Senior Computer Vision / Applied AI Engineer - Construction Plans, Open to On-site / Hybrid / Remote in Santa Clarita

Energy Jobline
Santa Clarita, CA, United States
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Computer-Aided Design Artificial Intelligence Computer Vision Building Information Modeling Python (Programming Language) Machine Learning Object Detection OpenCV Parsing Tensorflow Computational Geometry Pytorch

Requirements

  • 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 \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- 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, * 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

Benefits & conditions

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.

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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.

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What You’ll Be Doing

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  • 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, , 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

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\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

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Bonus Points

\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

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Our Values

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  • Act like an owner \n

  • Strive for excellence \n

  • Communicate openly and honestly \n

  • Lead with data \n

  • Succeed in work and life \n

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Why You’ll Love Working Here

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  • 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

Apply for this position

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Apply on www.energyjobline.com
Prepare application