Build multimodal intelligence for Palona’s physical-world AI using visual grounding, temporal reasoning, and structured prediction from video.
This AI Research Engineer role focuses on vision-language modeling and computer vision for busy restaurant environments. You will develop approaches for changing scenes, incomplete information, and difficult visual conditions. The work spans research questions, model adaptation, dataset creation, evaluation, and production collaboration.

Key Responsibilities





Develop VLM approaches for events and activities across videoFine-tune models for grounding and structured predictionCreate representative image and video datasetsBuild benchmarks for temporal consistency and perception qualityTranslate research advances into practical product capabilitiesRequirements:
Three-plus years of applied or research experienceDepth in video understanding, grounding, tracking, or multimodal reasoningHands-on model training beyond basic API integrationStrong Python and PyTorch or equivalent framework experienceExperience analyzing failures and using ablationsBring research depth in multimodal learning, visual grounding, and video understanding to Palona’s restaurant-focused AI products.
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📌 Multimodal Vision Research Engineer (Winnipeg)
🏢 Palona AI
📍 Winnipeg