AWS Machine Learning Engineer

• Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
• Exploring, analyzing and visualizing data to gain an understanding of it.
• Maintaing Data quality on different type of datasets.
• Supervising the data acquisition process if more data is needed
• Defining Model validation strategies
• Defining the preprocessing or feature engineering to be done on a given dataset
• Data augmentation pipelines
• Training models and tuning their hyperparameters
• Analyzing the errors of the model and designing strategies to overcome them.
• Defining the A/B testing setups.
• Deploying and maintaining the MLOps pipelines.

Technical Expertise:

• Hands on experience on TensorFlow, PyTorch, Keras, Caffe,Supervised Machine Learning Algorithms,Deep Learning Models (CNN, RNN, LSTM, BERT, NLU and YOLO), Cloud Platforms (AWS/GCP)
• Experience in Data Wrangling and PySpark(Good to have knowledge over EMR and Glue)
• Excellent skills developing in Python as well as significant experience working in a Linux environments.
• Experience with containerizing applications using Docker
• Experience in SQL and at least one NoSQL data store Elasticsearch, MongoDB, Cassandra, HBase
• Experience in handling branch based deployments.

Good to Have:

Knowledge over MLFlow and Kubeflow.

Optimization of Multipe GPUs..