• Design, write, and maintain high-quality, efficient, and maintainable code in accordance with team standards and best practices • The development and long-term maintenance of web crawlers and scrapers — this will be the primary and strategic focus of the role • Analyze, optimize, and significantly improve existing functionality with an eye toward performance, scalability, and reliability • Drive technical decisions, evaluate trade-offs, and introduce new technologies and approaches when appropriate • Solve complex, non-standard problems and take a proactive role in defining robust technical solutions • Collaborate closely with other engineers, share expertise, and contribute to improving overall engineering quality

Role Description We are seeking a Senior AI Engineer to lead the development of automated building design systems and advance the state-of-the-art in AI/ML applications for the built environment. You'll architect and implement generative design algorithms, computer vision systems, and optimization models that fundamentally transform how buildings are conceived, designed, and validated. This role sits at the intersection of deep learning, computational geometry, and architectural design, creating AI systems that augment human creativity while respecting engineering constraints and building codes. This is a rare opportunity to apply cutting-edge AI research to one of humanity's most fundamental challenges: creating better spaces for people to live, work, and thrive. Key Responsibilities - Design and implement generative AI models for automated building design, including floor plan generation, facade design, and structural optimization using state-of-the-art architectures (diffusion models, transformers, GANs). - Develop computer vision pipelines for design and drawing analysis using modern frameworks like YOLO, SAM, and NeRF-based 3D reconstruction. - Build graph neural networks and geometric deep learning models for structural analysis and MEP (Mechanical, Electrical, Plumbing) system optimization. - Create reinforcement learning systems for multi-objective building optimization (energy efficiency, cost, occupant comfort, sustainability metrics). - Integrate AI models with industry-standard BIM tools (Revit, Rhino/Grasshopper) through custom APIs and plugins. - Deploy production ML pipelines using modern MLOps practices, including experiment tracking (Weights & Biases, MLflow), model versioning, and A/B testing frameworks. - Implement physics-informed neural networks for building performance simulation and predictive modeling. - Collaborate with architects and engineers to ensure AI systems produce practical, code-compliant, and constructible designs. - Lead research initiatives and publish findings to establish us as a thought leader in AEC AI innovation. Qualifications - Master's degree or PhD in Computer Science, AI/ML, Computational Design, or related field (or equivalent industry experience). - 3-5+ years of hands-on experience building and deploying ML models in production environments. - Deep expertise with modern deep learning frameworks (PyTorch preferred). - Strong foundation in computer vision, 3D geometry processing, and spatial reasoning algorithms. - Experience with generative AI models (VAEs, GANs, Diffusion Models, Transformers) and their practical applications. - Proficiency in Python and scientific computing libraries (NumPy, SciPy, scikit-learn, Open3D, trimesh). - Experience with cloud ML platforms (AWS SageMaker, Vertex AI, or Azure ML) and distributed training frameworks. - Understanding of optimization techniques (genetic algorithms, gradient-based optimization, constraint satisfaction). - Strong software engineering practices and experience with containerization (Docker) and orchestration (Kubernetes). - Excellent communication skills to translate complex AI concepts to domain experts and stakeholders. Preferred Qualifications - Experience with computational design tools (Grasshopper, Dynamo) and parametric modeling. - Familiarity with building information modeling (BIM) standards and IFC data schemas. - Knowledge of graph neural networks (PyTorch Geometric, DGL) for structural and spatial analysis. - Experience with physics simulation engines (Mujoco, Isaac Sim) or FEA integration. - Background in multi-agent reinforcement learning for complex system optimization. - Contributions to open-source ML projects or published research in relevant venues (NeurIPS, ICML, CVPR, or domain-specific conferences). - Experience with point cloud processing and 3D scene understanding (PointNet++, DGCNN). - Understanding of construction workflows and building codes. Benefits - The opportunity to define and build AI systems that will reshape a $10 trillion global industry. - Access to unique datasets and real-world problems at the intersection of AI and the built environment. - Collaboration with leading architects, engineers, and construction professionals who are eager to embrace AI transformation. - Resources to pursue cutting-edge research while maintaining a focus on practical, deployable solutions. - Mentorship from industry veterans who understand both the technical and business aspects of AEC technology. - The freedom to experiment with emerging AI architectures and techniques in a high-impact domain. Why us? Here, AI engineers aren't building demos—you'll be creating systems that influence how real buildings get designed and built. We believe the AEC industry is on the cusp of an AI revolution, and we're positioning ourselves at the forefront. Our team has the domain expertise to identify the right problems, the technical depth to solve them, and the industry connections to deploy solutions at scale. If you're passionate about using AI to create a more sustainable, efficient, and beautiful built environment, this is where you can make it happen.