Computer Vision, Applied Research Scientist

🕒 Agosto 12

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧬 Cientista Pesquisador(a)

👻 Score fantasma 32%

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Boon

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2023

📦 Logística

💼 Consultoria

🤖 Inteligência Artificial

Logistics • Consulting • Artificial Intelligence

Boon é uma plataforma de IA projetada para frotas comerciais, focando na automação de processos críticos como entrada de dados, obtenção de carga, conformidade e gestão de documentos. Com um financiamento recente de $20,5 milhões, a Boon visa otimizar operações para empresas, conectando sistemas existentes e minimizando fluxos de trabalho manuais. A plataforma emprega agentes de IA para lidar com tarefas repetitivas, melhorar a comunicação entre motoristas e despachantes, e fornecer alertas em tempo real, levando a um aumento de eficiência e redução de erros humanos.

Descrição

• Own end-to-end experiments on Boon’s foundation model, from architecture design through self-supervised pretraining, supervised fine-tuning, and production deployment • Design and evaluate novel multi-stage vision architectures for construction drawing understanding • Drive decisions on backbones, decoders, fusion strategies, loss functions, and training regimes • Run rigorous experiments with baselines, ablations, and held-out evaluation on real construction drawings • Pursue research directions to improve accuracy across construction trades and scopes • Move models from experimental notebooks into the production inference pipeline • Work hands-on with PyTorch, YOLO, SAM, DINO, and other modern computer-vision stacks • Collaborate with ML engineers on deployment, quantization, and serving • Debug failures on customer drawings and incorporate findings into subsequent training runs • Collaborate with synthetic-data, annotation, and infrastructure teams on data and compute needs • Partner with engineering leadership on the accuracy roadmap and strategic direction • Write internal research reports and present findings, trade-offs, and recommendations to engineering leadership • Help determine data acquisition and annotation priorities • Define evaluation datasets and metrics • Identify failure modes and design experiments to address them

🎯 Requisitos

• 3–7+ years in computer vision research • Strong track record of published computer-vision research or trained production computer-vision models shipped at scale • Hands-on expertise in multi-modal dense prediction, including segmentation, detection, or joint vision-language tasks • Production experience with modern vision-transformer backbones such as SAM, DINOv2/v3, CLIP, SigLIP, or similar • Strong PyTorch fluency and experience training large vision models • Ability to move models from research into production inference pipelines • Strong deep-learning fundamentals, including optimization, loss design, regularization, and self-supervised learning • Fluency in English, written and verbal • Ability to collaborate during California business hours • Experience with Graph Neural Networks or relational reasoning architectures is a plus • Experience with text spotting, OCR, or scene-text detection is a plus • Experience with LoRA, adapters, or parameter-efficient fine-tuning is a plus • Experience with self-supervised pretraining is a plus • Experience with engineering or technical drawings, document understanding, or layout analysis is a plus • Contributions to open-source computer-vision research are a plus • Published papers at top venues are a plus

🏖️ Benefícios

• Meaningful equity in an early-stage, well-funded startup • Publication-friendly — we support our team publishing their work at top venues • Autonomy to propose, defend, and run your own experiments, shipping the winners to real customers • Collaboration with a world-class team from top tech companies and research institutions • Work at the intersection of computer vision research and real-world industry impact, in a trillion-dollar market • Potential additional compensation including discretionary bonuses and/or equity in the company