Software Engineer - Computer Vision

Ecopia.AI; Toronto; Hybrid; CAD 125,000 - 150,000; Full time

Job summary

A leading AI company is seeking a talented engineer for their Toronto office to develop deep learning algorithms for 3D built environments. You will work closely with experts in computer vision, with your contributions directly impacting innovative applications. Required skills include strong programming in C/C++ and Python, along with experience in machine learning and 3D applications. This permanent, full-time position offers a competitive salary and the flexibility of a hybrid remote working environment.

Benefits

Highly competitive salary

Annual salary increases

Bonuses

Flexible hybrid work environment

Qualifications

• Strong programming experience in C / C++ / Python.
• Research experience in machine learning and/or computer vision and/or 3D applications.
• Hands-on experience with semantic segmentation or 3D reconstruction.

Responsibilities

• Develop deep learning algorithms and build software systems for 3D built environments.
• Collaborate with the product team to transfer research into real-world applications.

Skills

C/C++

Python

Machine Learning

Computer Vision

3D Applications

Education

Master's or Ph.D. in Computer Science or related field

Job description

Ecopia AI’s mission is to create a digital twin of the Earth. Billions of geospatial images are captured every day by satellites, airplanes, vehicles, and personal devices. Ecopia leverages AI to convert high‑resolution images of our earth into high‑definition (HD) Vector Maps. These maps form a digital representation of reality and are embedded into critical decision‑making applications, offering unique insight at scale. Ecopia’s HD Vector Maps empower a wide range of applications such as smart cities, insurance, real estate, retail, manufacturing, utilities, logistics, autonomous driving, and augmented reality (AR).

We’re seeking a passionate, talented engineer to join us at our Toronto office. You will have the incredible experience of working alongside our computer vision and engineering experts. Your work will have a direct impact on our end products, which empower various real‑world applications on a scale never thought possible. The position is permanent, full‑time and will have a highly competitive salary, annual salary increases and bonuses.

We are looking for talented self‑starting engineers who enjoy diving into a subject and getting their hands dirty. With Ecopia’s flexible hybrid remote working environment, it’s your choice to work from home and/or our office, located in the beautiful MaRS Discovery District building at 101 College Street in Toronto. Come join us on the journey to map the world!

Key Responsibilities

• Develop deep learning algorithms and build software systems to automatically reconstruct 3D built environments, interpret and understand 3D contents from geospatial image data captured by satellites, airplanes, drones, vehicles, and smartphones at a country‑scale
• Collaborate with the product team to transfer research into products that empower various real‑world business applications

Qualifications

• Master's or Ph.D. in Computer Science or related field, or equivalent experience
• Strong programming experience in C / C++ / Python
• Deep understanding of algorithms and data structures
• Research experience in machine learning and/or computer vision and/or 3D applications
• Deep understanding of multiview geometry and 3D computer vision
• Hands‑on experience with semantic segmentation, and/or 3D reconstruction and generation, and/or simultaneous localization and mapping (SLAM)
• Publications at top venues, e.g. CVPR, ICCV, ECCV, ICML, NeurIPS, ICLR, … are a plus

Commitment to Diversity and Inclusion

Ecopia is committed to fostering a diverse and inclusive working environment. We welcome applications from qualified candidates of all backgrounds, regardless of age, physical ability, gender, race, religion, or sexual orientation. We will provide any requested accommodation to candidates with disabilities throughout the recruitment process.