Research Engineer III

As a Research Engineer-III, you will be an integral part of the AI research team focused on transforming the construction industry through cutting-edge deep learning, computer vision and NLP technologies. You will contribute to the development of intelligent systems for automated construction take-off and estimation by working with unstructured data such as blueprint, drawings (including SVGs), and PDF documents. You will support the end-to-end lifecycle of AI-based solutions — from prototyping and experimentation to deployment in production.
What You'll Do
Contribute to research and development initiatives focused on Computer Vision or NLP and Deep Learning applied to construction-related data.
Build and optimize models for extracting insights from documents such as blueprints, scanned PDFs, and SVG files.
Contribute development of multi-modal models that integrate vision with language-based features (NLP/LLMs).
Follow best data science and machine learning practices, including data-centric development, experiment tracking, model validation, and reproducibility.
Collaborate with cross-functional teams including software engineers, ML researchers, and product teams to convert research ideas into real-world applications.
Write clean, scalable, and production-ready code using Python and frameworks like PyTorch, TensorFlow, or HuggingFace.
Stay updated with the latest research in computer vision and machine learning and evaluate applicability to construction industry challenges.
Must have
4-7 years of experience in applied AI/ML and research with a strong focus on Computer Vision or NLP with state of the art Deep Learning. Prior Experience working with large datasets and models. Solid understanding of image processing, visual document understanding, and feature extraction visual data. Solid understanding of transformers, NLP, or LLM based architectures. Familiarity with SVG graphics is a plus. Deep understanding of unsupervised learning techniques like clustering, dimensionality reduction, and representation learning. Proficiency in Python and ML frameworks such as PyTorch, OpenCV, TensorFlow, and HuggingFace Transformers. Hands-on experience with model optimization techniques (e.g., quantization, pruning, knowledge distillation).
Good to have
Experience with version control systems (e.g., Git), project tracking tools (e.g., JIRA), and cloud environments (GCP, AWS, or Azure). Familiarity with Docker, Kubernetes, and containerized ML deployment pipelines. Strong analytical and problem-solving skills with a passion for building innovative solutions; ability to rapidly prototype and iterate. Comfortable working in a fast-paced, agile, startup-like environment with excellent communication and collaboration skills.

Work arrangement
No