Research Engineer - II

CodeRound; Hinoba-an; On-site; PHP 600,000 - 1,200,000; Full time

Job summary

CodeRound is hiring a Research Engineer-II to advance AI solutions for automated construction take-off and estimation. You will work with unstructured data from blueprints, PDFs, and SVGs to develop computer vision, NLP, and multimodal models, moving ideas from research to production.

You will collaborate with software engineers and product teams, implement robust ML pipelines, and publish results while applying best practices in data-centric development and model validation in a startup

Qualifications

• Research Engineer-II with focus on Computer Vision, Deep Learning and NLP for construction-related data.
• Ability to work with unstructured data from blueprints, PDFs and SVGs to build AI solutions.
• Contribute across the AI lifecycle from research to production deployment.

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 blueprints, scanned PDFs, and SVG files.
• Contribute development of multi-modal models that integrate vision with language-based features (NLP/LLMs).
• Support the end-to-end lifecycle of AI-based solutions from prototyping and experimentation to deployment in production.
• Follow best data science and machine learning practices, including data-centric development, experiment tracking, model validation, and reproducibility.
• Collaborate with 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 industry challenges.

Skills

AI/ML

Machine Learning

Deep Learning

Computer Vision

Image Processing

NLP

LLM

Multimodal Models

Python

PyTorch

TensorFlow

OpenCV

HuggingFace

Transformers

Representation Learning

Unsupervised Learning

Feature Extraction

Model Optimization

Quantization

Pruning

Knowledge Distillation

Docker

Kubernetes

Cloud

AWS

GCP

Azure

ML Deployment

Production AI

AI Research

Document Intelligence

PDF Processing

SVG Graphics

Tools

Docker

Kubernetes

AWS

GCP

Azure

PyTorch

TensorFlow

HuggingFace

Job description

Client: Develops AI-powered construction takeoff, estimating, bid management, and BIM software that automates preconstruction workflows for contractors and field service businesses.

Requirements:

Research Engineer AI/ML Machine Learning Deep Learning Computer Vision Image Processing Visual Document Understanding Multimodal Models NLP LLM Generative AI Python PyTorch TensorFlow OpenCV HuggingFace Transformers Representation Learning Unsupervised Learning Feature Extraction Model Optimization Quantization Pruning Knowledge Distillation Docker Kubernetes Cloud AWS GCP Azure ML Deployment Production AI Applied AI AI Research Document Intelligence PDF Processing SVG Graphics Startup Environment

Looking for a Research Engineer-II to work on cutting-edge AI solutions focused on Computer Vision, Deep Learning, NLP, and multimodal models. The role involves building AI systems for automated construction take-off and estimation by working with unstructured data such as blueprints, drawings (including SVGs), and PDF documents. The engineer will contribute across the AI lifecycle, from research and experimentation to production deployment.

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 blueprints, scanned PDFs, and SVG files
• Contribute development of multi-modal models that integrate vision with language-based features (NLP/LLMs)
• Support the end-to-end lifecycle of AI-based solutions from prototyping and experimentation to deployment in production
• Follow best data science and machine learning practices, including data-centric development, experiment tracking, model validation, and reproducibility
• Collaborate with 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 industry challenges

Nice to have:

Research Engineer AI/ML Machine Learning Deep Learning Computer Vision Image Processing Visual Document Understanding Multimodal Models NLP LLM Generative AI Python PyTorch TensorFlow OpenCV HuggingFace Transformers Representation Learning Unsupervised Learning Feature Extraction Model Optimization Quantization Pruning Knowledge Distillation Docker Kubernetes Cloud AWS GCP Azure ML Deployment Production AI Applied AI AI Research Document Intelligence PDF Processing SVG Graphics Startup Environment