Machine Learning Engineer I

Harris Brand•St Paul, MN

12h•$71,079 - $106,618•Hybrid

About The Position

We are seeking a Machine Learning Engineer I (MLE) to join our Business Intelligence team. In this entry-level role, the MLE will primarily assist with building and maintaining data structures to support ongoing AI initiatives and related administrative tasks. The MLE will work under the guidance of the Data Scientist and peer Database Developer, helping with the organization and management of databases, preparation of data for analytics, and routine administrative responsibilities. As part of the team, the MLE will gain hands-on experience in modern data systems and cloud environments while supporting broader digital transformation objectives. This is a hybrid-remote position, which may be based out of our corporate headquarters in St. Paul, MN, or one of our regional offices. Fully remote work arrangement may be considered for highly qualified candidates.

Requirements

Bachelor’s degree in Computer Science or a related technology (required); advanced degree preferred
Hands-on experience with at least one ERP system, such as CMIC, COINS OA, IFS, SAP, or Microsoft Dynamics
Strong experience with vector databases, big data tools (e.g., Spark), and data visualization and reporting platforms including Power BI and SSRS
Demonstrated competency in LLM and Retrieval-Augmented Generation (RAG) development
Solid understanding of Azure resources and Azure SQL administration
Proficiency in programming and data querying, including SQL and Python
Proven knowledge of data structures and advanced SQL concepts
Experience with ETL processes and pipelines, including data ingestion, transformation, and integration across enterprise systems
Track record of diagnosing, analyzing, and resolving business process issues and translating technical solutions into meaningful business outcomes
Authorization to work in the US without sponsorship is required.

Responsibilities

Build and maintain strong technical knowledge of enterprise software platforms, including CMiC, WennSoft, Adaptive, and Salesforce
Work with front-end user interfaces to improve usability and workflows
Understand back-end database structures, including schemas and ERDs
Contribute to the design, development, and ongoing enhancement of machine learning models
Perform feature engineering on data from multiple sources
Train, evaluate, and deploy models for real-world business applications
Develop visualizations and dashboards to effectively communicate insights to stakeholders
Implement and integrate generative AI solutions
Fine-tune generative AI models using domain-specific data
Build systems and pipelines that connect AI outputs to internal applications, such as chatbots
Write and maintain code under the direction of a Data Scientist and peer Database Developer
Identify and resolve bugs, and complete break/fix tasks promptly
Follow established software development lifecycle methodologies
Adhere to company coding standards and industry best practices
Collaborate within a version-controlled development environment
Continuously enhance coding skills and technical knowledge
Maintain large relational data sets across SQL and other databases
Perform SQL Server and SSMS DBA administration, including permissions, backups, and other maintenance tasks
Work with data warehouse and data lake platforms, including Snowflake and Azure
Monitor and audit data flows between databases and other applications
Assist with data migration efforts
Troubleshoot and resolve data quality and performance issues
Stay current on process improvement and technology trends that could enhance company operations
Recommend practical solutions to leadership to improve efficiency and effectiveness
Maintain relevant knowledge through seminars, trade shows, industry publications, certifications, and other learning opportunities
Keep up-to-date on project management, process improvement, and change management methodologies and best practices