> Markdown version of [/jobs/ext/1219573-senior-deep-learning-engineer-perception-autonomous-driving](https://www.wearedevelopers.com/jobs/ext/1219573-senior-deep-learning-engineer-perception-autonomous-driving). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Deep Learning Engineer - Perception, Autonomous Driving - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $184,000.0 - $287,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, C++ (Programming Language), Program Optimization, Computer Programming, Python (Programming Language), Machine Learning, Object Detection, DataOps, Software Engineering, Pytorch, Deep Learning, Data Strategy, Information Technology, TensorRT - **Published:** July 9, 2026 - **Apply:** https://www.disabledperson.com/jobs/73569894-senior-deep-learning-engineer-perception-autonomous-driving ## About the Role * Ph.D. or MS in Computer Science, Robotics, Machine Learning, Computer Vision, or a related field (or equivalent experience). * 8+ years of applied research and software engineering experience, with a heavy emphasis on deep learning for computer vision. * Proven Track Record: Demonstrated success as a lead technical contributor in shipping commercial, high-quality deep learning software products to end customers. * Domain Expertise: Deep foundational knowledge and hands-on experience in building architectures for object detection, occupancy networks, semantic/instance segmentation, and temporal tracking. * Data Intuition: A strong intuition for data-centric AI. Proven experience taking care of massive datasets, defining labeling taxonomies, and building automated pipelines to surface hard examples and edge cases. * Engineering Excellence: Strong programming skills in Python and C++, with experience using deep learning frameworks like PyTorch. Ways to stand out from the crowd: * Prior experience specifically within the autonomous driving or robotics industry shipping models deployed on edge compute. * Experience with model optimization, quantization, and deployment on embedded platforms (especially using NVIDIA TensorRT). * First-author publications at top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, ECCV, NeurIPS). * Experience designing multi-modal perception systems (camera, lidar, radar fusion). ## Description * Architect and Innovate: Develop, train, and deploy modern, state-of-the-art deep learning architectures (e.g., Transformers, variants of Transformers, Few Shots Learning) for 3D obstacle detection, dense occupancy prediction, semantic segmentation, and multi-object tracking. * Ship High-Quality Products: Drive the end-to-end productization of perception models. You will have ownership of shipping robust, production-grade deep learning features to our global automotive customers, ensuring they meet the highest standards of safety and quality. * Lead Corner-Case Driven Development: Champion a rigorous, safety-critical development process. You will proactively identify, mine, and solve long-tail corner cases in sophisticated urban and highway driving environments. * Define Data Strategy: Act as the technical authority on data quality. You will define data labeling guidelines, establish quality control metrics, and work closely with data operations to ensure high-fidelity ground truth for sophisticated perception tasks. * Technical Leadership: Serve as a technical pillar for the perception organization. You will mentor senior engineers, influence cross-functional teams (planning, mapping, and infrastructure), and set the technical roadmap for next-generation perception architectures. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Intelligent Data Selection for Continual Learning of AI Functions](https://www.wearedevelopers.com/videos/367-intelligent-data-selection-for-continual-learning-of-ai-functions) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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