Associate AI/Machine Learning Engineer

Role Overview

We are hiring an Associate AI / Machine Learning Engineer (Proof of Concept) to design and deliver hands-on AI/ML experiments using MySQL HeatWave and HeatWave ML. This early-career role is ideal for new graduates or technologists with a foundation in SQL and programming, basic ML knowledge, and a strong desire to learn; you will work with real operational data and be mentored by internal engineers and partners (Oracle, Domo) to produce reproducible, demo-ready POCs that generate actionable predictions and insights.

Key Responsibilities

• POC Design and Delivery Build an end-to-end ML proof of concept in MySQL HeatWave covering data ingestion, feature engineering, model training, evaluation, and inference.
• In-Database Modeling Leverage HeatWave ML where appropriate and evaluate tradeoffs between in-database and external model workflows.
• Integration and Automation Develop lightweight Python and/or PHP scripts or services to automate data flows, run experiments, and serve inference results.
• Feature Engineering and Evaluation Explore datasets, create features, compare model approaches for regression, classification, and forecasting, and produce clear evaluation metrics.
• Partner Collaboration Work closely with Oracle, Domo, and internal subject matter experts to absorb best practices and translate them into repeatable implementations.
• Documentation and Communication Produce architecture diagrams, assumptions, limitations, evaluation results, and an executive summary that communicates business impact.
• Productionization Roadmap Deliver a pragmatic recommendation for next steps including cost estimates, scalability considerations, security and compliance risks, and a prioritized implementation plan.

Required Qualifications:

• Experience: 0–2 years of professional experience or equivalent hands-on projects, internships, or academic work.
• Machine Learning Fundamentals: Practical or academic exposure to supervised learning and time series forecasting; familiarity with basic model evaluation metrics.
• Databases: Strong SQL skills and comfort with relational data concepts.
• Programming: Proficiency in Python for data workflows; familiarity with PHP is a plus.
• Mindset: Demonstrated curiosity, ability to learn quickly, and willingness to seek mentorship and iterate.
• Communication: Ability to document technical work clearly and present findings to both technical and nontechnical stakeholders.
• Independence: Able to run experiments, troubleshoot issues, and deliver a demo-ready POC with guidance from senior engineers.

Preferred Qualifications:

• HeatWave ML: Prior exposure to HeatWave ML or other in-database analytics platforms.
• Domain Experience: Background in SaaS, logistics, operational analytics, or enterprise systems (SAP, ERP, WMS).
• Cloud Familiarity: Experience with OCI, AWS, or GCP for data pipelines and deployment planning.
• POC Operationalization: Experience or coursework that demonstrates understanding of moving POCs toward production, including cost modeling and monitoring.
• Security Awareness: Basic understanding of data security, access controls, and compliance considerations for operational data.

ShipERP is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or other protected category.