Machine Learning Engineer (MLE)  

A Machine Learning Engineer train machine learning (ML) and deep learning (DL) models or implement pretrained models to perform visual recognition tasks, text generation, classification, etc.

• Design & implement ML/DL solutions and integrate them with various Big Data platforms and architectures.
• Creating and maintaining ML pipelines that are scalable, robust, and ready for production.
• Collaborate with domain experts, software developers, and product owners.
• Troubleshoot ML/DL model issues, including recommendations for retrain, revalidate, and improvements/optimization.
• Realize Continuous Integration (CI) and Continuous Deployment (CD) pipelines within ML/DL platforms.

Requirements:

• 3 years of hands-on experience in building ML models deployed into real-world business applications or research.
• Good understanding of ML/DL framework such as Jupyter Notebook, Anaconda, Tensorflow, Keras, Scikit-Learn, PyTorch, MXNet, etc.
• Experience working with cloud services platform (AWS or Azure) to build ML/DL pipelines; training (GPU CUDA), evaluating, deploying (SageMaker, Docker container).
• Proficiency with Python and basic libraries for ML such as scikit-learn and pandas
• Strong working knowledge of ML/DL algorithms (classification, regression, clustering, hyperparameter tuning, etc).
• Experience in working with LLM for text and image generation

Preferred:

• Having a working knowledge of AI agents is nice to have
• Experience with Image Processing/Computer Vision is nice to have
• Experience with Continuous Integration and Continuous Delivery(CI/CD) is nice to have
• We will also factor in relevant certifications (e.g., AWS, Azure, Coursera)