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Lyrasis is seeking a Full Stack Engineer who will be joining a diverse engineering team in the Ebooks and Community Engagement (EBCE) Department working on the Palace Project platform. You will closely collaborate with product, operations, and support teams to build solutions that provide our users and library partners with a great digital experience. As part of a small team, you will be involved in all stages of the development process: - Contributing code to backend services and frontend interfaces - Refactoring and architectural design - Deploying and monitoring services - Documenting your work - Troubleshooting issues Qualifications - 3+ years of experience developing backend applications in Python - 2+ years of experience with JavaScript development (React preferred) - Proven understanding of web service development best practices - Experience refactoring and modernizing codebases - Strong written and verbal communication skills Requirements - Develop and maintain backend services using Python (Flask, SQLAlchemy) - Build and enhance frontend interfaces using JavaScript (React, Next.js) - Contribute to technical architecture and design decisions - Deploy, monitor, and maintain backend services in AWS - Troubleshoot issues across the full application stack - Collaborate with cross-functional teams to deliver high-quality solutions Benefits - Salary Range: $95,000 to $100,000 per year - This position is fully remote - Occasional travel to Lyrasis company events and in-person professional development and conferences Application Details - Applications will be accepted through Thursday, March 19, 2026 - Applications must include: Cover Letter and Resume - Applications without a Cover Letter will NOT be considered

• Set technical direction for our document content extraction and transformation team, establishing patterns for scalable, secure, and performant systems on AWS. • Lead architectural decisions that use OCR technologies such as Tesseract and Apryse OCR. • Drive initiatives that improve scalability, performance, and reliability of the product while considering and implementing changes that control costs without impacting customer satisfaction. • Guide the evolution of our content extraction and transformation technology stack as the business and customer needs mature and scale. • Make critical technical decisions that balance user experience, performance, security, and maintainability. • Design and implement event-driven architectures using AWS services, Kafka, and modern data pipelines. • Build production-grade applications across C#/.Net, AWS services, and document extraction/transformation technologies. • Design and implement scalable APIs (REST, GraphQL) that power our front-end and enable third-party integrations. • Integrate AI-driven services and emerging technologies to enable greater backend efficiencies and increase customer productivity. • Build the product to enable seamless, scalable, and flexible semantic search capabilities. • Ensure security, performance, and compliance considerations are applied across all implementations. • Solve complex technical challenges from real-time customer experiences and issues to event-driven document processing at scale. • Take full ownership of initiatives from concept through production and ongoing evolution. • Make sound architectural decisions by weighing trade-offs with reasoning that stands up over time. • Proactively identify and address technical debt before it impacts the team. • Write high-quality, well-tested code across the full stack with emphasis on maintainability. • Design resilient systems that maintain uptime and performance as we scale globally. • Implement observability through logging, metrics, and telemetry to proactively triage issues. • Monitor and optimize performance at scale, identifying bottlenecks and implementing solutions. • Create comprehensive technical documentation including architectural diagrams and design decisions. • Partner closely with product management to translate requirements into technical solutions. • Mentor engineers across experience levels, elevating technical skills and best practices. • Collaborate with Platform Services, Ops, and other teams on integration points and shared infrastructure. • Build consensus on technical approaches while having authority to make final decisions when needed. • Lead knowledge-sharing initiatives through code reviews, design discussions, and documentation. • Stay at the forefront of content extraction and transformation technologies and industry trends, cloud-native architectures, and AI-powered tools. • Research and prove out new technologies through POCs that align with product strategy. • Contribute ideas that directly improve engineering velocity and quality.