- 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.
- 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.
- Experience with StorageGrid, DBT, and Sagemaker is a plus.
- Familiarity with Snowpark, APIs, Talon Batch, Kafka, and graph-based models.
- Knowledge of building databases on Snowflake would be advantageous.
- If you possess the required skills and are passionate about AI engineering, we encourage you to apply and join our team of talented professionals driving innovation in AI.
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Artificial Intelligence Engineer - San Antonio, United States - Fractal
Description
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 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. 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
Required Qualifications
Good to Have
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