Senior Computer Vision Engineer

This is a fully remote position, open to applicants in Philippines.

📋 Description

• Design, train, and refine custom object detection models specifically tailored for retail settings, inventory management, and product identification.

• Fine-tune and implement open-source vision-language models (LLaVA, Qwen-VL, InternVL, PaliGemma, etc.) for enhanced product comprehension, zero-shot classification, and scene analysis.

• Develop vision-language-action pipelines that convert visual insights into actionable decisions.

• Optimize cutting-edge models for edge deployment through techniques such as quantization, pruning, and architectural refinement.

• Create resilient data pipelines and annotation workflows to consistently elevate model performance across diverse retail scenarios.

• Remain at the forefront of computer vision and vision-language model research, prototype innovative architectures, and assess production readiness.

• Guide engineers, establish best practices for model development, and influence technical decisions concerning our computer vision infrastructure.

⛳️ Requirements

• Over 3 years of practical experience in computer vision engineering, with a proven history of deploying models into production.

• Profound knowledge of YOLO and YOLO-E architectures - you've trained them, optimized them, and are well-acquainted with their nuances.

• Practical experience with open-source vision-language models (LLaVA, Qwen-VL, InternVL, PaliGemma, or similar) - including fine-tuning, assessment, and production deployment.

• Understanding of vision-language-action frameworks and their application to real-world perception and decision-making challenges.

• Mastery in edge deployment - experience with TensorRT, ONNX Runtime, or comparable frameworks for optimizing models for resource-constrained devices, including quantized vision-language models.

• Solid software engineering principles - including clean code practices, version control, CI/CD for machine learning, and the ability to develop maintainable systems.

• Experience in production machine learning - you recognize the distinctions between a Jupyter notebook and a production-level ML system.

🏝️ Benefits

• Competitive salary

• Flexible working hours

• Professional development opportunities