NVIDIA · 4 days ago
DL Algorithms Engineer - Cosmos - New College Graduate 2026
US, CA, Santa Clara
Full-time
Onsite
New Grad, Entry Level
$124K/yr - $196K/yrNVIDIA is seeking a highly skilled Deep Learning Algorithms Engineer to optimize and deploy advanced AI models, particularly Large Language Models and Vision-Language Models. The role involves collaboration with various specialists to ensure efficient integration of AI models from prototype to production, focusing on performance optimization across GPU platforms.
AI InfrastructureArtificial Intelligence (AI)Consumer ElectronicsFoundational AIGPUHardwareSoftwareVirtual Reality
Responsibilities
Optimize deep learning models for low-latency, high-throughput inference, with a focus on LLMs, VLMs, diffusion models, and World Foundation Models (WFMs) designed for physical AI applications
Convert, deploy, and optimize models for efficient inference using frameworks such as TensorRT, TensorRT-LLM, vLLM, and SGLang
Understand, analyze, profile, and optimize performance of deep learning and physical AI workloads on state-of-the-art NVIDIA GPU hardware and software platforms
Implement and refine components and algorithms for efficient serving of LLMs, VLMs, and WFMs at datacenter scale, leveraging technologies like Dynamo
Collaborate with research scientists, software engineers, and hardware specialists to ensure seamless integration of cutting-edge AI models from training to deployment
Contribute to the development of automation and tooling for NVIDIA Inference Microservices (NIMs) and inference optimization, including creating automated benchmarks to track performance regressions
Qualification
Required
Master's or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience)
Experience in deep learning, applied machine learning, or physical AI development
Strong foundation in deep learning algorithms, including hands-on experience with LLMs, VLMs, and multimodal generative models such as World Foundation Models
Deep understanding of transformer architectures, attention mechanisms, and inference bottlenecks
Proficient in building, optimizing, and deploying models using PyTorch or TensorFlow in production-grade environments
Solid programming skills in Python and C++
Experience with model quantization and modern inference optimization techniques (e.g., KV cache, in-flight batching, parallelization mapping)
Strong fundamentals in GPU performance analysis and profiling tools (e.g., Nsight, nsys profiling)
Familiarity with serving models using Triton Inference Server and PyTriton via Docker
Preferred
Proven experience deploying LLMs, VLMs, diffusion models, or World Foundation Models (WFMs) at scale in real-world applications, especially for robotics or autonomous vehicles
Hands-on experience with model optimization and serving frameworks, such as: TensorRT, TensorRT-LLM, vLLM, SGLang, and ONNX
Direct experience with NVIDIA Cosmos, Isaac Sim, Isaac Lab, or Omniverse platforms for synthetic data generation and physical AI simulation
Experience with data curation pipelines and tools like NVIDIA NeMo Curator for large-scale video data processing and model post-training
Deep understanding of distributed systems for large-scale model inference and serving
Benefits
Equity
Benefits
Company
NVIDIA
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
Founded in 1993
10001+ employees
H1B Sponsorship
NVIDIA has a track record of offering H1B sponsorships. Please note that this does not
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2025 (1877)
2024 (1355)
2023 (976)
2022 (835)
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Funding
Current Stage
Public CompanyTotal Funding
$4.09BKey Investors
ARPA-EARK Investment ManagementSoftBank Vision Fund
2023-05-09Grant· $5M
2022-08-09Post Ipo Equity· $65M
2021-02-18Post Ipo Equity
Leadership Team
Jensen Huang
Founder and CEO
Michael Kagan
Chief Technology Officer
Recent News
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