We are seeking a Lead Data Scientist working in a cutting-edge European project aimed at reducing energy consumption in large-scale Edge computing ecosystems. play a key role in developing and implementing AI aand ML algorithms to optimize the energy efficiency of edge computing infrastructure, including hardware, software, networking, application and connected devices as IoT and operational processes across the ecosystem. This role requires collaboration with internal and external partners and stakeholders.
WHAT WILL YOU DO?
- Develop and implement AI/ML models that dynamically optimize energy usage across edge computing infrastructure, including workload scheduling, resource allocation, and load balancing to enable a sustainability fosucsed orchestration for cloud edge computing and other IT eco systems.
- Leverage predictive algorithms to anticipate demand and adjust power consumption in real-time, reducing unnecessary energy use without sacrificing performance
- Conduct research into state-of-the-art AI/ML approaches for energy efficiency, focusing on areas such as green AI, energy-aware algorithms, and AI models that require less computational power
- Work closely with sustainability experts, product managers, and engineering teams to ensure AI/M solutions are fully integrated into the broader energy-saving goals of the project
- Evaluate tools and product in the market that can support the use of AI and data collection in an sustainability focused orchstration solution
- Implement AI/ML techniques that reduce the need for large-scale data transmission, such as edge-based data processing and federated learning, to minimize energy consumption associated with data transfers