Mid-Level AI & Machine Learning Engineer, Fieldwire

• If you have strong experience in delivering impactful AI solutions while ensuring applications remain secure, scalable, and performant, Fieldwire wants to talk to you!
• Bachelor’s or Master’s degree in Computer Science or equivalent work experience
• 3+ years experience in a Fullstack, Backend, AI Engineering, or Machine Learning role
• Strong practical experience in machine learning, including training, evaluating, and deploying models
• Hands-on experience with computer vision and image-processing techniques
• Knowledge of modern toolchain used for developing high-quality applications
• Expert at writing clean, well-tested, and modular code

Desirable

• As a Mid-Level AI & Machine Learning Engineer, you will be joining a team of talented and passionate engineers focused on creating the next generation of AI features to make Fieldwire the World’s best Construction Management Platform!
• Your role will focus on adapting existing models, running models in our own infrastructure, as well as extracting and categorizing meaningful information from complex documents, PDFs and images
• Your work building core AI features and services will directly impact all of our 1 million end users
• Architect, build, and maintain AI foundations across the full stack, embedding them into core platform capabilities
• Evaluate & select open-source models, adapt them to our domain specific cases through fine-tuning, transfer learning and lightweight training
• Deploy and operate models within our own infrastructure, including GPU-backed environments with a strong focus on inference performance, resource utilization, throughput & latency
• Develop solutions for image understanding, visual object detection, classification and segmentation
• Extract and interpret information from PDFs, scanned documents, images, and other complex visual content, combining OCR, document layout analysis, and multimodal models
• Apply AI and computer vision techniques to surface relevant, context-aware information within users’ workflows, leveraging context to power smarter product experiences
• Debug production issues across services and multiple levels of the stack
• Work to improve our Engineering standards, tooling, and processes