Machine Learning Engineer (AWS, Sagemaker)

1.Understanding of Natural Language Processing (NLP), Natural Language
2.Understanding (NLU) and Natural Language Generation (NLG)
3.Develop and implement technical efforts to design, build, and deploy AWS ML models at the direction of lead architects, including large-scale data processing, computationally intensive statistical modelling, and advanced analytics
4.Familiarity with deep learning, machine learning and NLP/NLG frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.)
5.Should have experience in AWS services such as SageMaker,
Elasticsearch, and general knowledge of AWS architecture & other services
6.Ability to write robust code in Python, Java and R
7.Experience optimizing model hyperparameter tuning for speed and cost
8.Experience in building MLOps pipeline using MLOps frameworks like Kubeflow, MLFlow, and DataRobot
9.Experience with Docker and Kubernetes
10. Familiarity with Eventbridge and AWS step function for workload orchestration
11.Experience with Agile Development.