AI Engineer

About the role

As an 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.

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

• 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.
• Data Pipeline Design and Implementation: Experience in designing and maintaining robust data pipelines for ETL processes, model scoring, model performance monitoring, and data offloading.
• Workflow Orchestration Tools: Proficiency with tools such as Airflow for workflow scheduling and Domino and Control-M for task automation and management.
• Version Control and CI/CD: Skilled in using version control systems like GitLab or Git, with an understanding of Continuous Integration and Continuous Deployment pipeline activities.
• Data Storage Technologies: Knowledge of data storage and processing technologies such as Snowflake, Cloudera, Hadoop, HDFS, and Hive.
• Cross-Functional Collaboration: Ability to work effectively with cross-functional teams to integrate AI solutions into existing company infrastructure and workflows.
• Problem Solving: Strong analytical and problem-solving skills with a capacity to handle complex challenges in data and AI model deployment environments.

Qualifications (Nice to Have)

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

Pay

A reasonable estimate of the current range is: $120,000–$130,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.

Benefits

• Eligible to participate in health, dental, vision, life insurance, and disability plans on the first day of employment.
• Eligible to participate in the Company 401(k) Plan after 30 days of employment.
• 11 paid holidays and 12 weeks of Parental Leave.
• “Free time” PTO policy for sick time or vacation.