Full-Time

3D Perception Engineer

SLAM with Mono Cameras

EchoTwin AI

EchoTwin AI

11-50 employees

AI vision sensors for urban analytics

No salary listed

San Francisco, CA, USA

In Person

Category
AI & Machine Learning (2)
,
Required Skills
Python
C/C++
OpenCV
Requirements
  • Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field. A PhD is a plus.
  • Three or more years of experience in computer vision, SLAM, or related perception systems.
  • Strong proficiency in C++ and/or Python for algorithm development and optimization.
  • Hands-on experience with monocular SLAM techniques, including feature detection, tracking, and loop closure.
  • Experience with deep learning-based approaches for monocular depth estimation or visual odometry.
  • Knowledge of sensor fusion techniques, particularly with inertial measurement units or other inertial sensors.
  • Familiarity with computer vision libraries such as Open Computer Vision Library, Point Cloud Library and frameworks such as Robot Operating System and Eigen.
  • Experience deploying SLAM systems in real-world applications, such as autonomous vehicles or drones.
  • Understanding of camera models, calibration, and image processing techniques.
  • Experience with real-time systems and optimizing algorithms for embedded platforms.
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
Responsibilities
  • Design and develop monocular SLAM algorithms for real-time localization and 3D mapping in dynamic environments.
  • Optimize SLAM pipelines for performance, accuracy, and computational efficiency on resource-constrained platforms.
  • Integrate monocular camera data with other sensor inputs (e.g., IMU) to enhance system robustness.
  • Conduct experiments to evaluate and improve SLAM performance under varying lighting, occlusion, and motion conditions.
  • Collaborate with cross-functional teams, including robotics, software, and hardware engineers, to integrate SLAM solutions into production systems.
  • Implement and test algorithms in C++ and/or Python, ensuring scalability and reliability.
  • Stay updated on the latest advancements in computer vision, SLAM, and monocular depth estimation, incorporating relevant techniques into development.
  • Document technical designs, algorithms, and experimental results for internal and external stakeholders.

EchoTwin AI sells and implements AI-powered vision sensor systems for vehicles, drones, and urban platforms to collect real-time visual and environmental data in cities. Its CityView product uses computer vision and natural language understanding to help urban managers make informed decisions, automate compliance monitoring, and scale urban intelligence across streets, sidewalks, and service areas. The company combines sensors, AI analytics, and a services bundle that covers consulting, strategy, implementation, deployment, ongoing support, optimization, and training. It partners with local networks to deliver its platform globally. Revenue comes from product sales, professional services fees, and licensing of its patented technologies.

Company Size

11-50

Company Stage

Seed

Total Funding

$8M

Headquarters

Dubai, United Arab Emirates

Founded

2024

Simplify Jobs

Simplify's Take

What believers are saying

  • Global smart cities market projected to reach $4 trillion by 2030 with massive expansion potential.
  • Active pilot projects across US, Europe, and Middle East validate platform for real-world municipal deployment.
  • Secured $8M seed funding from Metis Ventures and strategic investors including Automotive Ventures and Supernova.

What critics are saying

  • NVIDIA Metropolis and OpenAI multimodal models commoditize proprietary vision-language capabilities within 12-18 months.
  • UAE data sovereignty regulations force 40% higher server costs or loss of government pilot contracts.
  • Huawei CityBrain dominates Middle East and Asia municipal contracts, eroding EchoTwin's pilot pipeline.

What makes EchoTwin AI unique

  • Proprietary visual intelligence engine with full spatial reasoning for autonomous issue detection and resolution.
  • Agentic AI workflows automate compliance monitoring from detection through regulatory follow-up without human intervention.
  • Deep active learning in vision-language models achieves superior anomaly detection rates versus commodity vision platforms.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

Health Savings Account/Flexible Spending Account

401(k) Retirement Plan

401(k) Company Match

Unlimited Paid Time Off

Profit Sharing

Company News

Ars Technica
Mar 6th, 2026
Ex-CEO of $464M AI startup accused of forging board signatures, selling $1.2M in unauthorised stock

Hayden AI, a San Francisco startup valued at $464 million, has sued co-founder and former CEO Chris Carson, alleging he stole 41GB of proprietary data before his September 2024 termination. The company claims Carson engaged in fraud including forged board signatures and unauthorised stock sales. According to the lawsuit, Carson secretly sold over $1.2 million in company stock without board approval to fund a multimillion-dollar Florida home and luxury purchases including a gold Bentley Continental. He allegedly downloaded his entire email file, containing proprietary information, days before launching rival firm EchoTwin AI. Hayden AI further alleges Carson fabricated his professional credentials, including a PhD from Waseda University. The complaint states that in 2007, Carson was actually operating a paintball equipment business in a Florida strip mall, not completing doctoral studies.

Webrazzi
Sep 24th, 2025
EchoTwin AI secures $8M funding round

EchoTwin AI, an Abu Dhabi-based company developing AI-driven urban infrastructure solutions, secured $8 million in seed funding led by Metis Ventures. Participants included Automotive Ventures, Supernova, Plug and Play, Higher Life Ventures, and Tesserakt Ventures. EchoTwin AI's platform helps municipalities manage cities more efficiently by transforming vehicle fleets into real-time AI-supported sensors, creating a digital twin of cities to proactively address infrastructure issues.