Senior Computer Vision Engineer – Classical & Deep Learning (f/m/x)

Our requirements

• At least 5 years in computer vision engineering, with vision systems shipped to production — not just research prototypes
• Solid grounding in geometric vision: projective geometry, camera models, epipolar geometry, and 3D reconstruction fundamentals
• Hands-on deep learning experience: training and deploying CNN- and transformer-based models (e.g., YOLO family, Mask R-CNN, DETR, SAM) for real applications
• Strong Python and OpenCV skills; comfort with PyTorch and the surrounding ecosystem (torchvision, Albumentations, ONNX)
• Experience optimizing inference for constrained environments — latency budgets, embedded hardware, or high-throughput video
• The judgment to pick a homography over a transformer when the problem calls for it — and to defend that choice
• Ability to work autonomously while collaborating effectively with architects, engineers, and product teams
• Fluent English (both written and spoken)
• Fluent Polish required
• Residing in Poland required

Optional

• C++ skills for performance-critical pipelines and integration with existing vision systems
• Previous work with visual SLAM, sensor fusion (LiDAR, radar, IMU), or autonomous driving perception stacks
• Exposure to vision-language models (CLIP, Grounding DINO) and foundation-model-based labeling or zero-shot pipelines
• Experience deploying on NVIDIA Jetson, industrial cameras (GenICam/GigE), or cloud vision services on Azure, AWS, or GCP

Your responsibilities

• Design and implement vision systems combining classical and learning-based approaches — choosing the right method for the constraints of each problem
• Apply geometric computer vision in practice: camera calibration (intrinsic/extrinsic), stereo and multi-view geometry, feature detection and matching, pose estimation, structure-from-motion, and visual SLAM
• Build, train, and fine-tune deep learning models for object detection, semantic and instance segmentation, multi-object tracking, OCR, and anomaly detection using PyTorch
• Develop image processing pipelines with OpenCV and NumPy: filtering, morphology, thresholding, contour analysis, and color space operations
• Optimize models and pipelines for deployment: quantization, pruning, ONNX/TensorRT conversion, and real-time inference on edge devices and GPUs
• Own data quality end-to-end: dataset design, annotation strategy, augmentation, and systematic error analysis on real-world imagery
• Build evaluation frameworks that measure what matters in production — not just mAP on a benchmark, but failure modes under real conditions
• Collaborate with AI Architects and ML engineers to integrate vision components into larger systems, on-prem and in the cloud

About the project

What we offer

• AI Grant — Stop talking about AI and start building it. Our AI Grant gives you dedicated budget and resources to turn your wildest AI idea into a working project, backed by two paid weeks to focus on nothing else
• AI Center of Excellence — Work alongside specialists in agentic AI, sovereign AI, generative and discriminative AI. This isn’t a siloed team — it’s the people you’ll learn from and build with daily
• Your tools, your choice — Full access to AI-powered development tools including Claude, Cursor, and GitHub Copilot. Pick what works best for you
• Real project variety — From generative AI for legal document compliance, through agentic systems in manufacturing environments, to enterprise-scale AI platforms, computer vision, and autonomous driving. You won’t get bored
• Conference and speaking support — Want to attend conferences? We’ll back you. Want to speak at them? Even better — we’ll support you with dedicated preparation time and bonuses

Recruitment stages

• 1.
  Send your CV
• 2.
  Talk to us about your expectations
• 3.
  Learn more about our projects and choose the best
• 4.
  Start your adventure with Sii!

Sii Sp. z o.o.