3D Technical Artist / Synthetic data (Junior / Co-op)
Create synthetic 3D scenes and training imagery in game engines to improve computer vision models for aerial threat detection. Develop a scalable, repeatable synthetic-data pipeline with accurate labels and metadata.
- Hybrid
- Toronto, ON
- Posted Aug 12, 2026
- Apply by Sep 11, 2026
- 1 position
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Job summary
Synthetic Data / 3D Technical Artist (Junior / Co-op) SageMesh Inc. · Toronto, ON · Hybrid This posting is to build our founding-team talent pool. It is not an active vacancy. We're lining up candidates ahead of hiring in 2026, which is conditional on our current funding decisions (expected around September 2026). Applying now puts you first in line for a role once hiring opens, and we'll reach out as positions are confirmed. Who we are Small, cheap drones now slip past radar and RF sensors, and the threat is growing faster than the systems built to stop it. SageMesh builds autonomous, off-grid sensor networks that detect, classify, and track these aerial threats. The AI behind them is only as good as the data it learns from, and some of the most important cases are rare, dangerous, or impossible to film in the real world, so we build them in software. We're a founder-led Toronto startup, and this is an early, hands-on role with room to grow. Why this role matters You'll create the training imagery that teaches our vision models to recognize targets and conditions they'd almost never see in real footage. In your first few months you'll stand up a synthetic-scene pipeline that measurably improves what our models can detect. You'll work directly with our Computer-Vision engineer, who tells you what the models are missing, and you turn that into usable, labelled data. It's a rare chance to see your work feed a real AI system and a real defence product. What you'll work on Synthetic scenes built and rendered in a game engine (Unreal or Unity) to expand our vision training datasets. 3D models, textures, and environments, staged under varied lighting, weather, angles, and backgrounds. Large batches of rendered images with accurate, automatically-produced labels and metadata. Fast iteration with the Computer-Vision engineer to fill specific gaps in model performance. A repeatable synthetic-data pipeline that scales without manual rework. What you bring Hands-on experience with a game engine (Unreal or Unity) and/or 3D modelling tools (Blender, Maya, 3ds Max, or similar). A good eye for visual realism: lighting, materials, composition, and variety. Organized, iterative work habits and well-labelled output. Eagerness to learn and take on responsibility. Recent grads and co-op students are genuinely welcome. Nice to have Interest in computer vision or AI, even if you haven't worked in it directly. Version control (Git) and asset-management workflows. Scripting (Python, Blueprints, or C#) to automate scene generation and rendering. Procedural generation, domain randomization, or synthetic data for machine learning. How we work We're a small team that moves fast and wears many hats, and we hire for ability over credentials: what you can make matters more than your résumé. It's hybrid: in-person collaboration in Toronto plus remote-friendly focus time for asset and render work. We ask for flexibility around project milestones and give it back; we care about the quality of your output, not hours logged. This is a genuine on-ramp: you'll be mentored, you'll link what you're learning to real work, and there's a path to a larger role as we grow. Compensation & growth Competitive junior or co-op compensation commensurate with experience. Salary Range: $35,000 – $65,000 per year. You'll get mentorship, real ownership of your pipeline, and a clear path to grow with the company. As noted above, start timing depends on funding and is targeted for 2026. Eligibility Because we work on Canadian defence programs, some work and data are access-controlled. Depending on the data you handle, this role may require eligibility for a Canadian government security assessment. We're happy to talk specifics with candidates. How to apply Send your résumé and a portfolio or demo reel to [email protected]. So we know you read this far, point us to something you modelled or rendered that you're proud of, and tell us what you'd do differently now. AI disclosure: we may use AI-assisted tools to help screen and organize applications. Our team reviews candidates before any interview or hiring decision. SageMesh is an equal-opportunity employer. We're building a diverse and inclusive team and welcome applicants of every background, including neurodivergent candidates, and people who don't meet every bullet above. Need an accommodation during hiring? Just ask, and we're glad to help.
What you’ll do
Create synthetic 3D scenes and training imagery in game engines to improve computer vision models for aerial threat detection. Develop a scalable, repeatable synthetic-data pipeline with accurate labels and metadata.
Requirements
Requires hands-on experience with game engines and 3D modeling tools, with a strong eye for visual realism. Candidates should be organized and eager to learn, with scripting and version control skills being a plus.
Benefits
• Mentorship • Ownership of pipeline
Listed skills
- PythonPreferred
- C++Preferred
- GitPreferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Unreal Engine
- Unity
- 3D Modelling
- Blender
- Maya
- 3ds Max
- Visual Realism
- Synthetic Data Generation
- Python
- Blueprints
- C#
- Git
- Procedural Generation
- Domain Randomization
- Computer Vision
Job areas
- Art & Design
- Technology
- Software
- Creative & Media
- Engineering
Additional details
- Minimum experience
- 0+ years
- Apply by
- Sep 11, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Entry level
- Application method
- Direct apply is available
