Nvidia Principal Engineer Federated Learning 

United States, California 

756606452

The quality of AI models developed is only as good as the data it was trained on, and hence large datasets are necessary to extract complex and predictive patterns. Compared to the classical centralized training approach, federated learning is a privacy-preserving, distributed learning paradigm which tackles the challenges associated with learning from data in a decentralized way.

What you’ll be doing:

• Lead the design and development of cutting-edge federated learning solutions.

• Closely collaborate with researchers world-wide to advance federated learning algorithms and techniques.

• Work with cross-functional teams in NVIDIA, including data scientists, software engineers, and industry experts, to integrate federated learning solutions into real-world applications.

• Optimize federated learning system for performance, scalability, ease of use, reliability and security.

• Leverage NVIDIA's cutting-edge hardware and software platforms to enhance federated learning solutions.

• Enhance federated learning solutions with the highest standards of data privacy, security, regulations and best practices.

• Mentor and guide junior engineers, set best engineering practice and process, fostering a culture of continuous learning and innovation within the team.

What we need to see:

• MS or PhD in Computer Science, Electrical Engineering, or a related field (or equivalent experience).

• 12+ years of work or equivalent experience in delivering high-performance software systems.

• 8+ years of architect experience in designing and developing distributed systems.

• 5+ hands-on working experience with distributed machine learning technologies such as Distributed PyTorch, Horovod, Ray and MPI.

• 5+ working experience in machine learning libraries like Llama, Nemo, PyTorch, TensorFlow, XGBoost and scikit-learn.

• Outstanding skills for system and API design.

• Excellent hands-on programming skills in Python and C++.

• Advanced knowledge and experience in communication and network protocols such gRPC, HTTPS, TLS.

• Experience enterprise security such as PKI, authentication and authorization

• Excellent analytical and problem-solving abilities, with a creative approach to tackling complex technical challenges.

• Strong technical leadership with a strategic mindset, seeing beyond immediate tactical tasks to envision and drive long-term goals.

Ways to stand out from the crowd:

• Working experience in federated learning frameworks such as FLARE, Flower, OpenFL, PySyft, and Tensorflow Federated.

• experience in designing generative AI and agentic AI solutions.

• Hands on experience in developing edge-based AI solutions.

• Architect experience in major open-source projects.

• Direct working experience with NVIDIA software, hardware and SDKs.