AI/ML Engineer

Who we’re looking for

We are revolutionizing construction site documentation through computer vision and AI-driven insights. Our platform enables intuitive navigation of job sites, facilitates seamless collaboration between field and office teams, and integrates with industry-leading project management tools.

As an AI/ML Engineer, you will leverage our extensive data lake to architect and deploy cutting-edge machine learning models that turn raw data into actionable intelligence. You will develop modern AI-driven solutions to provide customers with seamless, data-rich insights for enhanced jobsite understanding and collaboration. By building and optimizing high-performance ML pipelines, you will play a critical role in scaling our platform’s capabilities and ensuring our system remains a leader in construction technology innovation.

What you’ll be doing

The primary responsibilities for our next AI / ML Engineer will be to:

• Demonstrate proficiency in machine learning frameworks and apply them to develop robust AI solutions.
• Use and adapt existing VLMs, LLMs, generative AI, RAG architectures, and agents to solve complex construction site challenges.
• Lead data curation and conduct rigorous data quality assessments to prepare datasets for continuous, automated model updates and improvements.
• Collaborate within an agile, multifaceted team to deploy solutions in a cloud environment, enabling fast prototyping and iteration.
• Take proactive ownership of your assigned components, from conception through to production deployment and monitoring.

At Fieldwire, we’re looking for our next AI / ML Engineer to have the following skills and experiences

• Ideally an MSc or Ph.D. in a related technical discipline.
• Proven technical expertise demonstrated through a portfolio of projects where you have built and deployed AI/ML solutions or products.
• Strong background in Computer Vision (CV), Core Deep Learning, and Neural Architectures.
• Experience with modern AI/ML development, such as:
  • Computer Vision & Perception: Experience developing and deploying advanced vision models for detection, segmentation, and classification to interpret complex visual data.
  • Multimodal Systems: Ability to integrate and align vision, language, and other sensor data to create intelligent, context-aware applications.
  • Spatial Intelligence: Familiarity with 3D scene understanding, reconstruction, or geometry-based AI techniques.
• Operational Competencies
  • Proficiency in modern deep learning frameworks and production-grade programming.
  • Experience optimizing models for performance and efficiency, particularly for resource-constrained environments.
  • Understanding of deployment pipelines and model optimization for diverse hardware targets.