Inference Optimization Architect, Speech AI
Nvidia · Bangalore, India
About this role
Nvidia is hiring a senior-level Machine Learning Engineer based in Bangalore, India. The posting calls out experience with CUDA, PyTorch, LLMs, Deep Learning and roughly 10+ years of relevant work. Listed education preference: a master's degree or equivalent.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Bangalore, India
- Experience
- 10+ years
- Education
- Master's degree
- Posted
- Apr 20, 2026
More roles at Nvidia
Job description
from Nvidia careersWidely considered to be one of the technology world’s most desirable employers, NVIDIA is an industry leader with groundbreaking developments in High-Performance Computing, Artificial Intelligence and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, autonomous cars and conversational AI that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company, and build our teams with the smartest people in the world. Join us at the forefront of technological advancement.
NVIDIA is looking for an Inference Optimization architect to accelerate and scale our Speech AI models & improve the experience of millions of customers. You will focus on reducing inference latency, improving throughput, and optimizing resource utilization across our AI infrastructure. If you're creative & passionate about solving real world conversational AI problems, come join our Speech AI Engineering team.
What you’ll be doing:
Optimize Inference Performance: Improve streaming latency and throughput through advanced batching strategies, encoder caching, and multi-threaded pipeline optimizations
Model Compression: Implement techniques including quantization, pruning, and knowledge distillation.
This is an excerpt. Read the full job description on Nvidia careers →