Mandatory Skills are:
AWS machine learning services(AWS machine learning services)
data science SaaS tools (Dataiku, Indico, H2O.ai, or similar platforms)
knowledge of AWS data engineering services (S3, Glue, Athena, Lambda)
Python and common data manipulation libraries
Experience:
5+ years of experience in machine learning engineering or a related field.
Technical Skills:
* Programming Languages: Proficient in Python and experience with other languages (e.g., Java, Scala, R) is a plus.
* Machine Learning Libraries: Strong experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Keras, etc.
* Data Processing: Experience with data manipulation and processing using libraries like Pandas, NumPy, and Spark.
* Model Deployment: Experience with model deployment frameworks and platforms (e.g., TensorFlow Serving, TorchServe, Seldon, AWS SageMaker, Google AI Platform, Azure Machine Learning).
* Databases: Experience with relational and NoSQL databases (e.g., SQL, MongoDB, Cassandra).
* Version Control: Experience with Git and other version control systems.
* DevOps: Familiarity with DevOps practices and tools.
* Strong understanding of machine learning concepts and algorithms: Regression, Classification, Clustering, Deep Learning etc.
* Soft Skills:
* Excellent problem-solving and analytical skills.
* Strong communication and collaboration skills.
* Ability

Keyskills: AWS machine learning services SAAS Dataiku Aws Sagemaker Athena S3 Glue google AI plateform Lambda Aws indico Python