AI Engineer

Fractal Analytics•Texas, TX

1d•$120,000 - $130,000

About The Position

As an AI Engineer at Fractal, you will develop and deploy AI models using Python and design, implement, and maintain data pipelines for ETL, model scoring, performance monitoring, data offloading, scheduling, and automation. You will use SQL to support AI model development and optimization, and work with cross-functional teams to integrate AI solutions into existing infrastructure and workflows. The role involves workflow orchestration and automation, version control and CI/CD activities, and working with data storage and processing technologies including Snowflake and Hadoop-related tools.

Requirements

Demonstrable experience developing and deploying AI models using Python.
Extensive knowledge of SQL for complex data manipulation, querying, and analysis.
Experience designing and maintaining data pipelines for ETL, model scoring, performance monitoring, and data offloading.
Proficiency with workflow tools such as Airflow, Domino, and Control-M.
Experience with version control systems such as GitLab or Git, and understanding of CI/CD pipeline activities.
Knowledge of Snowflake, Cloudera, Hadoop, HDFS, and Hive.
Ability to work effectively with cross-functional teams to integrate AI solutions into company infrastructure and workflows.
Strong analytical and problem-solving skills for complex data and AI model deployment challenges.

Nice To Haves

Experience with StorageGrid, DBT, and SageMaker.
Familiarity with Snowpark, APIs, Talon Batch, Kafka, and graph-based models.
Knowledge of building databases on Snowflake.

Responsibilities

Develop and deploy AI models using Python.
Design, implement, and maintain data pipelines for ETL, model scoring, performance monitoring, data offloading, job scheduling, and automation.
Use SQL for data manipulation, querying, and analysis to support AI model development and optimization.
Collaborate with cross-functional teams to integrate AI solutions into existing infrastructure and workflows.
Use tools such as Airflow, Domino, and Control-M for workflow orchestration, scheduling, and automation.
Manage code using GitLab or Git and participate in CI/CD pipeline activities.
Work with Snowflake, Cloudera, Hadoop, HDFS, and Hive for data storage, retrieval, and processing.