Computer Vision Applied Research Scientist (AI)

Location: United States (Remote); collaboration during California business hours

Company

hirify.global is an early-stage AI platform for construction that embeds AI agents into estimating and bid-management workflows.

What you will do

• Design and evaluate novel multimodal vision architectures for construction drawing understanding, including perception, text-object association, and relational reasoning.
• Drive decisions on backbones, decoders, fusion strategies, loss functions, and training regimes.
• Run rigorous baselines, ablations, and held-out evaluations on real construction drawings.
• Own supervised training and self-supervised pretraining with PyTorch and modern computer vision stacks such as YOLO, SAM, and DINO.
• Move successful models from research notebooks into production inference pipelines, collaborating on deployment, quantization, and serving.
• Define evaluation datasets and metrics, investigate real customer failure modes, and communicate findings to engineering leadership.

Requirements

• Must be based in the United States.
• 7+ years of computer vision research experience or equivalent experience in an industry research lab, applied science team, or PhD research and industry.
• Deep hands-on experience with multimodal vision transformers and dense prediction tasks such as segmentation, detection, or joint vision-language tasks.
• Production experience with modern vision transformer backbones, including SAM, DINOv2/v3, CLIP, SigLIP, or similar models.
• Strong PyTorch fluency and experience training large vision models, with deep fundamentals in optimization, loss design, regularization, and self-supervised learning.
• Clear written and verbal English communication and availability during California business hours.

Nice to have

• Graph Neural Networks or relational reasoning architectures.
• Text spotting, OCR, or scene text detection integrated with vision models.
• LoRA, adapters, or parameter-efficient fine-tuning of large vision models.
• Experience with engineering drawings, document understanding, or layout analysis.
• Open-source contributions or publications at CVPR, ICCV, ECCV, NeurIPS, or ICLR.

Culture & Benefits

• High autonomy to propose, defend, and run research experiments.
• Publication-friendly environment supporting research publication at top venues.
• Direct ownership of a foundation model for construction drawings and its impact on real customers.
• Collaboration with experienced engineering and research professionals from leading technology companies and institutions.
• Meaningful equity in an early-stage, well-funded startup.