Woven by Toyota - Machine Learning Engineer, Perception Autolabeling (Internship)
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Requirements
• Currently pursuing a Masters or a PhD degree in Computer Science, Computer Engineering, Computer Systems, Data Science, or similar discipline • Proven ability to develop ML models for image, video, 3D or 4D data processing and/or generation (must be supported by school projects and/or publications) • Strong programming skills in Python and ML development with PyTorch • Good written and verbal communication skills • Passionate about self driving car technology and its potential for humanity • Experience developing ML models for autonomous driving or ADAS • Experience developing Perception algorithms for autonomous driving or ADAS • Publications in top tier CV, ML or robotics conferences or journals • The base pay for this position ranges from $30 - $55 per hour. • This internship is a temporary, non-permanent position designed to provide practical experience and learning opportunities. The duration of the internship is 12 weeks. The total compensation offered to an intern will be dependent upon the individual's skills, experience, qualifications, location, and level.
Responsibilities
• Develop and implement machine learning models for automated labeling of images in the context of autonomous driving systems. • Collaborate with cross-functional teams to integrate ML solutions into existing workflows within AD/ADAS projects at Toyota. • Collect, preprocess, and annotate a diverse set of image data relevant to autolabeling tasks for training machine learning models. • Monitor model performance using appropriate metrics and make iterative improvements based on feedback from team members or project leads. • Document the ML pipeline architecture, including algorithms used, feature selection methods, and evaluation techniques applied in automated labeling processes. • Participate in regular meetings with stakeholders to understand their requirements for autolabeling accuracy and speed within AD/ADAS projects at Toyota. • Maintain a high level of proficiency in programming languages commonly used in machine learning, such as Python or R, along with knowledge of relevant libraries like TensorFlow or PyTorch.
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