Lead AI Engineer

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. 

Please visit Fractal | Intelligence for Imagination for more information about Fractal. 

Role Overview 
As Lead AI Engineer at Fractal, a company committed to integrating artificial intelligence in decision-making across Fortune 500 companies, you will develop and deploy AI models using advanced Python programming. You will design and maintain data pipelines for a range of processes including ETL, model scoring, and performance monitoring, and work collaboratively with cross-functional teams to ensure AI solutions are effectively integrated into the existing infrastructure. This role requires a deep understanding of SQL, workflow orchestration tools like Airflow, and data storage technologies such as Snowflake and Hadoop, positioning you at the forefront of AI innovation and application in a dynamic corporate environment. 

Responsibilities 

• Develop and deploy AI models leveraging a strong background in Python programming. 

• Design, implement, and maintain data pipelines for various purposes, including ETL processes, model scoring, model performance monitoring, data offloading, job scheduling, and automation. 

• Utilize 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. 

• Familiarize with and utilize tools such as Airflow, Domino, and Control-M for workflow orchestration, scheduling, and automation. 

• Manage codebase using version control systems like Gitlab (or Git) and participate in CI/CD pipeline activities. 

• Work with data storage technologies such as Snowflake, Cloudera, Hadoop, HDFS, and Hive for data storage, retrieval, and processing. 

• Skills Needed: 

• Strong Python background with demonstrable experience in AI and machine learning. 

• Good knowledge of SQL for data manipulation, querying, and analysis. 

• Experience with designing and implementing data pipelines for various purposes, including ETL, model scoring, and automation. 

• Familiarity with Airflow, Domino, Control-M, Snowflake, Gitlab (or Git in general), and CI/CD Pipelines. 

• Understanding of Cloudera, Hadoop, HDFS, and Hive for big data processing and storage. 

Required Qualifications 

• Strong Python Skills: Demonstrable experience in developing and deploying AI models using Python. 

• Proficiency in SQL: Extensive knowledge in SQL for complex data manipulation, querying, and analysis essential for AI model development and optimization.