Spatially intelligent layer embedded within SSI’s ShipConstructor and SPLM products extending its capabilities providing full 3D geometric understanding and reasoning for objects, assemblies and systems - BC-1013

Project type: Innovation
Desired discipline(s): Engineering - other, Engineering, Computer science, Mathematical Sciences, Statistics / Actuarial sciences
Company: SSI
Project Length: 6 months to 1 year
Preferred start date: 07/06/2026
Language requirement: English
Location(s): Victoria, BC, Canada
No. of positions: 2
Desired education level: Master'sPhDPostdoctoral fellowRecent graduate
Open to applicants registered at an institution outside of Canada: No

About the company: 

With 35 years of experience, SSI is a global company with a dynamic, fast-paced, and accountable culture. We deliver industry-leading software for the shipbuilding and offshore sectors, from the widely adopted ShipConstructor (SC) CAD platform to the integrated Shipbuilding Product Lifecycle Management (SPLM) solution that connects engineering, planning and production, helping shipyards work smarter, reduce risk, and deliver complex projects with precision confidence.

Describe the project.: 

This proposal outlines the development of a spatially intelligent AI layer integrated into ShipConstructor and SPLM, extending its capabilities providing full 3D geometric understanding. The system will incorporate spatial reasoning to interpret components details, where they exist and how they relate physically within the vessel. By leveraging geometric data alongside metadata and relationships, users will be able to query and explore the model with spatial relationships, enabling a more natural and intuitive interaction with vessel objects. This approach transforms SC and SPLM into a unified environment where geometry, data and relationships are seamlessly combined.

A core capability of the system will be the ability to reason across geometry to detect design issues, evaluate changes and guide user interaction. The solution will augment traditional rule-based methods by understanding clashes, clearance violations and spatial based risk on explicit constraints and learned patterns. It will also evaluate the downstream impact of geometric modifications, identifying affected systems and highlighting areas requiring redesign or rerouting. AI-guided navigation to modeled objects will allow users explore connected components and understand dependencies with context. In parallel, spatial analysis will assess whether components can be installed, accessed or maintained providing insights such as viable access paths, clearance envelopes and potential physical constraints that may impact production.

The system will support optimization and knowledge reuse through geometry-driven intelligence. It will suggest improved layouts, routing strategies on spatial constraints and historical patterns, while also identifying similar configurations across past projects to promote reuse of proven designs. Additionally, the platform will generate spatial summaries and insights, highlighting areas of congestion, potential design conflicts and regions of interest within selected volumes or compartments. Together these capabilities will position ShipConstructor and SPLM as an intelligent, geometry-aware platform that enhances decision making, reduces design risk and bridges the gap between engineering and physical realization.

Required expertise/skills: 

• Strong programming experience in SQL, Python, and C# for application and backend development
• Experience with SQL and relational database design, including data modeling and query optimization
• Experience with machine learning, artificial intelligence concepts including model development and evaluation
• Exposure to generative AI techniques (e.g. LLMs, agent-based systems)
• Familiarity with retrieval-augmented generation (RAG)
• Familiarity with CAD systems
• Solid understanding of 3D geometry, geometric modeling and spatial structures
• Understanding of distributed systems and scalable architecture