AI/ML Engineer
Fieldwire · San Francisco, CA (Hybrid) or United States (Remote)
About this role
## AI/ML Engineer **Who We're Looking For** We are revolutionizing construction site documentation through 360° video capture, 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 site captures into actionable intelligence. You will develop modern AI-driven solutions to provide customers with seamless, data-rich insights for enhanced jobsite understanding and collaboration. **What You'll Be Doing** • 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 **Required Skills & Experience** • MSc or Ph.D. in a related technical discipline (preferred) • Proven technical expertise demonstrated through a portfolio of AI/ML projects and deployed solutions • Strong background in Computer Vision, Core Deep Learning, and Neural Architectures • Experience with modern AI/ML development: - **Computer Vision & Perception**: Detection, segmentation, and classification for complex visual data - **Multimodal Systems**: Integration of vision, language, and sensor data - **Spatial Intelligence**: 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 in resource-constrained environments - Understanding of deployment pipelines and model optimization for diverse hardware targets
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