Job Description

As a full-stack MLengineer, your primary responsibility is to develop production-grade datascience solutions.

This requiresexpertise in all phases of the ML life cycle.

Requirements

To be successful in this role

• You must have knowledge and hands-on experience with a variety of ML algorithms.
• Proficient in using data science platforms like SageMaker.
• Experience with orchestration tools like Airflow or similar tools.
• Highly skilled in programming languages like Python, SQL and Spark.
• Additionally, you should be capable of driving the project independently and have the ability to mentor and train other members of the team to achieve the project goals.
• You should be flexible and equipped to pick to build AI product in Consumer space like Personalization and Demand Forecasting.