Full-Time

Computer Vision Engineer

Duranta

Duranta

11-50 employees

AI-powered landscape business management platform

Compensation Overview

$160k - $275k/yr

Seattle, WA, USA

In Person

On-site role in Seattle, Washington.

Category
AI & Machine Learning (1)
Required Skills
LLM
Python
Neural Networks
PyTorch
Machine Learning
Computer Vision

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Requirements
  • Have 5+ 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

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Simplify Jobs

Simplify's Take

What believers are saying

  • Duranta raised $7 million in July 2025 from Base10, Pear, and operators.
  • AIdan removes site visits, which directly saves sales time and improves close rates.
  • The platform combines CRM, design, invoicing, and QuickBooks integration into one workflow.

What critics are saying

  • ServiceTitan's January 2026 Aspire acquisition intensifies competition against Duranta's commercial landscaping wedge.
  • Jobber, LMN, QuoteIQ, and Yardbook already crowd pricing-sensitive SMB landscapers.
  • If AIdan measurement accuracy disappoints, Duranta loses trust and proposal workflows quickly.

What makes Duranta unique

  • Duranta's 2025 AIdan automates property measurement, estimates, and proposals for landscapers.
  • Samuel Adeyemo brings Aurora Solar operating-system experience to a narrow vertical workflow.
  • Seattle headquarters and 2024 founding position Duranta as a new, focused category entrant.

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Benefits

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

4%

1 year growth

4%

2 year growth

10%
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.