- Company Name
- Acosta Group
- Job Title
- AI/Machine Learning Data Engineer
- Job Description
-
Job title: AI/Machine Learning Data Engineer
Role Summary: Design, develop, deploy, and support AI‑powered solutions on Azure and related enterprise platforms. Build and maintain models, APIs, and reusable components, ensuring scalability, reliability, and compliance. Act as a technical mentor and second‑/third‑level support for business users and citizen developers.
Expectations:
• Deliver production‑ready AI/ML models and intelligent automation workflows.
• Provide knowledgeable support and guidance to cross‑functional teams.
• Participate in AI Center of Excellence activities, driving governance and best practices.
• Ensure infrastructure readiness, performance monitoring, and responsible AI compliance.
Key Responsibilities:
- Design, develop, and deploy AI/ML models, embeddings, and vector databases.
- Build REST/GraphQL APIs to expose AI services.
- Integrate Azure AI, Power Platform AI Builder, Copilot Studio, Power Apps, Power Automate.
- Deploy models via Azure Functions, Databricks, Docker/Kubernetes, CI/CD pipelines.
- Monitor production AI solutions for performance, reliability, and responsible AI.
- Provide 2nd/3rd level support for incidents, enhancements, and deployments.
- Collaborate with infrastructure, security, and operations teams for readiness and compliance.
- Develop reusable AI templates, components, and frameworks.
- Mentor business users and citizen developers in AI solution building.
- Evaluate new AI tools, platforms, and methodologies for innovation.
- Document architecture, workflows, and best practices.
- Maintain change control and operational standards.
- Support AI Center of Excellence governance and enterprise AI strategy.
Required Skills:
- Proficient in Python (essential) and SQL.
- Cloud experience (preferably Azure) with Azure AI, Azure Functions, Azure DevOps.
- Knowledge of agentic frameworks (e.g., LangChain).
- Expertise in Large Language Models, fine‑tuning, Retrieval‑Augmented Generation (RAG).
- Experience with vector databases, semantic search, dimensional modeling.
- Familiarity with Databricks, Docker, Kubernetes, CI/CD.
- Understanding of MLOps, model lifecycle management, and monitoring.
- Awareness of responsible AI principles.
Required Education & Certifications:
- Bachelor’s degree in Technology, Computer Science, or equivalent work experience.
- Minimum 2 years professional experience in Machine Learning, Data Science, or Software Engineering.
- Microsoft AI‑102 exam (preferred).