Rodion Shyshkin Email & Phone Number

Experienced Machine Learning Engineer (4+ years in Computer Vision and Machine Vision) with a solid foundation in AI technologies and a commitment to developing innovative solutions. Proven track record in applying machine learning techniques to real-world problems, focusing on enhancing visual recognition and processing capabilities.Key strengths:• Computer Vision Expertise: Skilled in designing and implementing algorithms for real-time object detection and tracking, image classification and segmentation, visual data analysis, leveraging PyTorch, TensorFlow, Keras and OpenCV frameworks.• Cloud and Edge Deployment: Experienced in deploying machine learning models both on cloud platforms, specifically Amazon Web Services and Google Cloud Platform, and in edge environments, ensuring optimized performance and scalability across various applications using TFLite and specific tools.• Programming Proficiency: Experienced in Python for ML applications, with foundational knowledge in C++ for performance-critical tasks.• Project Leadership: Proven ability to lead teams and manage projects from initial concept to production release. Skilled in team formation and building effective workflows to ensure successful project execution. I excel in client interaction and effective communication, fostering collaboration and understanding between technical teams and stakeholders.• Diverse Technical Experience: Versatile background in backend and embedded systems, with some experience in frontend development, building web servers, training classic ML models and generating synthetic datasets for object detection applications.• Continuous Learning: Committed to staying updated with emerging technologies and methodologies in the field of machine learning, always seeking to enhance skills and knowledge.Tech-stack I used to work with:• Languages: Python, C/C++• Frameworks: PyTorch, TensorFlow, TensorFlow Lite, TensorFlow Lite Micro, OpenCV, Flask, Django• Clouds: AWS, GCP• Edge platforms: Raspberry Pi, Orange Pi, NVIDIA Jetson Nano, Google Coral, custom NPU-based boards.• ML Tools: MLflow, Weights & Biases (W&B), Neptune, Pytest, Great Expectations• Monitoring and Deployment: Grafana, Seldon, Kubeflow, KServe, Kalib, Amazon SageMaker• Databases: MySQL, SQLiteML, Machine Learning, CV, Computer Vision, Machine Vision, AI, Image Processing, Deep Learning, Neural Networks, Object Detection, Object Tracking, Segmentation, Classification, Model Deployment, Cloud Computing, Visual Recognition, Python, C++ Programming, Algorithm, Edge AI, Continuous Learning, CI/CD.