Sr. Computer Vision Engineer

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Computer Vision Engineer based in Brazil.** We are looking for a Senior Computer Vision Engineer to design, develop, and deploy advanced AI models that power next-generation retail intelligence solutions. The role focuses on building production-ready computer vision systems, from model training and optimization to edge deployment. You will work on challenging problems involving object recognition, multimodal AI, and vision-language-action systems. This position offers the opportunity to contribute to innovative applications that transform real-world retail operations through artificial intelligence. The ideal candidate will combine deep technical expertise with strong engineering practices and a passion for applied machine learning. You will collaborate with multidisciplinary teams to develop scalable, high-performance AI solutions from research concepts to production environments. ### Accountabilities: The Senior Computer Vision Engineer will be responsible for architecting, training, optimizing, and deploying advanced computer vision models while driving technical innovation and best practices across AI development initiatives. - Design, train, evaluate, and iterate on custom computer vision models for retail object recognition, inventory tracking, and product understanding. - Develop and optimize YOLO-based architectures, applying expertise in training, tuning, and production deployment. - Fine-tune and deploy open-source vision-language models (VLMs) for tasks such as product understanding, zero-shot classification, and scene reasoning. - Build vision-language-action (VLA) pipelines that connect visual perception with downstream decisions and automated actions. - Optimize AI models for edge deployment through techniques such as quantization, pruning, and architectural improvements. - Develop robust dataset pipelines, annotation workflows, and data strategies to continuously improve model performance. - Research emerging computer vision and multimodal AI technologies, identifying opportunities for practical production adoption. - Establish best practices for machine learning development, model deployment, and AI infrastructure. - Mentor engineers and contribute to technical decisions related to computer vision systems and workflows. - Ensure ML solutions are production-ready, maintainable, and scalable beyond experimental environments. ## Requirements: The ideal candidate should have strong experience in computer vision engineering, machine learning production systems, and AI model optimization, with the ability to transform advanced research concepts into reliable real-world applications. - 3+ years of hands-on experience in computer vision engineering, with proven experience deploying models into production environments. - Deep expertise with YOLO and YOLO-E architectures, including training, optimization, and performance tuning. - Practical experience with open-source vision-language models such as LLaVA, Qwen-VL, InternVL, PaliGemma, or similar technologies. - Experience fine-tuning, evaluating, and deploying multimodal AI models in production scenarios. - Familiarity with vision-language-action frameworks and their application to perception and decision-making tasks. - Strong experience with edge AI optimization using technologies such as TensorRT, ONNX Runtime, or similar frameworks. - Knowledge of model quantization techniques and deployment on resource-constrained devices. - Strong software engineering fundamentals, including clean code practices, version control, CI/CD, and maintainable ML systems. - Experience building production machine learning pipelines beyond experimentation or research notebooks. - Experience with PyTorch and modern AI training frameworks is preferred. - Familiarity with tools such as Transformers, LitGPT, Unsloth, vLLM, llama.cpp, or SGLang is a plus. - Exp…