CBTS is Searching for a Sr AI/Sagemaker Developer. This role focuses on leveraging cutting-edge computational techniques, including AI and computer vision, to revolutionize the design, engineering, and manufacturing processes for building façades. We are seeking an independent, innovative, and resourceful Sr AI/Sagemaker Developer to join our team. The Sr AI/Sagemaker Developer would join this team of around 20 people that have backgrounds in design, engineering, programming, and visualization. The team collaborates across specialties to research and develop new products, software, and visualization tools for Clients.

Role Overview:

In this role, you will spearhead the development and deployment of state-of-the-art AI/Sagemaker and computer vision models. You’ll apply these technologies to tasks such as automated design optimization, predictive material performance, supply chain insights, and manufacturing quality assurance. You will work closely with cross-functional teams, including data scientists, material engineers, software developers, and product managers, to integrate advanced AI solutions that drive efficiency and innovation.

Responsibilities :

Model Development & Deployment:

Design, train, and optimize AI/Sagemaker and LLM-based models for diverse applications.

Develop computer vision models for component recognition, defect detection, and automated annotation.

Utilize frameworks like PyTorch or TensorFlow and integrate annotation tools such as CVAT into the training pipeline.

Cloud Architecture & Integration:

Implement scalable ML pipelines and model hosting on AWS using services such as Amazon S3, EC2, SageMaker, Lambda, and ECS/EKS.

Ensure that deployed models meet performance, availability, and cost requirements.

Data Management & Experimentation:

Work with large, heterogeneous datasets—including files, images, drawings, operation manuals, ensuring proper preprocessing and augmentation.

Implement MLOps best practices, including CI/CD pipelines, versioning, monitoring, and automated retraining.

Cross-Functional Collaboration:

Collaborate with team members—engineers, architects, and business stakeholders—to understand project needs and translate them into AI-driven solutions.

Clearly communicate complex AI concepts and results to non-technical stakeholders, providing actionable insights.

Research & Innovation:

Keep pace with the latest advancements in generative AI, LLMs, and computer vision.

Experiment with cutting-edge models and techniques (e.g., diffusion models, transformer-based architectures, self-supervised learning) to enhance capabilities.

Qualifications:

Education & Experience:

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field.

Minimum 5+ years of professional experience in ML/AI, Specifically with Sagemaker

Technical Expertise:

Proven track record in training and deploying advanced deep learning models at scale.

Proficiency in Python and ML frameworks like PyTorch or TensorFlow.

Solid experience with AWS ML services (SageMaker, ECS, Lambda) and MLOps frameworks.