(Level Middle-Senior)
Job Description:
- Translate and refine business goals into appropriate machine learning objectives.
- Design and implement ML/DL solutions and integrate them with various Big Data platforms and architectures.
- Create and maintain ML pipelines that are scalable, robust, and ready for production.
- Collaborate with domain experts, software developers, and data scientists.
- Troubleshoot ML/DL model issues, including recommendations for retrain, re-validate, and improvements/optimization.
- Leading model algorithm building (from training models, tuning hyperparameter), model registry and also model deployment and CI/CD pipeline in predictive modelling projects.
Requirements:
- 2+ years of hands-on experience in building ML models deployed into real-world business applications or research.
- Good understanding of Machine Learning / Deep learning framework such as Jupyter Notebook, Anaconda, Tensorflow, Keras, Scikit-Learn, PyTorch, MXNet, etc.
- Proven track-record in building large-scale, high-throughput, low-latency production systems
- Experience building data stream processes
- Ability to implement CI/CD and TDD
- Experience working with cloud services platform (AWS or GCP) to train models and model deployment
- Strong working knowledge of ML/DL algorithms (classification, regression, clustering, hyperparameter tuning, etc).
- Experience in model compression or quantization for on-edge-device inference
Preferred
- Experience in ML experiment tracking tools (e.g. MLFlow, WandB, Neptune, TensorBoard).
- Relevant certifications in machine learning and cloud technologies (e.g., AWS, Coursera) would be a plus.
