Work at the intersection of plant cell biology and applied AI to build, productionize, and maintain computer vision pipelines that accelerate Doubled Haploid (DH) breeding in Biotechnology. The contractor will contribute to end‑to‑end imaging and analytics—from microscopy microspore detection to macroscopic structure assessment and plantlet characterization—supporting decisions that reduce cycle time and cost in DH programs. Solutions will be developed primarily in Python, integrated with our repositories and workflow tooling, and aligned with Biotech strategy initiatives Must Have:4–6 years hands‑on in computer vision with Python (PyTorch/TensorFlow), including detection/segmentation/classification for scientific or industrial imaging.Proven ability to productionize models: Git/GitLab, code reviews, CICD basics, experiment tracking (MLFlow or equivalent), reproducible data/experiments, and clear documentation. Experience with microscopy image processing, multi‑page TIFFs, z‑stacks, autoscale/normalization, and image quality challenges. Familiarity with hyperspectral or multispectral imaging pipelines (preprocessing, dimensionality reduction, modeling) applied to plant or biological materials.Track record of measurable model performance reporting and communicating results via posters/presentations for technical audiences.  Nice‑to‑HaveVision Transformers (ViT) and modern YOLO workflows for microscopy/macroscopic tasks; comfort with infer tooling.Experience optimizing inference (e.g., torch.compile, mixed precision) and scaling batch workflows.Domain familiarity with Biotech breeding workflows.Collaboration with discovery and strategy teams; ability to work across biology, engineering, and data science groups.
