Babcock & Wilcox

Junior AI Developer - Data Engineering Emphasis

Junior AI Developer - Data Engineering Emphasis
Notice info
LocationAkron, OH
On-site
Renewable Energy Power Generation

About This Job

We are seeking a Junior AI Developer with a strong interest in artificial intelligence and data engineering, particularly within the Microsoft ecosystem. This role is ideal for someone who enjoys working with data, building intelligent applications, and learning how to operationalize AI solutions using Azure technologies.

- Assist in developing and deploying AI models using Azure Machine Learning, Azure Cognitive Services, and Azure OpenAI.

- Support data engineering tasks such as data ingestion, transformation, and pipeline development using Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.

- Collaborate with software engineers and data scientists to integrate AI models into Microsoft-based applications (e.g., .NET, Power Platform).

- Participate in model evaluation, performance tuning, and responsible AI practices.

- Contribute to documentation, testing, and version control using Azure DevOps and GitHub.


Qualifications


Required Qualifications

- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience).

- Familiarity with Microsoft Azure, especially services like Azure Machine Learning, Azure Cognitive Services, or Azure Data Factory.

- Proficiency in Python and/or C#, with experience using libraries such as scikit-learn, TensorFlow, or ML.NET.

- Basic understanding of data pipelines, ETL processes, and structured/unstructured data handling.

- Experience with Visual Studio, VS Code, or Azure Data Studio.

- Strong analytical, communication, and collaboration skills.


Preferred Qualifications

- Exposure to Azure Synapse, Azure Databricks, or Power BI.

- Experience with Power Platform tools (Power Apps, Power Automate) for AI integration.

- Familiarity with GitHub Copilot, Azure AI Studio, or Azure OpenAI Service.

- Understanding of data governance, model monitoring, and responsible AI principles.

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