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# Software Engineer

- **Company:** Pony.AI, Inc.
- **Location:** United States
- **Experience:** Experienced
- **Salary:** $140,000.0 - $280,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, C++ (Programming Language), Program Optimization, Nvidia CUDA, Convex Optimization, Data Structures, Python (Programming Language), Machine Learning, Language Modeling, Motion Planning, Natural Language Processing, Software Architecture, Computational Geometry, Reinforcement Learning, Real Time Systems, Feature Engineering, Large Language Models, Deep Learning, Parallel Computation, Information Technology, TensorRT, Data Pipelines
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-software-engineer-deep-learning-ponyai-5493228

## About the Role

* Master in Computer Science, or at least 2 years of equivalent industry experience in similar technical fields.
 * Solid understanding of data structures, algorithms, parallel computing, code optimization and large scale data processing.
 * Experience in applied machine learning including data collection and analysis, evaluation and feature engineering.
 * Expertise in C++/Python.
 * Strong communication skills and team spirit., * PhD in Deep Learning, Machine Learning, Robotics, Natural Language Processing, or similar technical field of study.
 * Publications on top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/ICLR/AAAI/IJCV/PAMI
 * Experience in applying ML/DL for behavior prediction, imitation learning, motion planning.
 * Experience in deploying deep learning algorithms for real time applications, with limited computing resources.
 * Experience in convex optimization, computational geometry or linear algebra.
 * Experience in GPU/CUDA/TensorRT

## Description

* Work with experts in the field of self-driving vehicles on software architecture and design, system and module design, evaluation metrics, specification and implementation of test and regression frameworks.
 * Design and develop large-scale foundation models trained on vast of real world data
 * Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems; scale them to data pipelines; and streamline them to run in real-time on the cars.
 * Develop and deploy deep learning models, including vision language models (VLMs) and Large Language Models (LLMs)
 * Optimize deep learning models to run robustly under tight run-time constraints.


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