- Prepare training data, conduct feature engineering, both from internal and external sources
- Apply Machine learning in Production: support to design and implement scalable and user-friendly Machine Learning infrastructure, model tuning, and monitoring
- Design and build fast, reliable services for Machine Learning model: training, serving, and scaling Machine Learning infrastructure
- Build Machine Learning pipeline for various classification and decision problems using a variety of algorithms.
- Undergraduate or hold Bachelor’s degree in Information Technology or comparable qualification
- Familiar with Object-Oriented Programming, Modular Programming
- Familiar with conventional Machine Learning and Deep Learning packages: Pandas, Numpy, Scikit-learn, Pytorch or Tensorflow
- Experience working with Computer Vision tasks and related frameworks / open sources such as OpenCV, YOLOv4 or v5
- Experience with serving and storage platforms: such as Docker, Ceph
- Experience with cloud services: such as AWS or GCP
- Experience with MLOps frameworks such as Airflow, MLFlow, Kedro
Good to have:
- Experience with building and maintaining high availability, low latency systems, especially with respect to reliability, testing, and observability.
- Familiar with the full life cycle of software development