What you will be doing
Design and build agent systems that plan and execute multi-step tasks across imagery, geometry, and documents.
Own the context layer. Build retrieval and grounding over a spatially and temporally indexed site record so an agent gets the evidence a question actually needs.
Design the tool surface: the primitives an agent calls to locate a component, compare two captures, read a region of a drawing, or query a BIM element.
Build evaluations for tasks where ground truth is ambiguous, then use them to make honest calls about what is ready and what is not.
Choose the right model for each step. Frontier API, open-weight model, fine-tuned small model, or classical CV, weighed against cost, latency, and accuracy at production volume.
Make outputs traceable. Every claim should point back to the pixel, sheet, or spec section that supports it.
Prototype quickly, kill what doesn't work, and partner with platform engineers to ship what does.
What we are looking for
M.S./Ph.D. in a related field or equivalent industry experience.
5+ years building ML systems, including at least one LLM or VLM-based system you took to production and kept running. We will ask what broke.
Experience designing evaluations from scratch where ground truth is expensive, sparse, or contested.
Strong multimodal fluency: vision-language models, embeddings and retrieval, context design, and fine-tuning when it earns its cost.
Solid engineering. Python, async orchestration, tracing and cost instrumentation. You build your own harness.
Comfort with spatial data. You don't need SLAM depth, but coordinate frames, camera poses, and projections shouldn't slow you down.
Judgment about what is worth automating, and the willingness to say when the answer is nothing yet.
Nice to have
Post-training or reinforcement learning on agent trajectories.
Document understanding over technical drawings, specifications, or other structured PDFs.
Sensor streams beyond core imagery, such as mobile capture, wearables, or field audio.
Experience in construction, robotics, geospatial, or another domain where models meet the physical world.
Base Salary: $181,000 - $230,000 CAD
OpenSpace welcomes employees from varied backgrounds and walks of life, and it’s reflected in our diverse community. OpenSpace is proud to be an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.