As a seasoned software engineer on NVIDIA’s Metropolis team, you will design and develop innovative video analytics services using advanced AI technologies such as Vision-Language Models (VLMs) and Large Language Models (LLMs). Your responsibilities include leading the full lifecycle of software development from conceptualization to production release, optimizing models for performance on NVIDIA hardware, and collaborating with a global team to deliver impactful real-world applications. You will leverage modern C++ and Python in Linux environments, work with GPU acceleration technologies like CUDA and TensorRT, and utilize cloud-native tools such as Docker and Kubernetes. This role requires extensive experience in machine learning systems, distributed architectures, and multimedia technologies, making it ideal for those passionate about transforming the physical world through intelligent video analytics at scale.
Skills
Python
C++
CUDA
TensorRT
PyTorch
Docker
Kubernetes
Helm
AWS
Azure
NVIDIA_TAO
AutoML
REST_APIs
Linux
Multimodal_VLMs
LLMs
GPU_cloud_infrastructure
Video_processing
Codecs
Streaming_pipelines
Embedded_environments_NVIDIA_Jetson_Orin
What you'll do
Design and develop modern software and services for video processing across diverse domains.
Own the full lifecycle of software development from conceptualization to production release.
Integrate innovative AI technologies like Vision-Language Models and Large Language Models into video processing systems.
Ensure high reliability and maintainability by applying strong software engineering practices.
Optimize models using advanced tooling to enhance accuracy and hardware utilization.
Collaborate globally to translate advanced technologies into impactful real-world applications.
What we're looking for
5+ years of professional software development experience with production-grade machine learning systems.
Strong background in computer science fundamentals including algorithms, data structures, concurrency, and distributed systems.
Hands-on experience with multimodal Vision-Language Models (VLMs) and Large Language Models (LLMs).
Practical expertise in GPU-accelerated machine learning inference using CUDA or TensorRT.
Sound understanding of microservices, REST APIs, and cloud-native deployment tools like Docker and Kubernetes.
Experience delivering comprehensive video AI solutions including multimedia technologies such as codecs and streaming pipelines.
Familiarity with optimizing frameworks like NVIDIA TAO and AutoML for vision and LLM/VLM model enhancement.
Market check
Salary context
This
$152,000–$241,500
range sits above
72%
of similar postings on FindRole.
Peer median band
$119,800–$209,000
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$139,087–$204,725
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
802 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 798 roles with salary data.