Applied AI Engineer

Foresight builds a platform that connects project schedules, field progress and execution data for complex capital projects. The Applied AI Engineer will build, train, deploy and monitor machine-learning models and backend features for project risk prediction, planning, progress tracking and risk mitigation.

Responsibilities:

• Risk prediction: Build, train and deploy models that predict if a project will be at risk and by how much
• Criticality prediction: Build models that use project plans to identify which of the tasks are the most critical to complete the project on time before the project even starts
• Project planning: Build models that accept blueprints and 3D Replit models to create project timelines and scaffolding as the starting point for human planners to make project planning a breeze
• Progress trackers: Build models that take in multi-model data from static cameras or videos from humans/drones on-site, voice notes, etc about a task to predict what percent of the task is complete
• Risk mitigation: Build, train and deploy models that can predict the best path forward for risk mitigation or timeline amelioration for major projects
• Continuous improvement: Evaluate models repeatedly and prototype methods and new models to improve the accuracy of current features, inspired by latest research publications
• Own features from technical design through release and beyond: measure adoption, learn and keep improving
• Work alongside Full Stack engineers to help them turn new models into production features customers rely on
• Partner with product, design and customers to find the problems most worth solving
• Tune performance across the modelling stack, from accuracy to latency and reliability
• Raise the bar on architecture, testing, observability and how the team ships
• Help shape the product and technical roadmap