AI Engineer
il y a 5 jours
As an AI Engineer, you'll join our core Deep Learning team and contribute across the pretraining and fine-tuning stacks, driving product-ready improvements in medical AI models.
You'll work in a fast-paced, research-meets-product environment with high standards for scientific rigor and production-grade code.
What You'll Work OnPretraining (images ± text)Design and scale visual representations from large de-identified 2D/3D datasets
Objectives: masked image modeling, self-supervised/contrastive (MAE/DINO), vision–language alignment (CLIP-style)
Modalities: X-ray, CT, occasional MRI; 2D/3D ViTs and UNet-style decoders
Infra: high-throughput DICOM loaders, augmentations, mixed-precision, distributed training
Evaluation: transfer tasks, label efficiency, robustness across sites/vendors
Adapt and optimize models powering Gleamer's clinical features
Tasks: detection, segmentation, follow-up (temporal matching, tracking), calibration
Vision–Language Models (VLMs): fine-tune encoders + LLMs for report generation and extraction
Techniques: SFT, LoRA/PEFT, distillation, quantization
Deployment: Docker, ONNX, TensorRT, batching, inference optimization
Evaluation: AUROC/FROC, Dice, ECE calibration, factuality vs labels, clinician review
PyCharm, Windsurf, GitHub Copilot
PyTorch (Lightning), MONAI, Hugging Face, timm
ClearML, DVC
Multi-GPU training, ONNX/TensorRT for deployment
Clean, production-level code: type annotations, comprehensive tests, documentation
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