Mid-Level AI & Machine Learning Engineer

Fieldwire•San Francisco, CA

9d•$170,000 - $195,000•Hybrid

About The Position

As a Mid-Level AI & Machine Learning Engineer, you will join a team developing AI features for Fieldwire’s construction management platform. The role focuses on adapting existing models, running models on Fieldwire’s own infrastructure, and extracting and categorizing useful information from complex documents, PDFs, and images. You will build core AI features and services used by Fieldwire’s end users, while helping ensure applications are secure, scalable, and performant. The position is hybrid in San Francisco, California.

Requirements

Bachelor’s or Master’s degree in Computer Science, or equivalent work experience.
At least 3 years of experience in a full-stack, 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 tools used to develop high-quality applications.
Expertise writing clean, well-tested, and modular code.

Nice To Haves

Experience working with pretrained models and adapting them to domain-specific tasks through fine-tuning and transfer learning.
Understanding of modern model architectures, including transformers and vision-language models.
Experience with image and document processing, including OCR, document layout analysis, or extracting structured information from PDFs and images.
Experience building production systems, preferably in Rust, Ruby on Rails, or Angular.

Responsibilities

Architect, build, and maintain AI foundations across the full stack, embedding them into core platform capabilities.
Evaluate and select open-source models, adapting them to domain-specific use cases through fine-tuning, transfer learning, and lightweight training.
Deploy and operate models within Fieldwire’s infrastructure, including GPU-backed environments, with attention to inference performance, resource utilization, throughput, and 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 using OCR, document layout analysis, and multimodal models.
Apply AI and computer vision techniques to surface relevant, context-aware information in users’ workflows and enable smarter product experiences.
Debug production issues across services and multiple levels of the stack.
Improve engineering standards, tooling, and processes.