Senior Engineer in Machine Learning for Automotive
IT & Telekom
Detta uppdrag är inte längre tillgängligt.
Location: Linköping, Sweden
Duration: July 1, 2024 - March 14, 2025 (with possibility of extension)
Work Arrangement: Onsite
Role Overview:
We are seeking a Senior Engineer or Software Developer with 4-8 years of experience in Machine Learning or Computer Vision. The ideal candidate will contribute to algorithm development for automotive applications, focusing on the design, implementation, and optimization of machine learning algorithms tailored for computer vision tasks.
Key Responsibilities:
Develop and optimize machine learning algorithms for real-time application in the automotive sector.
Manage data preprocessing and ensure the quality and relevance of large-scale datasets for training models.
Train, fine-tune, and evaluate deep learning models, considering the constraints of embedded platforms.
Conduct system engineering tasks including requirements analysis, testing, and documentation.
Qualifications:
Master’s degree in Computer Science, Electrical Engineering, or a related field.
Proficient in Python, C, and C++.
Strong understanding of deep learning architectures such as CNNs.
Experience with TensorFlow, PyTorch, Keras, or similar tools.
Previous exposure to automotive sensor data is beneficial.
Candidate Profile:
Excellent team player with a collaborative mindset, capable of working effectively in a multidisciplinary team environment.
Duration: July 1, 2024 - March 14, 2025 (with possibility of extension)
Work Arrangement: Onsite
Role Overview:
We are seeking a Senior Engineer or Software Developer with 4-8 years of experience in Machine Learning or Computer Vision. The ideal candidate will contribute to algorithm development for automotive applications, focusing on the design, implementation, and optimization of machine learning algorithms tailored for computer vision tasks.
Key Responsibilities:
Develop and optimize machine learning algorithms for real-time application in the automotive sector.
Manage data preprocessing and ensure the quality and relevance of large-scale datasets for training models.
Train, fine-tune, and evaluate deep learning models, considering the constraints of embedded platforms.
Conduct system engineering tasks including requirements analysis, testing, and documentation.
Qualifications:
Master’s degree in Computer Science, Electrical Engineering, or a related field.
Proficient in Python, C, and C++.
Strong understanding of deep learning architectures such as CNNs.
Experience with TensorFlow, PyTorch, Keras, or similar tools.
Previous exposure to automotive sensor data is beneficial.
Candidate Profile:
Excellent team player with a collaborative mindset, capable of working effectively in a multidisciplinary team environment.
Period
2024-07-01 -
2025-03-14