Senior On-Device Model Inference Optimization Engineer

at Nvidia
USD 184,000-356,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 7 Machine Learning @ 4 Communication @ 7 PyTorch @ 4 CUDA @ 4

Details

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. We are seeking a highly-skilled Senior On-Device Model Inference Optimization Engineer to lead efforts in improving the performance and efficiency of AI models enabling the next generation of autonomous vehicles technology.

Responsibilities

  • Develop and implement strategies to optimize AI model inference for on-device deployment.
  • Employ techniques like pruning, quantization, and knowledge distillation to minimize model size and computational demands.
  • Optimize performance-critical components using CUDA and C++.
  • Collaborate with multi-functional teams to align optimization efforts with hardware capabilities and deployment needs.
  • Benchmark inference performance, identify bottlenecks, and implement solutions.
  • Research and apply innovative methods for inference optimization.
  • Adapt models for diverse hardware platforms and operating systems with varying capabilities.
  • Create tools to validate the accuracy and latency of deployed models at scale with minimal friction.
  • Recommend and implement model architecture changes to improve the accuracy-latency balance.

Requirements

  • MSc or PhD in Computer Science, Engineering, or a related field, or equivalent experience.
  • Over 10 years of confirmed experience specializing in model inference and optimization.
  • Expertise in modern machine learning frameworks, particularly PyTorch, ONNX, and TensorRT.
  • Proven experience in optimizing inference for transformer and convolutional architectures.
  • Strong programming proficiency in CUDA, Python, and C++.
  • In-depth knowledge of optimization techniques, including quantization, pruning, distillation, and hardware-aware neural architecture search.
  • Skilled in building and deploying scalable, cloud-based inference systems.
  • Passionate about developing efficient, production-ready solutions with a strong focus on code quality and performance.
  • Meticulous attention to detail, ensuring precision and reliability in safety-critical systems.
  • Strong collaboration and communication skills for working optimally across multidisciplinary teams.

Ways to stand out

  • Publications or industry experience in optimizing and deploying model inference at scale.
  • Hands-on expertise in hardware-aware optimizations and accelerators such as GPUs, TPUs, or custom ASICs.
  • Active contributions to open-source projects focused on inference optimization or machine learning frameworks.
  • Experience in designing and deploying inference pipelines for real-time or autonomous systems.

Compensation & Benefits

  • Base salary range:
    • Level 4: 184,000 USD - 287,500 USD
    • Level 5: 224,000 USD - 356,500 USD
  • You will also be eligible for equity and benefits (see NVIDIA benefits page).

Other

  • Applications for this job will be accepted at least until October 10, 2025.
  • NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.