Senior Computer Vision / Applied AI Engineer - Construction Plans, Open to On-site / Hybrid / Remote
14 days ago
Bakersfield
Hey, we're KonstructIQ \n \n KonstructIQ is a fast-growing startup on a mission to modernize residential construction. We're building the system of record for how contractors run their business - spanning estimating, projects, finances, and money movement. AI is at the center of our product. Contractors can upload construction plans, photos, or describe a project and use KonstructIQ to generate scopes of work, takeoffs, and detailed estimates in minutes. \n \n About the Role \n \n We're looking for a Senior Computer Vision / Applied AI Engineer to improve how KonstructIQ reads construction plans and generates takeoffs - detecting rooms, walls, doors, windows, fixtures, symbols, and dimensions, and turning them into reliable quantities and measurements. \n You'll be part of a small team that owns the full pipeline: document ingestion, image and vector processing, scale and geometry, detection and segmentation, multimodal reasoning, measurement, validation, and evaluation. This role is open to on-site / hybrid / remote. \n \n What You'll Be Doing \n \n\n • Build and improve computer vision and multimodal AI systems that detect, classify, segment, and measure plan elements - walls, rooms, doors, windows, fixtures, finishes, and symbols - extracting counts, dimensions, and areas\n, • Improve scale detection and geometric reasoning across drawings of varying scale, orientation, resolution, and format, combining vector PDF data, raster imagery, OCR, and multimodal foundation models\n, • Decide when to use traditional CV, specialized models, multimodal LLMs, deterministic algorithms, or hybrid approaches, and build structured, production-ready outputs from foundation models\n, • Build deterministic post-processing and validation systems - including confidence scoring - that turn probabilistic model outputs into stable, explainable takeoffs and flag ambiguous results instead of silently guessing\n, • Build evaluation frameworks and datasets (labeling strategies, estimator feedback loops) that measure detection accuracy, measurement variance, and end-to-end takeoff quality, and turn production failures into new test cases and model improvements\n, • Build visual overlays and debugging tools that make it easy to see what the system detected, measured, and missed\n, • Partner with construction estimators, product, and engineering to translate real-world estimating workflows into technical solutions, and evaluate new CV/multimodal models where they materially improve accuracy or simplify the system\n\n \n Skills and Attributes We're Looking For \n \n\n • Bachelor's degree with 3+ years of experience in computer vision, machine learning, applied AI, or related engineering roles; MS/PhD with a focus in computer vision preferred\n, • Strong experience building production computer vision systems, not just research prototypes\n, • Deep knowledge of object detection, segmentation, image processing, and geometric reasoning (coordinate systems, transformations, polygons, spatial relationships)\n, • Strong Python experience with CV/ML frameworks such as PyTorch, OpenCV, YOLO, Detectron2, or similar\n, • Experience with multimodal vision-language models, and judgment for where foundation models outperform - or underperform - traditional CV approaches\n, • Experience processing complex documents, diagrams, engineering drawings, PDFs, or other spatial/visual documents, ideally combining OCR with visual information\n, • Experience designing datasets, labeling strategies, training pipelines, and evaluation frameworks\n, • Strong debugging intuition - able to distinguish model, data, geometry, and pipeline problems, and optimize for real-world accuracy and consistency, not just benchmarks\n, • Comfortable with ambiguous problems with no off-the-shelf solution; high ownership and high agency from experimentation through production\n\n \n Bonus Points \n \n\n • Experience with architectural drawings, blueprints, CAD, BIM, construction documents, or takeoff software\n, • Experience with vector PDF parsing, CAD formats, or computational geometry libraries\n, • Experience with floor-plan understanding, document AI, geospatial imagery, or other precise spatial-reasoning applications\n, • Experience building human-in-the-loop ML systems where user corrections improve future model performance\n, • Background in construction tech or prior startup experience\n\n \n Our Values \n \n\n • Act like an owner\n, • Strive for excellence\n, • Communicate openly and honestly\n, • Lead with data\n, • Succeed in work and life\n\n \n Why You'll Love Working Here \n \n\n • Work on a technically difficult computer vision problem with immediate real-world impact\n, • Own a core part of KonstructIQ's AI platform and product differentiation\n, • Work with a growing dataset of real construction plans, takeoffs, estimates, and estimator feedback\n, • See your models used directly by contractors to bid and execute real construction projects\n, • Small team, high ownership, and the ability to shape the technical architecture from the ground up\n, • Competitive salary and meaningful equity\n