Browse 23 exciting jobs hiring in Tensorrt now. Check out companies hiring such as NVIDIA, Cyngn, Advanced Technology Services in Plano, Omaha, Virginia Beach.
Help architect and run a global, multi-cloud compute platform at NVIDIA that ensures scalable, cost-efficient delivery of AI training for millions of learners.
Work on NVIDIA’s learning systems platform to enable content creators, build scalable delivery pipelines, and operate GPU-accelerated, multi-cloud learning environments.
Lead development and deployment of multi-modal deep learning perception models (camera + lidar) to enable robust pallet detection and tracking for Cyngn's autonomous industrial vehicles.
Apply computer vision expertise to design, optimize, and deploy high-performance edge AI solutions on NVIDIA Jetson platforms for EchoTwin AI's urban sensing systems.
Embedded software engineer needed to develop Linux kernel drivers, optimize real-time firmware, and collaborate with silicon teams to bring new chips and boards to production.
Lead technical engagements to architect and implement robotics simulation and AI solutions using NVIDIA's Isaac, Omniverse, and related tooling for customers building next-generation autonomous systems.
NVIDIA is hiring a Senior Deep Learning Frameworks Sustaining Engineer to integrate, back-port, and stabilize TensorFlow, PyTorch and TensorRT for enterprise LTS releases.
Lead a high-impact team accelerating LLM inference performance at NVIDIA by combining deep systems expertise, GPU profiling, and cross-functional collaboration.
NVIDIA is hiring university students for 12-week Software Engineering internships to contribute to projects in development tools, cloud infrastructure, infrastructure tooling and MLOps using modern software and GPU-accelerated technologies.
Zoox is hiring a Senior Manager to lead perception teams building multi-modal detection and sensor-fusion systems for its autonomous vehicle platform.
Lead developer and partner engagement to drive adoption of NVIDIA GPUs and SDKs across power generation, creating blueprint reference solutions, SDK integrations, and high-impact developer content for industrial and regulated environments.
Lead the design and deployment of production AI systems at VORTO, focusing on LLM fine-tuning, RAG-based retrieval, and low-latency inference to optimize supply-chain operations.
Lead the development of distributed runtime and orchestration systems (Rust, Kubernetes, Slurm) to enable large-scale, low-latency GPU inference for NVIDIA's Dynamo/Inference Server ecosystem.
A new-graduate software engineer role on NVIDIA's TensorRT team to help design and optimize high-performance deep learning inference software for specialized platforms.
Contribute to aion's inference infrastructure as an ML Inference Platform Intern, learning and implementing high-performance optimization techniques for production GPU systems.
Serve Robotics is hiring an ML Performance Engineer to optimize and deploy real-time ML models on NVIDIA Jetson-based delivery robots in Los Angeles.
Lead the design and scaling of high-performance ML training infrastructure at a seed-stage robotics startup using distributed GPU systems and modern ML tooling.
NVIDIA is hiring a Systems Software Engineer to develop and evaluate cloud-native AI inference systems, agentic workflows, and developer-focused content that leverage GPU-accelerated frameworks.
Lead developer relations for GPU-accelerated solutions across grid, industrial and data-center power domains, connecting OT systems to AI-enabled IT infrastructures.
Help accelerate production LLM inference at .txt by optimizing multi-GPU pipelines, kernel performance, and deployment reliability for structured generation workloads.
Work on the core model-serving infrastructure at ByteDance to design and scale distributed inference systems that power ranking and recommendation across products.
Senior engineer role to design, prototype, and productionize vision-based navigation and perception algorithms for Anduril’s aerial robotics platforms in Seattle.
At Roboflow, contribute to production-ready computer vision systems—deploying and optimizing models, building inference services, and scaling pipelines for real-world use.
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