Full-Time

Computer Vision Engineer

Posted on 10/31/2025

Duranta

Duranta

11-50 employees

AI-powered landscape business management platform

Compensation Overview

$150k - $210k/yr

Seattle, WA, USA

In Person

Category
AI & Machine Learning (2)
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Requirements
  • Have 2+ years experience in ML / deep learning, ideally in Computer Vision
  • Have strong coding ability (Python, PyTorch)
  • Have trained segmentation/detection models on real-world data at scale
  • Have experience with generative modeling and large foundation models
  • Have worked in startups or fast-moving teams and can wear many hats
Responsibilities
  • Building the components of a state-of-the-art computer vision pipeline for our AI system
  • Build and improve CV models (e.g., Mask2Former, SAM, ViT, Swin) for aerial and oblique imagery
  • Run experiments at scale with deep learning frameworks like PyTorch
  • Develop and maintain clean, modular ML infrastructure
  • Collaborate on model deployment and inference optimizations
  • Read and reproduce ideas from latest papers (CVPR, NeurIPS and other similar top-tier venues)
Desired Qualifications
  • Experience with high-res aerial/remote sensing imagery and LiDAR
  • Experience with self-supervised and weakly-supervised learning
  • Knowledge of 3D, CAD and computer graphics
  • Experience with cloud computing (e.g., AWS)

Duranta builds software for landscaping and lawn care professionals. It offers a SaaS platform that unifies property measurement, landscape design, CRM, and invoicing/payments. The flagship AIdan AI model automatically measures property details (like lawn square footage and other surfaces) to generate customer proposals and estimates, reducing the need for on-site visits. A graphics engine handles landscape design, while the CRM and invoicing tools (integrating with QuickBooks) help manage customers and payments. The company differentiates itself with an experienced team from Aurora Solar and big tech companies, and by providing an end-to-end toolset tailored for outdoor service businesses. Duranta’s goal is to streamline operations and boost profitability for thousands of small and medium-sized landscaping firms, supported by seed funding of $7 million to accelerate product development and growth.

Company Size

11-50

Company Stage

Seed

Total Funding

$7M

Headquarters

Seattle, Washington

Founded

2024

Simplify Jobs

Simplify's Take

What believers are saying

  • Fragmented landscaping industry with <15% digital adoption offers massive TAM expansion opportunity.
  • Customers already closing large contracts without site visits, validating core AIdan value proposition.
  • Angel investors Thomas Dohmke and Andrew Miklas provide credibility and downstream funding network access.

What critics are saying

  • Satellite imagery providers integrate native AI measurement, commoditizing AIdan's core differentiation within 18–36 months.
  • ServiceTitan, Jobber, Housecall Pro add AI measurement via acquisition, leveraging 50,000+ existing landscaper bases.
  • $7M seed provides only 18–24 months runway; Series A required by Q2–Q3 2027 if unit economics deteriorate.

What makes Duranta unique

  • AIdan AI automatically generates precise property estimates from satellite imagery, eliminating on-site visits.
  • Mobile-first platform saves landscapers three hours daily on estimates, design, and administrative tasks.
  • Founding team built Aurora Solar, bringing proven cleantech software execution to landscaping operations.

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Benefits

Remote Work Options

Company News

FinSMEs
Jul 14th, 2025
Duranta Raises $7M in Seed Funding

Duranta, a Seattle, WA-based provider of a software platform for landscapers and lawn care professionals and their businesses, raised $7M in Seed funding.

Landscape Management
Jul 10th, 2025
Exclusive: Duranta secures $7 million seed round | Landscape Management

Duranta empowers the professionals shaping the outdoor world to succeed by providing modern tools that help them attract customers, deliver exceptional service, and manage their operations efficiently.

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