Senior Machine Learning Engineer, LLM/VLM Visual Reasoning
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El puesto
Design and implement cutting-edge models and algorithms for spatial-temporal visual reasoning using LLMs and VLMs in autonomous driving scenarios.
Build and maintain robust training and evaluation pipelines for VLMs, focusing on decision-making rationale and free-form QA tasks.
Collaborate with ML engineers and researchers to integrate visual reasoning capabilities into product systems.
Lead the creation of large-scale rationale/QA data sets and establish rigorous evaluation metrics for visual reasoning tasks.
Explore advanced techniques such as Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) to optimize model performance on complex visual reasoning challenges.
Analyze and interpret large-scale sensor data to identify challenges and opportunities for improving LLM/VLM performance in real-world driving environments.
Build and maintain robust training and evaluation pipelines for VLMs, focusing on decision-making rationale and free-form QA tasks.
Collaborate with ML engineers and researchers to integrate visual reasoning capabilities into product systems.
Lead the creation of large-scale rationale/QA data sets and establish rigorous evaluation metrics for visual reasoning tasks.
Explore advanced techniques such as Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) to optimize model performance on complex visual reasoning challenges.
Analyze and interpret large-scale sensor data to identify challenges and opportunities for improving LLM/VLM performance in real-world driving environments.
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