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.

Experience with NVIDIA Jetson devices, synthetic data generation, data augmentation, MLflow, Weights & Biases, or AWS AI services is considered a differentiator.

Background in retail technology, inventory management, or product-focused computer vision applications is a plus.

Benefits:

Fully remote work environment.

Opportunity to work on cutting-edge computer vision and multimodal AI projects.

Collaboration with multidisciplinary teams focused on solving complex technical challenges.

Exposure to modern AI technologies, including vision-language models, edge AI, and MLOps practices.

Opportunity to contribute to scalable solutions with real-world business impact.

Professional growth through technical challenges and innovation-driven projects.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1