Short-term Research Project on Distributed / Federated Learning on Mobile Devices

 

TELEFONICA RESEARCH:

Telefonica Research is hiring for a short-term research project focused on Privacy-Preserving / Federated Learning on Mobile/Edge Devices.

 

Telefonica Research is a leading industrial research lab based in Barcelona (Spain). The aim of the lab is to carry out research studies on mid to long-term topics related to several technological areas of interest to the Telefónica Group. The Research group follows an open research model in collaboration with universities and other research institutions, promoting the dissemination of their work both through publications and technology transfer. The board is constituted of a multi-disciplinary team with a variety of skills that includes systems, networks, HCI, Machine Learning and Privacy/Security. We are seeking candidates at all levels of seniority for research engineer positions to strengthen and complement our research efforts in the areas Telefonica Research is currently work on, relating to systems and networks, security and privacy of machine learning, networks, measurements, and beyond. 

 

We are looking for a researcher (close to finishing their PhD or in early stages after the PhD) to join our team of experts who are working in the development of privacy-preserving machine learning solutions. During this short-term project, which can last up to 6 months, the researcher will be responsible for designing and implementing privacy preserving federated learning solutions for Android or other mobile/edge platforms, particularly in low resource settings.

 

Key Responsibilities:

• Design and develop privacy preserving federated learning solutions for mobile platforms. 
• Implement state-of-the-art techniques such as differential privacy, secure aggregation, and homomorphic encryption to ensure data privacy.
• Optimize federated learning algorithms for low resource environments.
• Collaborate with cross-functional teams to integrate federated learning solutions into existing mobile applications. 
• Conduct experiments and evaluations to assess the performance of federated learning solutions. 
• Stay up-to-date with industry trends and developments related to privacy preserving federated learning and make recommendations for future improvements.
• Write technical reports and documentation to communicate results to internal and external stakeholders.

 

Qualifications:

• PhD (or close to completion) in Computer Science, Electrical Engineering, or related field.
• Experience in privacy preserving federated learning in mobile platforms, especially in low resource settings.
• Strong understanding of machine learning algorithms and their implementation on mobile platforms.
• Strong knowledge and experience in development of high-quality code for research in the area of (distributed) ML, Split Learning, systems & networks for Large ML Models, etc.
• Experience with privacy preserving techniques such as differential privacy, secure aggregation, and homomorphic encryption.
• Solid understanding of ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), distributed ML frameworks (e.g., Flower).
• Preferred candidates will have prior experience in utilizing machine learning on low-end devices (using libraries such as TensorFlowLite), coupled with proficiency in Android development.
• Strong programming skills in languages such as Java, Kotlin, and Python.
• Experience with mobile development frameworks such as Android Studio and Xcode.
• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal skills to collaborate with cross-functional teams.

• We are seeking candidates at all levels of seniority. 

 

If you join us, we offer you...

• Work in a dynamic team and be part of challenging projects that will allow you to play a leading role in the transformation of the company.
• An interesting package of social benefits (luncheon vouchers, health, life and accident insurance, pension plan, flexible compensation plan...).
• A flexible working environment with hybrid models of face-to-face and telecommuting.
• Access to a wide range of continuous learning opportunities for you to grow with us.
• Participate in volunteering programmes, social actions, international mobility, off-site...

 

#UnidadesGlobales #CDO

 

 

If you join Telefónica
You join almost 100 years of history, a team of 106 nationalities present in more than 35 countries. You join a team that works to connect people wherever they are, without borders. A team that is leading the digital revolution with the enthusiasm of the first day in all our businesses, creating the best digital ecosyst