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What you will be doing:
Build and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our driving systems.
Explore novel data generation and collection strategies to improve diversity and quality of training datasets. Develop, pre-train, and optimize LLM/VLM/VLA models for autonomous driving and robotics applications.
Collaborate cross-functionally to deploy and integrate AI models into vehicle firmware.
Deliver production-quality, safety-critical software that meets performance, safety, and reliability standards.
What we need to see:
PhD or Master's degree with equivalent experience.
8+ years of experience
Hands-on experience training LLMs/VLMs/VLAs from scratch, or a proven record as a top-tier ML engineer/researcher passionate about autonomous systems.
Strong programming skills in Python and proficiency with major deep learning frameworks. Basic familiarity with C++ for model deployment and integration in safety-critical systems.
Comprehensive grasp of current deep learning structures and improvement methods. Consistent track record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.
Ways to stand out from the crowd:
Experience developing and shipping LLM/VLM/VLA solutions for autonomous vehicles or general robotics products.
Publications, contributions to open-source projects, or victories in competitions connected to LLM/VLM/VLA systems.
Profound comprehension of behavior and motion planning in real-world autonomous vehicle (AV) applications.
Experience building and training large-scale datasets and models and/or training agents with reinforcement learning.
These jobs might be a good fit

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These jobs might be a good fit

Share
These jobs might be a good fit

Share
These jobs might be a good fit

Share
These jobs might be a good fit

Share
These jobs might be a good fit

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Being the cybersecurity partner of choice, protecting our digital way of life.
Your Career
As the Backend Platform group, we develop end-to-end features and provide services to other development teams within Palo Alto. Our work involves building and maintaining the platform that powers all Cortex cloud products. In this role, you will also be responsible for managing large-scale data pipelines.
This is a unique opportunity to build a large-scale product. You will have a truly unique opportunity to influence the development of a new product. The new team will work closely with the PMs, cyber-research, and Dev leaders, help define the requirements, and conduct a substantial part of the technical research.
Your Impact
Your Experience
All your information will be kept confidential according to EEO guidelines.
These jobs might be a good fit

Share
What you will be doing:
Build and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our driving systems.
Explore novel data generation and collection strategies to improve diversity and quality of training datasets. Develop, pre-train, and optimize LLM/VLM/VLA models for autonomous driving and robotics applications.
Collaborate cross-functionally to deploy and integrate AI models into vehicle firmware.
Deliver production-quality, safety-critical software that meets performance, safety, and reliability standards.
What we need to see:
PhD or Master's degree with equivalent experience.
8+ years of experience
Hands-on experience training LLMs/VLMs/VLAs from scratch, or a proven record as a top-tier ML engineer/researcher passionate about autonomous systems.
Strong programming skills in Python and proficiency with major deep learning frameworks. Basic familiarity with C++ for model deployment and integration in safety-critical systems.
Comprehensive grasp of current deep learning structures and improvement methods. Consistent track record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.
Ways to stand out from the crowd:
Experience developing and shipping LLM/VLM/VLA solutions for autonomous vehicles or general robotics products.
Publications, contributions to open-source projects, or victories in competitions connected to LLM/VLM/VLA systems.
Profound comprehension of behavior and motion planning in real-world autonomous vehicle (AV) applications.
Experience building and training large-scale datasets and models and/or training agents with reinforcement learning.
These jobs might be a good fit