AI/ML Engineer - Computer Vision (Entry to Mid-Level

SSN CorporationPosted Mar 20, 2026Position Filled

About the Company

SSN Corporation is a Design and Build General Contractor offering services in building construction, building and infrastructure design, land planning and subdivision, structural, site/civil, geotechnical, and MEP design, construction inspection and material testing as well as permitting and construction support.

Role Overview

SSN Engineers Nepal Pvt. Ltd. is hiring for QTakeoff.ai, an AI startup that automates construction quantity takeoff from 2D architectural and engineering drawings. Our goal is to save construction professionals significant time and effort by using computer vision and machine learning to extract and quantify elements directly from plan sheets. You will play a hands-on role in building the core models that power our product.

We know the ideal candidate may be hard to find in Nepal. We value curiosity and a willingness to learn just as much as experience. If you meet most of the criteria below and are excited to grow, we encourage you to apply.

Key Responsibilities

Train and fine-tune object detection models (such as YOLO) to identify construction elements - walls, doors, windows, columns - from 2D drawings and blueprints
Help build and maintain data pipelines for preprocessing engineering drawings (PDFs, scanned images, CAD exports) as model inputs
Support dataset creation: annotating drawings and organizing training data using tools such as Roboflow or LabelImg
Assist in integrating trained models into backend APIs so outputs can be consumed by the application layer
Assist with document parsing workflows to extract dimensions, symbols, and annotations from drawing sheets
Track and report on model performance, and iterate to improve results over time
Collaborate closely with the product team and prepare regular progress updates

Requirements

Basic understanding of machine learning concepts and how models are trained
Exposure to computer vision or object detection - even through coursework, personal projects, or online learning - is a strong plus
Familiarity with YOLO, PyTorch, or TensorFlow is desirable but not required
Sound Python programming skills - this is the primary language used
Comfortable working with image processing libraries such as OpenCV
Basic experience with APIs (consuming or building) is helpful
Self-motivated with an ability to research and learn independently
Detail-oriented with strong problem-solving ability
Clear communicator who can present technical progress to non-technical team members

Qualifications & Experience

Bachelor's or master's degree in computer science, Computer Engineering, or a related field
Exposure to PDF or image parsing libraries (e.g., PyMuPDF, pdf2image)
Awareness of CAD formats (DWG, DXF) or tools like AutoCAD
Familiarity with Git/GitHub for version control
Any exposure to construction drawings or engineering document conventions

Knowledge of cloud platforms (AWS, GCP, or Azure) is a plus, not a requirement

Perks & Benefits

Opportunity to work on a cutting-edge AI product in the construction technology space
Hands-on experience in real-world computer vision and machine learning applications
Collaborative and learning-focused work environment
Potential for long-term engagement based on performance
Flexible working arrangement for suitable candidates

Additional Info

Location: Kathmandu, Nepal (Remote-friendly for suitable candidates)
Job Type: Contract – Full Time
Working Hours: Sunday to Friday, 8:00 AM – 4:00 PM (NPT)
Duration: 6 months (extendable based on performance)
Compensation: Negotiable (paid monthly)
Selection Process: Two-stage interview (Initial Screening + Technical Interview)
Application Requirement: Resume, Cover Letter, Statement of Purpose (SOP), and GitHub/profile portfolio (preferred)

To apply, please submit your cover letter, Statement of Purpose (SOP), and resume. A GitHub profile or any project portfolio is highly encouraged.

Apply via LinkedIn, website job vacancy announcement or send your resume to pbasnet@ssnbuilders.com

Position Filled

This role is no longer accepting applications.

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