Job Duties and Responsibilities:

• Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
• Transforming data science prototypes and applying appropriate ML algorithms and tools.
• Ensuring that algorithms generate accurate user recommendations.
• Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
• Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
• Developing ML algorithms to analyze huge volumes of historical data to make predictions.
• To study and convert data science prototypes.
• To design and develop Machine Learning systems and schemes.
• To perform statistical analysis and fine-tune models using test results.
• To find available datasets online for training purposes.
• To train and re-train ML systems and models as and when necessary.
• To extend and enrich existing ML frameworks and libraries.
• To develop Machine Learning apps according to customer/client requirements.
• To research, experiment with, and implement suitable ML algorithms and tools.
• To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by their success probability.
• To explore and visualize data for better understanding and identify differences in data distribution that could impact model performance when deploying it in real-world scenarios.
• Robust data modelling and data architecture skills.

Technologies Involved / Skills required for the position:

Pandas, NumPy, ScikitLearn, TensorFlow, ML Flow, Model Registry, Feature Store, AWS, GCP, AWS - Hadoop Ecosystem (HDFS, MapReduce, Spark, Scoop, Hive, Presto), Python, UNIX Shell Scripting, LINUX, Autosys, PySpark, SQL Server, Oracle, MYSQL, Teradata, Hue, Mercurial, DB Visualizer, Tableau, MS Excel, GIT, JIRA and Confluence