Description
Research Engineer - III
Location: Noida, India
Department: AI
Experience: 4-7
About Us - Attentive.ai is transforming the field services and construction industries with our flagship AI solution - Beam AI. Our platform empowers businesses to double their bidding capacity and accelerate growth through automation and intelligent insights.
More than 900 businesses across the U.S. and Canada already use our products to boost sales velocity and streamline operations. Backed by Peak XV (Surge), InfoEdge, Insight Partners, Tenacity and Vertex Ventures, we’re on a mission to make advanced AI tools accessible, practical, and impactful in the real world.
Position Description:
As a Research Engineer-III, you will be an integral part of our 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.
In this role, you will support the end-to-end lifecycle of AI-based solutions — from prototyping and experimentation to deployment in production. Your contributions will directly impact the scalability, accuracy, and efficiency of our products.
Roles & Responsibilities
- 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.
Skills & Requirements
- 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.
- Bachelor’s degree in CSE, AI/ML, Data Science & Engineering, MnC, or EE from a Tier-1 engineering institute preferred.
- Prior Experience working with large datasets and models.
- Solid understanding of image processing, visual document understanding, and feature extraction from 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.
Why Work With Us?
- Be part of a visionary team building a first-of-its-kind AI solution for the construction industry.
- Exposure to real-world AI deployment and cutting-edge research in vision and multimodal learning.
- Culture that encourages ownership, innovation, and growth.
- Opportunities for fast learning, mentorship, and career progression.
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