Principal Engineer, Federated Learning

at Nvidia
📍 Santa Clara, United States
USD 248,000-391,000 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Security @ 4 Python @ 4 Algorithms @ 4 Distributed Systems @ 7 Machine Learning @ 6 scikit-learn @ 6 TensorFlow @ 6 Hiring @ 4 Leadership @ 7 Communication @ 7 gRPC @ 7 API @ 4 Technical Leadership @ 7 PyTorch @ 6 XGBoost @ 6 PKI @ 4

Details

The quality of AI models depends on the data they are trained on. Compared to classical centralized training, federated learning is a privacy-preserving, distributed learning paradigm that enables organizations to learn from decentralized data while protecting privacy. Join the NVIDIA FLARE team to build open-source federated learning solutions used across healthcare, finance, scientific computing, government, and edge AI applications.

Responsibilities

  • Lead the design and development of cutting-edge federated learning solutions.
  • Collaborate with researchers worldwide to advance federated learning algorithms and techniques.
  • Work with cross-functional teams at NVIDIA (data scientists, software engineers, industry experts) to integrate federated learning into real-world applications.
  • Optimize federated learning systems for performance, scalability, ease of use, reliability, and security.
  • Leverage NVIDIA hardware and software platforms to enhance federated learning solutions.
  • Ensure solutions meet high standards for data privacy, security, and regulatory best practices.
  • Mentor and guide junior engineers; set engineering best practices and foster continuous learning and innovation.

Requirements

  • MS or PhD in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
  • 12+ years of work or equivalent experience delivering high-performance software systems.
  • 8+ years of architect experience designing and developing distributed systems.
  • 5+ years hands-on experience with distributed machine learning technologies such as Distributed PyTorch, Horovod, Ray, and MPI.
  • 5+ years working with machine learning libraries such as Llama, Nemo, PyTorch, TensorFlow, XGBoost, and scikit-learn.
  • Outstanding skills in system and API design.
  • Excellent hands-on programming skills in Python and C++.
  • Advanced knowledge and experience in communication and network protocols such as gRPC, HTTPS, and TLS.
  • Experience with enterprise security (PKI, authentication and authorization).
  • Excellent analytical and problem-solving abilities and a creative approach to complex technical challenges.
  • Strong technical leadership with a strategic mindset.

Ways to stand out

  • Experience with federated learning frameworks such as FLARE, Flower, OpenFL, PySyft, and TensorFlow Federated.
  • Experience designing generative AI and agentic AI solutions.
  • Hands-on experience developing edge-based AI solutions.
  • Architect experience in major open-source projects.
  • Direct working experience with NVIDIA software, hardware, and SDKs.

Compensation & Benefits

  • Base salary range: 248,000 USD - 391,000 USD (final base salary determined by location, experience, and comparable positions).
  • Eligible for equity and NVIDIA benefits.

Additional information

  • Applications will be accepted at least until September 19, 2025.
  • NVIDIA is an equal opportunity employer and values diversity in hiring and promotion practices.