Lead AI ML Engineer

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Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Proficiency in SQL and Python.
• Experience with data integration tools like Airbyte.
• Strong knowledge of data warehousing concepts and hands-on experience with Snowflake.
• Experience with data transformation tools such as dbt.
• Proficiency in using Databricks and Apache Spark for big data processing and machine learning.
• Familiarity with Delta Lake for data lake management.
• Experience with data visualization tools like Tableau.
• Experience with relational databases like MySQL and PostgreSQL.
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork abilities.
• Ability to work in a fast-paced and dynamic environment.

Responsibilities:

• Design, develop, and deploy machine learning models using Databricks and Apache Spark.
• Implement data preprocessing, feature engineering, and model training pipelines.
• Utilize dbt to transform and model data in Snowflake to prepare datasets for machine learning.
• Use SQL and Python to analyze large datasets, derive meaningful insights, and build training datasets.
• Conduct exploratory data analysis to identify trends, patterns, and anomalies.
• Develop and maintain ETL pipelines using Airbyte to ingest data from various sources into Snowflake.
• Manage and optimize data storage and retrieval using Delta Lake on Databricks to ensure efficient access for ML models.
• Create and maintain interactive dashboards and visualizations in Tableau to communicate model results and insights to stakeholders.
• Collaborate with data scientists to refine and improve machine learning models.
• Monitor and evaluate the performance of deployed models, ensuring they meet accuracy and performance standards.
• Work with relational databases such as MySQL and PostgreSQL for data storage and management as needed.
• Communicate complex technical concepts and results to non-technical stakeholders effectively.