Computational Designer

Company Description

ARPM (Architecture & Placemaking) is an India-based consultancy that brings together urban planning, architecture, and AEC technology. Established in 2019, we serve a global client base across Australia, the USA, Austria, and Germanyas lead consultant, specialist sub-consultant, or advisory partner to governments, developers, design firms, and technology companies. We deliver end-to-end expertise across three integrated verticals: Urban planning, Architecture, and Technology. Our focus is turning ambitious intent into buildable, code-compliant outcomes. We do it with purpose-built digital tools and cross-disciplinary fluency, delivering from city-scale frameworks down to fabrication-ready detail.

Role Description

This is a full-time on-site role for a Computational Designer located in Gurugram. The Computational Designer will take an active part in developing and implementing parametric design solutions, creating workflows for architectural and urban design projects, and optimizing processes to ensure high-quality outcomes. Regular tasks include algorithmic modeling, scripting, data visualization, and creating interactive tools for design projects. Collaboration with multidisciplinary teams to translate conceptual design into implementable solutions will be a key part of this role.

Qualifications

• Bachelors in Architecture or allied field.
• Proficiency in computational design software such as Grasshopper, Rhino, and BIM tools.
• Intermediate to advanced skills in scripting languages like Python, C#, or JavaScript.
• Experience in parametric design, algorithmic workflows, and data visualization.
• Strong understanding of urban planning, architecture principles, and design processes.
• Ability to create purpose-built digital tools and streamline large-scale project workflows.
• Excellent problem-solving skills and the ability to collaborate within multidisciplinary teams.
• Educational background in architecture, urban design, computational design, or a related field.
• Familiarity with ShapeDiver, GIS software, machine learning integration, and fabrication workflows is a plus.