• Design and integrate LLM-powered features, including conversational interfaces, AI agents, structured generation, and retrieval-augmented systems. • Build and maintain ML pipelines for prediction, anomaly detection, classification, and time-series analysis. • Develop backend APIs and services connecting data sources, models, and client-facing applications. • Work with structured and unstructured data across relational databases, data warehouses, and external APIs. • Optimize model performance and scalability for production environments, including monitoring and fine-tuning. • Collaborate with cross-functional teams (product, data, and engineering) to translate business requirements into technical solutions. • Ensure code quality, documentation, and best practices for deployment, testing, and maintainability.

• Designing and developing high-performance UIs using Qt/QML and C++. • Using AI agents and tools to conduct rapid technical research, automate repetitive coding tasks, and optimize the development lifecycle. • Leveraging AI to assist in UI/UX prototyping and "AI-first" problem-solving. • Guiding the team on how to effectively (and safely) integrate AI tools into their daily work. • Gathering requirements and translating them into modern, scalable architectures.

• Develop, train, and deploy machine learning models to support and optimize payment operations • Work closely with a Product Analyst to translate business requirements into ML solutions • Build and improve models for transaction scoring, anomaly detection, fraud detection, and payment routing optimization • Automate decision-making processes using machine learning approaches • Prepare and process data, including feature engineering and building data pipelines • Monitor model performance and continuously improve model quality and reliability • Participate in the design and development of ML solution architecture

• Develop cutting-edge machine learning and deep learning solutions using multimodal sensor data from vehicles and road environments. • Design and build scalable software pipelines for computer vision applications, including: - Data curation and preprocessing - Model training and evaluation - Testing and validation - Deployment and monitoring • Create innovative solutions for complex traffic and mobility-related problems. • Design and implement efficient, low-cost approaches for video-based inference. • Train, fine-tune, and optimize machine learning and deep learning models for real-world performance and scalability. • Collaborate with cross-functional teams to contribute to the development of advanced, production-ready systems. • Stay up to date with emerging technologies, research, and open-source tools, and apply them to improve system performance and capabilities.