Computer Vision Engineer

An innovative, highly advanced deep-tech computer vision startup founded by elite technological veterans. The company engineers a pioneering, production-grade automated inspection platform powered by state-of-the-art Deep Learning models.

By blending complex Computer Vision architectures with advanced Signal Processing techniques over performance-critical MLOps infrastructure, their technology automates the high-precision detection of intricate structural and surface anomalies in real time.

Operating a highly professional R&D center, the company is located in the Center region and offers a hybrid work model with 2 days of remote work per week.

Position Overview-

• Senior Computer Vision & Deep Learning Researcher joining an elite algorithmic division to drive advanced applied research and production engineering.
• Taking comprehensive ownership over the formulation and training of next-generation models across Image Understanding, Segmentation, Classification, Multimodal Fusion, and Hyperspectral Imaging.
• Operating in a high-impact split focused 70% on core algorithmic research and exploratory architecture design, and 30% on hardening, profiling, and benchmarking production models.
• Bridging academic-level research with robust practical application building high-throughput training infrastructures, meeting critical development milestones, and systematically documenting algorithmic experimental outcomes.

Requirements-

• M.Sc. or Ph.D. in Computer Science, Data Science, Electrical Engineering, Physics, or a highly equivalent quantitative discipline from a leading university (Mandatory).
• 5+ years of proven professional experience as a Computer Vision / Deep Learning Researcher inside product-centric or advanced R&D organizations (Mandatory).
• Proven track record in researching, designing, and training complex Deep Learning and Machine Learning architectures (Mandatory).
• Deep, production-grade mastery of enterprise deep learning frameworks, specifically PyTorch, PyTorch Lightning, or TensorFlow (Mandatory).
• Hands-on technical background or research exposure to Digital Signal Processing (DSP) or Signal Intelligence is a highly valuable asset.
• Prior domain experience operating within Medical Imaging, Biomedical Engineering, or advanced clinical diagnostics ecosystems is a significant advantage.

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