
   
• Monitor model health and address performance or bias issues as they arise.
   
• Document architectures, algorithms, and workflows clearly and effectively.
   
• Contribute to code reviews to ensure high-quality and maintainable solutions.
   
• Stay updated on AI research, tools, and industry trends, sharing insights with the team.
   

Requirements

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or related field.
   
• 2+ years of experience in machine learning, deep learning, or AI development.
   
• Strong programming proficiency in Python and one or more ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.).
   
• Experience designing and deploying AI or ML models in production environments.
   
• Knowledge of computer vision, natural language processing, and/or reinforcement learning techniques.
   
• Solid understanding of data preprocessing, feature engineering, and model evaluation methodologies.
   
• Ability to work collaboratively in a cross-functional, agile environment.
   
• Strong analytical, problem-solving, and communication skills.
   
• Familiarity with cloud technologies (AWS, GCP, Azure) and containerization (Docker/Kubernetes).
   
• Experience with version control and code development best practices (Git, CI/CD).