Senior Machine Learning Engineer for Systems and Networks
hace 5 días
Job Description
We are seeking a highly skilled Senior Machine Learning Engineer to join our team at Telefonica Innovacion Digital - Discovery Research. The successful candidate will be responsible for developing and implementing novel algorithms, methodologies, and AI models to improve system and network efficiency, reliability, and scalability.
About the Role
This is an exciting opportunity to work on challenging projects that will allow you to be the protagonist of the company's transformation. You will have the chance to collaborate with cross-functional teams, including researchers, engineers, and data scientists to define system/network requirements and design specifications.
Main Responsibilities:
- 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.
- Mentor and guide junior researchers, providing technical expertise and fostering a culture of innovation and excellence.
Requirements:
- Bachelor's, Master's, or Ph.D. 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.g., TensorFlow, PyTorch), distributed ML frameworks (e.g., Flower.ai), and distributed computing platforms (e.g., Apache Spark).
- Experience with cloud computing platforms (e.g., AWS, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
- Familiarity with version control systems (e.g., 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.
About Us
We are Telefonica, S.A., a leading industrial research lab based in Barcelona, Spain. Our mission is to carry out research studies on mid to long-term topics related to several technological areas of interest to the Telefónica Group.
What We Offer
- An estimated salary of €80,000 - €120,000 per year, depending on experience.
- A dynamic team environment and the chance to work on challenging projects.
- A comprehensive benefits package, including health insurance, pension plan, and flexible compensation plan.
- Access to countless continuous learning opportunities to grow with us.
- The chance to participate in volunteer programs, social actions, international mobility programs, and off-sites.
- The opportunity to work in a multicultural environment with over 100 nationalities present in more than 35 countries.
How to Apply
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