AI Research Engineer, Computer Vision & VLMs

Palona is building AI for the physical world, starting with restaurants. Understanding a busy restaurant means making sense of people, objects, activities, and events as they change over time, despite occlusion, changing lighting, varied camera views, and incomplete information.We are looking for an AI Research Engineer with a strong research background in computer vision and vision-language models (VLMs) to develop the visual intelligence behind Palona's products. You will work on image and video understanding, spatiotemporal reasoning, and multimodal models that connect visual observations to useful insights and actions in real restaurant environments.This role combines research depth with ownership of working systems. You will formulate research questions, build datasets, train and evaluate models, and partner with product and engineering to bring successful approaches into production. Researchers and engineers from autonomous driving, robotics, embodied AI, and related perception fields are especially encouraged to apply.What You'll OwnDevelop computer vision and VLM approaches for scene understanding, object detection and tracking, activity recognition, and understanding events across videoAdapt, fine-tune, and evaluate vision and vision-language models for visual grounding, temporal reasoning, and structured prediction grounded in observable evidenceDesign training and adaptation strategies, including supervised fine-tuning, representation learning, distillation, and domain adaptation, based on measurable product needsBuild representative image and video datasets, annotation workflows, and evaluation sets that capture difficult edge cases while protecting sensitive dataCreate rigorous experiments and benchmarks that measure perception quality, temporal consistency, hallucinations, robustness, latency, and cost across locations and operating conditionsDiagnose failures caused by occlusion, lighting changes, camera placement, rare events, and domain shift; use those findings to improve data and modelsPartner with infrastructure and product engineers to deploy efficient inference pipelines, with monitoring, quality gates, staged rollouts, and rollback pathsTranslate advances in computer vision, VLMs, and embodied AI into practical product capabilities, and communicate the evidence and tradeoffs behind your decisionsRaise research and engineering standards through reproducible experiments, thoughtful reviews, and clear documentationRequirements3+ years of research or applied development experience in computer vision, multimodal learning, or a closely related field; relevant graduate research counts toward this experienceA demonstrated research track record in computer vision or vision-language modeling, through publications, substantial research projects, open-source contributions, or research delivered in industryStrong foundations in deep learning, visual representation learning, and experimental design, with depth in areas such as video understanding, detection and tracking, visual grounding, or multimodal reasoningHands-on experience training, fine-tuning, or adapting computer vision models, and developing or evaluating VLMs beyond basic API integrationStrong Python skills and experience with PyTorch or an equivalent deep learning framework, along with modern training and evaluation toolingExperience building datasets, designing reliable evaluations, analyzing model failures, and using ablations to understand what drives improvementsStrong software engineering judgment and the ability to turn research code into reproducible, tested systems that other engineers can useAbility to connect modeling choices to product constraints including latency, cost, privacy, reliability, and user experienceComfort working through ambiguity and collaborating across research, engineering, and productEspecially relevant experienceA PhD or research-focused master's degree in computer vision, machine learning, robotics, or a related field, or equivalent research experienceIndustry research or engineering experience in autonomous driving, robotics, embodied AI, or other applications of perception in the physical worldPublications at venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, CoRL, ICRA, or RSSExperience with monocular video perception, spatial understanding, long-video reasoning, or learning from limited and noisy labelsExperience shipping vision models under real-time constraints, including model compression, distillation, quantization, or inference optimizationWhen applying, please include links to relevant publications, research projects, or code, and briefly describe your own contribution.BenefitsCompetitive salary and stock option planCompany-sponsored green card applications for strong candidates hired into U.S.-based roles, subject to eligibilityMedical, dental, vision, and retirement benefits as applicableFamily leave and short-term and long-term disability benefits as applicablePaid time off and company holidaysLearning and development support