AI Researcher

• Train, fine-tune, and evaluate deep learning models and Vision-Language Models for fine-grained retail scene understanding and product recognition
• Design and implement features combining computer vision and computer graphics for interactive Augmented Reality workflows
• Profile, optimize, and quantize algorithms for latency- and memory-constrained edge hardware
• Work with multimodal LLMs, VLMs, and advanced prompting techniques to create automated recognition tools
• Enhance and optimize algorithms for efficiency, robustness across varying store conditions, and global scalability
• Benchmark, test, and evaluate ML models against real-world retail datasets for accuracy and reliability
• Develop visual and multimodal architectures and ship production-grade solutions deployed across thousands of stores globally

• 3+ years of hands-on experience developing and deploying Machine Learning and Deep Learning models in production or applied R&D environments
• Strong understanding of classical and modern computer vision
• Linear algebra, calculus, and mathematical foundations required for 2D/3D geometry and spatial graphics
• Practical experience working with modern LLMs/VLMs and prompt engineering techniques
• High proficiency in Python and deep learning frameworks; Keras, TensorFlow, and JAX preferred
• Strong problem-solving ability to adapt complex academic/R&D concepts into robust production features
• Comfortable collaborating daily in English, written and verbal, in a distributed international team
• Experience with AR frameworks such as ARKit or ARCore, or computer graphics pipelines such as OpenGL, WebGL, or game engines
• Familiarity with optimizing models for edge devices and inference runtimes such as CoreML or TFLite
• Prior experience in retail analytics, planogram compliance, or fine-grained object recognition

• Full remote or hybrid work from the cozy office in Krakow
• Option to enroll in a medical package on preferential terms
• Subsidized English language courses
• Company-provided work equipment
• Opportunities for internal growth and career development
• Access to internal learning resources