RESEARCH ENGINEER IN (DISTRIBUTED) MACHINE LEARNING FOR SYSTEMS & NETWORKS DETALLES DEL PUESTO | TELEFÓNICA

TELEFONICA INNOVACIÓN DIGITAL - DISCOVERY SCIENTIFIC RESEARCH Telefonica Innovación Digital - Discovery Scientific 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 Innovación Digital - Discovery Research is currently work on, relating to systems and networks, security and privacy of machine learning, networks, measurements, and beyond.
MISSION  For this position, we are seeking talented and motivated candidates at all levels of seniority for a staff engineer position to strengthen and complement our efforts towards building robust Machine Learning (ML) models for telecommunication systems and networks.
Special focus is given to the areas of distributed or federated ML, and how it can be applied to mobile systems and networksembedded devices, and beyond.
Knowledge or experience in the aspects of privacy and security in these areas will be highly valued.
The ideal candidate will have strong experience in the entire ML lifecycle, from data collection and preprocessing to model training, optimization, and deployment where experience with on-device training will be highly valued.
Previous experience with cloud computing infrastructures (AWS, MS Azure) is an extra.
Candidates, and will be passionate about building scalable and efficient ML systems based on their strong background in software engineering, machine learning, and distributed computing.
This role requires a deep understanding of ML engineering principles, strong analytical, programming and machine learning skills, and a drive to push the boundaries of technology in the research areas of interest of the Research Team.
The ideal candidate will excel in a fast-paced, collaborative environment within our Team and beyond, and have a proven track record of delivering high-quality research outcomes.
The Research Engineer will help the Team with potential dissemination of research results and prototype demonstrations to major industrial and academic venues worldwide, generation of intellectual property, and partnership with Telefonica business units to ensure the successful exploitation of research outputs.
Finally, the Engineer will support the Team in pursuing available funding opportunities at the National, European and International level.
MAIN RESPONSABILITES.
Conduct in-depth research on ML systems and/or network design, architecture, and performance optimization, to address complex engineering challenges.
Support the Research Team in developing and implementing novel algorithms, methodologies, and AI models to improve system and network efficiency, reliability, and scalability.
Collaborate with cross-functional teams, including researchers, engineers, and data scientists to define system/network requirements and design specifications.
Design and conduct experiments to evaluate ML models and system/network performance and collect and analyze data for actionable insights.
Develop ML models and pipelines using state-of-the-art techniques, libraries and frameworks.
Optimize and tune existing or new ML models for better performance, scalability, energy efficiency, fairness, privacy, etc.
Stay up to date with the latest advancements in centralized and distributed ML computing technologies.
Support the Research Team in identifying and troubleshooting ML system issues, propose solutions based on state-of-art or novel methods, and implement necessary modifications or enhancements.
Support the Research Team with publication of research findings in top academic conferences and journals, and actively contributing to the scientific community.
Stay up to date with the latest advancements and emerging trends in ML modeling libraries, systems, tools and platforms, and evaluate their potential impact on our organization's products and services.
Mentor and guide junior researchers, providing technical expertise and fostering a culture of innovation and excellence.
Generate Intellectual Property for Telefonica Innovacion Digital - Discovery Research Team and other units.
Seek partnerships with business (and other Telefonica) units to ensure the successful exploitation of research outputs.
QUALIFICATIONS.
Bachelor’s, Master’s or Ph.
.
in Computer Science, Telecommunication, Machine Learning, Systems & Networking, or other related fields  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.
Strong background in ML systems engineering, including experience with ML system design, ML model architecture, ML performance analysis, ML system and on-device measurements, and optimization.
Proficiency in programming languages such as Python, Java, C/C++, and familiarity with software implementation practices.
Solid understanding of ML algorithms, deep learning frameworks (e.
., TensorFlow, PyTorch), distributed ML frameworks (e.
., Flower.
i), and distributed computing platforms (e.
., Apache Spark).
Experience with cloud computing platforms (e.
., AWS, Google Cloud) and containerization technologies (e.
., Docker, Kubernetes) is a plus.
Preferred candidates will have prior experience in utilizing machine learning on end devices (using libraries such as TensorFlowLite), coupled with proficiency in Android development.
Familiarity with version control systems (e.
., Git) and continuous integration/continuous deployment (CI/CD) pipelines.
Experience in research lifecycle through publications, patents, or technical reports for research dissemination is a plus.
Strong analytical thinking and search for solutions.
Accuracy & attention to detail.
Effective communication, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
Ability to work both independently and collaboratively in a team-oriented environment.
Prior experience in conducting research in related areas is a plus.
We are seeking candidates at all levels of seniority.
LANGUAGE.
English     If you join us we offer you.
• Work in a dynamic team and be part of challenging projects that will allow you to be the protagonist of the company's transformation.
• An interesting package of social benefits (food vouchers, medical insurance, life and accident insurance, pension plan, flexible compensation plan...).
• A flexible work environment with hybrid models of in-person and teleworking.
• Access to countless continuous learning opportunities so you can grow with us.
• Participate in volunteer programs, social actions, international mobility programs, off-sites...
#Unidadesglobales #CDO     If you join Telefónica You join almost 100 years of history, you join a team of 106 nationalities present in more tan 35 countries.
You join a team that works to connect people wherever they are.
We are leading the digital revolution with the enthusiasm of the first day in all our businesses, creating the best digital ecosystem for our clients.
network, IoT, cloud, security, innovation etc.
Here, at Telefónica you count with everything you need to be the best you.
We need people like you that wants to take this challenge of creating the Telefónica of tomorrow.
Telefonica is committed to the new working ways.
Under our proposition “Disconnect to Reconnect” we have applied the Digital Disconnection.
#WeAreInclusive We strongly believe diverse and inclusive teams become more innovative and they achieve improved results.
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gender, age range, sexual orientation and/or identity, culture, creed, disability or any other personal condition.