Software Engineer (Applied ML & Computer Vision)

GroundedAI Inc.; Vancouver; Hybrid; CAD 90,000 - 120,000; Full time

Job summary

A technology firm specializing in AI solutions is seeking a Software Engineer to join their core product engineering team. This role will involve designing, implementing, and maintaining production systems, collaborating with multidisciplinary teams. Ideal candidates will have around 5 years of professional experience, strong software design fundamentals, and proficiency in Python. The position offers competitive compensation and flexible hybrid/remote work options.

Benefits

Competitive compensation

Flexible hybrid/remote work options

Support for learning and professional growth

Qualifications

• 5+ years of experience as a software engineer (backend, platform, or product).
• Proficiency in Python and experience with modern development workflows (Git, CI/CD).
• Experience deploying software in cloud infrastructure.

Responsibilities

• Design, implement, and maintain production software systems.
• Build backend services and pipelines for data processing.
• Collaborate with engineering teams to deliver end-to-end features.

Skills

Software design

Debugging

Testing

Code quality

API management

Data pipelines

Collaboration

Python

Tools

Docker

AWS

GCP

Azure

Job description

About GroundedAI

GroundedAI builds software systems that turn complex, real-world data into reliable insights. Our products operate in challenging, industrial environments where correctness, performance, and maintainability matter just as much as innovation.

We work at the intersection of software engineering, applied machine learning, and geospatial data. Our focus is on shipping robust systems, not prototypes or research demos.

Role Overview

We’re looking for a Software Engineer to join our core product engineering team. This role is ideal for someone with ~5 years of experience who enjoys building and owning production systems end-to-end, including services that incorporate machine learning and computer vision components.

You’ll collaborate with engineers across the stack to design, build, deploy, and operate software that includes ML-powered features while maintaining high standards for reliability, performance, and code quality.

This is a software engineering role first, with machine learning as an important (but not exclusive) part of the problem space.

What You’ll Do

• Design, implement, and maintain production software systems that power GroundedAI’s products
• Build backend services and pipelines that support data processing, model training, and inference
• Integrate computer vision and ML components into user-facing applications
• Improve system performance, reliability, and observability in production environments
• Collaborate with product, ML, and frontend engineers to deliver end-to-end features
• Debug and resolve complex production issues across services, data, and infrastructure
• Contribute to technical design discussions and help evolve engineering best practices

What We’re Looking For

Required

• ~5 years of professional experience as a software engineer (backend, platform, or product)
• Strong fundamentals in software design, debugging, testing, and code quality
• Experience building and operating production systems used by real users
• Proficiency in Python and experience with modern development workflows (Git, CI/CD)
• Comfort working with APIs, services, and data pipelines
• Experience deploying software using Docker and cloud infrastructure (AWS, GCP, or Azure)
• Ability to collaborate across disciplines and take ownership of technical problems

ML / CV Experience (Nice to Have, Not Required)

• Experience working with ML-backed or data-driven systems in production
• Familiarity with computer vision concepts such as image segmentation, feature extraction, or object detection
• Exposure to ML frameworks like PyTorch or TensorFlow
• Experience working with large datasets, geospatial data, or 3D / point-cloud data

Why GroundedAI

• Work on real-world systems with meaningful constraints and impact
• Strong engineering culture focused on ownership, pragmatism, and quality
• Opportunity to influence core architecture and technical direction
• Competitive compensation and benefits
• Flexible hybrid / remote work options
• Support for learning, experimentation, and professional growth