Job Description

• Design & implement ML/DL solutions and integrate them with various Big Data platforms and architectures.
• Creating and Maintain Machine Learning pipelines that are scale-able, robust, and ready for production.
• Collaborate with domain experts, software developers, and data scientists.
• Troubleshoot ML/DL model issues, including recommendations for retraining, re-validate, 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 Machine Learning / Deep learning frameworks such as Jupyter Notebook, Anaconda, Tensorflow, Keras, Scikit-Learn, PyTorch, MXNet, etc.
• Experience working with cloud services platform (AWS or GCP) to build ML/DL pipelines; training (GPU CUDA), evaluating (Tensorboard), deploying (SageMaker, Docker container).
• Proficiency with Python, R, and basic libraries for machine learning such as sci-kit-learn and pandas
• Strong working knowledge of ML/DL algorithms (classification, regression, clustering, hyperparameter tuning, etc).
• Experience in model compression or quantization for on-edge-device inference
• Proficiency with Open CV
• Experience with Image Processing/Computer Vision
• We will also factor in relevant certifications (e.g., AWS, Coursera)
• Experience with Continuous Integration and Continuous Delivery(CI/CD)