Entry Level Python Game Developer Jobs in Toronto, ON

Wand makes gaming magical. Through game customization and guidance, we build tools that helps players have more fun in their favorite games.

Our platform works across thousands of PC games, ensuring that great games are accessible to everyone, regardless of time constraints, skill level, or accessibility needs. We want to build the future of game assistance, and we're hoping you'll join us.

The gaming industry is undergoing a massive transition. While the market has never been bigger, players are drowning in an ever-expanding sea of content, yet abandoning games at record rates due to pacing, friction, or simply getting stuck. When they look for help, they are forced into a broken paradigm: alt-tabbing out of their game to wade through ad-heavy media sites, spoiler-filled wikis, or tedious 15-minute YouTube walkthroughs.

Wand is building the augmentation and intelligence layer to fix this. Our technology reads game state in real time, powering a unified ecosystem across desktop, web, and native game overlays. Interactive maps are one of the surfaces players reach for most, and the ones that matter are ready the day a game launches — not months later when a community wiki has caught up. Over 40 million gamers have already found us, largely through word of mouth, because we solve this fundamental problem.

We’re hiring a Reverse Engineer to own the asset-extraction pipeline that feeds Wand Maps, Wikis, and Game Assistant. You’ll partner closely with our engineering team — the same engineers who build the extraction tooling alongside you and the front-end map experience players see in the app. The shape of the role is part data extraction, part tooling: each new game comes with its own quirks, and your job is to get the location data, world geometry, and asset references out cleanly so the rest of the team can turn them into a usable map.

This is an individual contributor role focused on the steady cadence of new game releases. You’ll work with the open-source extraction ecosystem (CUE4Parse, FModel, AssetRipper, etc.), and lean heavily on AI coding tools to build the scripts and small tools that automate the repetitive parts so the next game is faster than the last.

• Work with game archives, asset containers, and serialized data to pull out the locations, world geometry, item and NPC placements, and asset references that maps depend on.

• Convert proprietary formats into structured, open formats the rest of the team can consume — JSON, glTF, PNG, and similar.

• Get familiar with each new game’s data layout quickly. Different engines, different structures, different gotchas; that’s the job.

• Write scripts and small tools (Python, C#, whatever fits) that automate the repetitive parts of extraction.

• Reach for the open-source ecosystem when it fits — CUE4Parse, FModel, AssetRipper, UnrealPak — and stitch them together into a pipeline that works for our needs.

• Lean on AI coding tools heavily. Most of this work is moving fast across unfamiliar code and file formats; that’s exactly where AI tooling shines.

• Every game ships in a different shape. Aim to make the next game take a fraction of the time the last one did.
  

• Hands-on experience extracting data from game files using tools like CUE4Parse, FModel, AssetRipper, UnrealPak, or comparable. You don’t need to have written one of these tools — you need to know how to use them and where they fall short.

• Comfortable picking up a new game’s asset structure without a roadmap. Documentation is usually thin to nonexistent; you learn by reading code, watching how other extractors work, and running experiments.

• A solid mental model of how game assets are laid out — meshes, textures, transforms, world hierarchies, level streaming, common serialization patterns.

• Comfortable scripting in Python or C# (or both). You’re not building deep systems; you’re stitching together the right tools and automating what’s repetitive.

• Fluent with AI coding tools — Claude Code, Cursor, or equivalent. You use them day-to-day, and you’ve felt the speedup when you’re working through an unfamiliar codebase or file format. This is a must, not a nice-to-have.

• Self-managing. You can pick up a new title from the release calendar and drive the extraction to a clean handoff without daily check-ins.

• Strong written communication. The notes you leave matter as much as the data you pull.

• Available during US/Eastern hours.
  

• Unreal Engine ecosystem familiarity. UE games are a meaningful chunk of the target list.

• Unity asset pipeline at depth (AssetBundles, addressables, IL2CPP).

• Texture formats (DDS, KTX, BCn) and 3D formats (glTF, FBX).

• Experience with serialized data — Protobuf, FlatBuffers, custom packed structs.

• Contributions to the modding scene, dataminer community, or any open-source extraction tooling. Links welcome.

• PC gamer. You play the stuff our players play.
  

• Competitive compensation.

• Fully remote work arrangement.

• The chance to be the first person to map a brand-new game’s world for an audience of 40M+ players who will actually use it.

• A team of people who genuinely love games, move incredibly fast, and care deeply about what they build.
  

Please submit your resume.

Join us in creating the ultimate PC gaming companion!

Wand is an equal opportunity employer committed to building a diverse and inclusive team. We welcome applications from all qualified candidates regardless of background.