AI powered intelligence layer embedded within SSI’s products - BC-1012

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 project proposes the development of an AI powered intelligence layer embedded within ShipConstructor. At its core, the layer will build and maintain rich relationships between parts, assemblies, systems and associated metadata across the ship model. By leveraging these connections, the solution aims to enable users to seamlessly explore and correlate data that traditionally exists in fragmented views. The interface will act as the central access point, providing a unified environment where users can interrogate the model, uncover dependencies, and better understand how individual components contribute to the broad vessel design.

A key component of this initiative is the introduction of a natural language interface that functions as a semantic interpreter allowing users to interact with the model in an intuitive and conversational manner. This capability will be paired with relationship-aware reasoning, enabling the system to traverse complex dependencies and evaluate the impact of design changes across interconnected objects. Context-aware navigation will further enhance usability by surfacing relevant information, related components and historically linked work patterns based on user activity. In addition, assisted query building will help refine user intent into precise structured queries, lowering the barrier to entry for new users while improving efficiency for experience designers.

Beyond real-time interaction, the system will incorporate cross-project intelligence to identify patterns, similarities and reusable design elements across multiple vessels. It will also generate automated summaries and reports distilling large volumes of model data into actionable insights for engineering, production and management teams. Integration with ShipBuildingPLM will extend visibility into life cycle and production status, enabling users to assess progress, identify risks, and make informed decisions. Together, these capabilities will position SC and SPLM as intelligent hubs that not only provides access to data, but actively enhances understanding, productivity and consistency across projects.

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)
• Understanding of distributed systems and scalable architecture