We are looking for a visionary Lead Data Scientist to join a cutting-edge European project dedicated to revolutionizing energy efficiency within large-scale Edge computing ecosystems. If you are passionate about combining high-level AI with real-world environmental impact, this is your chance to lead the way.
Your primary goal will be to develop and implement AI/ML algorithms that optimize the energy efficiency of entire edge infrastructures—ranging from hardware and software to networking, IoT devices, and operational processes.
Sustainable Orchestration: Develop AI/ML models for dynamic energy optimization, focusing on workload scheduling, resource allocation, and load balancing for cloud-edge ecosystems.
Predictive Power Management: Leverage predictive algorithms to anticipate demand and adjust power consumption in real-time, ensuring maximum efficiency without compromising performance.
Innovative Research: Conduct research into state-of-the-art "Green AI" and energy-aware algorithms designed to function with minimal computational power.
Cross-Functional Collaboration: Work closely with sustainability experts, product managers, and engineering teams to integrate AI/ML solutions into the project’s broader energy-saving objectives.
Market Analysis: Evaluate emerging tools and products that support data collection and AI-driven sustainability orchestration.
Edge & Federated Learning: Implement advanced techniques to reduce large-scale data transmission, utilizing edge processing and federated learning to minimize the energy cost of data transfers.