Machine Learning Engineer – Intelligent Automotive Retail and Mobility

Machine Learning Engineer – Intelligent Automotive Retail and Mobility

Education: Bachelor's Degree in Computer Science/Electrical Engineering, Math, or related field.

Experience: Minimum 3 strong years of software engineering practices and experiences in data science, machine learning, generative AI.

Description:

• We are seeking passionate candidates for a machine learning/deep learning software engineering role who will join as a machine learning research engineer helping the team build intelligent automotive retail and mobility solutions.

Responsibilities:

• Contribute to state-of-the-art machine learning infrastructure and relevant software (e.g. supervised learning, reinforcement learning, data management, and evaluation at unparalleled scale).
• Implement cutting-edge deep learning models accelerating model training performance for intelligent automotive retail and mobility system applications.
• Apply the latest advances in deep learning and machine learning to personalize car owners' experience.
• Manipulate high-volume, high-dimensionality, structured data from automotive retail transactions to generate predictions and recommendations that address the challenges of the automotive industry.
• Work in a multidisciplinary team and collaborate with other teams across our R&D and Delivery team.

Skills:

• Strong machine learning background with a deep understanding of different types of machine learning algorithms (e.g., CNN, RNN, LSTM, and Reinforcement Learning). Experience in training deep-learning models in an end-to-end fashion.
• Project experience working with Azure Machine Learning, Azure Open AI, or other modern deep learning frameworks.
• Proficient in Python is a minimum. Additional knowledge of C++ / C# is a plus.
• Working knowledge of statistics (e.g., Monte Carlo, hypothesis testing, confidence intervals, maximum likelihood, bootstrap, Bayesian inference).
• Working knowledge in machine learning algorithms: logistic regression, random forest, gradient boosted trees, neural networks, k-means, and more.
• Excellent verbal and written communication skills.