Posted on: 23/08/2025
Responsibilities :
- Contribute to research and development initiatives focused on Computer Vision, Image Processing, 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 Hugging Face.
- Stay updated with the latest research in computer vision and machine learning, and evaluate applicability to construction industry challenges.
Requirements :
- 5-6+ years of experience in applied AI/ML and research with a strong focus on Computer Vision and Deep Learning.
- Solid understanding of image processing, visual document understanding, and feature extraction from visual data.
- Familiarity with SVG graphics, NLP, or LLM-based architectures 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.
- Prefers folks who have done a Master's in a Tier 1 college or an MS abroad.
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