MUST-HAVE SKILLS

• 6+ years of ML or CV engineering, including 3+ years building production-grade vision systems.
• Strong knowledge of CV tasks and architectures (classification, detection, segmentation).
• Proficient in PyTorch, TorchVision, Albumentations, and modern CV frameworks.
• Proven experience training and tuning models on real-world datasets.
• Skilled in production deployment (Docker, TorchServe, ONNX Runtime, BentoML, Kubernetes).
• Strong software engineering foundation: clean Python, Git workflows, testable architecture.
• Experience with ML orchestration tools (Airflow, Prefect, Dagster).
• Familiarity with monitoring and alerting systems for ML models.

ABOUT THE ROLE

We’re looking for a hands-on ML CV Engineer to lead the development and deployment of robust, production-grade computer vision pipelines. In this role, you’ll own the full lifecycle of CV models - from data curation and preprocessing, through model training and evaluation, to deployment, monitoring, and automated retraining.
You’ll play a critical role in ensuring our vision systems remain accurate, responsive, and scalable under real-world conditions. Your work will directly impact applications involving image classification, object detection, segmentation, and other visual inference tasks.
This is a role for someone who thrives in full-stack ML development, combining deep modeling expertise with disciplined engineering and deployment practices.