panoptyc
[https://app.ashbyhq.com/api/images/user-content/d79356cb-21b1-41b5-8e25-ceef94f4456f/b9bdb704-affe-499c-9c52-2fac490c879a/Screenshot%202025-10-13%20at%205.05.10%20PM.png] COMPUTER VISION ENGINEER Panoptyc is seeking an exceptional Senior Computer Vision Engineer to architect and train cutting-edge models for retail object recognition and drive our edge deployment strategy.
You'll be joining our awesome team of hardware, full-stack and CV engineers developing our next generation computer vision capabilities, building and optimizing models that power real-world retail applications. This role demands someone who can move seamlessly from training custom YOLO architectures to deploying optimized models on edge devices - and from fine-tuning open-source VLMs to building VLA pipelines that reason about and act on what they see.
- Model Development: Design, train, and iterate on custom object detection models specifically tuned for retail environments, inventory tracking, and product recognition - VLM & VLA Integration: Fine-tune and deploy open-source vision-language models (LLaVA, Qwen-VL, InternVL, PaliGemma, etc.) for product understanding, zero-shot classification, and scene reasoning; build vision-language-action pipelines that translate visual understanding into downstream decisions - Edge Optimization: Take state-of-the-art models and make them blazingly fast for edge deployment through quantization, pruning, and architectural optimization - Dataset Engineering: Build robust data pipelines and annotation workflows to continuously improve model performance on diverse retail scenarios - Research & Innovation: Stay ahead of the curve on CV and VLM research, prototype new architectures, and determine what's actually production-ready versus academic noise - Technical Leadership: Mentor engineers, establish best practices for model development, and drive technical decisions around our CV infrastructure REQUIRED EXPERIENCE - 4+ years of hands-on computer vision engineering, with a proven track record of shipping models to production - Deep expertise with YOLO and YOLO-E architectures - you've trained them, tuned them, and know their quirks intimately - Hands-on experience with open-source VLMs (LLaVA, Qwen-VL, InternVL, PaliGemma, or similar) - fine-tuning, evaluation, and production deployment - Familiarity with VLA frameworks and applying vision-language-action models to real-world perception and decision tasks - Edge deployment mastery - experience with TensorRT, ONNX Runtime, or similar frameworks for optimizing models for constrained devices, including quantized VLMs - Strong software engineering fundamentals - clean code, version control, CI/CD for ML, and the ability to build maintainable systems - Production ML experience - you understand the difference between a Jupyter notebook and a production-grade ML system PREFERRED QUALIFICATIONS - Experience developing solutions deployed to the NVIDIA Jetson family of products - Experience with retail, inventory management, or similar product-focused CV applications - Background with PyTorch and modern training frameworks (Transformers, LitGPT, Unsloth, etc.) - Experience running VLM inference efficiently (vLLM, llama.cpp, SGLang, or similar) - Familiarity with synthetic data generation and data augmentation techniques - Knowledge of model versioning and experiment tracking (MLflow, Weights & Biases, etc.) - Publications or open-source contributions in computer vision or multimodal AI - Experience with AWS: EC2, ECS, Fargate, S3, Bedrock, SageMaker, etc. TECHNICAL STACK While we value expertise over specific tools, you'll likely work with: PyTorch, YOLO variants, open-source VLMs, TensorRT, ONNX, vLLM, Docker, Kubernetes, and various MLOps tooling. Location: Remote Panoptyc is building the future of retail intelligence. If you're ready to tackle hard CV and multimodal problems at scale, we want to hear from you.