Senior ML Engineer – Scalable AI Platforms & RAG

4P Consulting Inc.; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

4P Consulting Inc. seeks a senior Machine Learning Engineer III to build scalable AI products for enterprise deployment. The role emphasizes Retrieval-Augmented Generation, multi-agent systems, NLP, and model deployment on Azure or Google Cloud platforms.

Responsibilities include building modular AI components, coordinating with MLOps and data teams, and ensuring security and observability across products. The ideal candidate has hands-on AI/ML experience and strong software engineering skills.

Qualifications

• Proven experience delivering production-grade AI/ML solutions.
• Hands-on work with RAG architectures, LLM apps, multi-agent systems, and NLP.
• Experience with Azure AI services, GCP AI services, or Azure ML.
• Proficiency in Python and ML frameworks (PyTorch, Transformers, LangChain).
• Experience deploying scalable AI services in cloud environments.

Responsibilities

• Design modular, reusable AI components and services.
• Develop scalable RAG solutions from structured and unstructured data.
• Engineer multi-agent systems for task coordination and automation.
• Build NLP pipelines for customer-interaction analysis.
• Develop and fine-tune models using PyTorch, Transformers, or LangChain.
• Package and deploy models using Azure ML, GCP, or Databricks.
• Integrate Databricks for data ingestion, feature engineering, and experiments.
• Create reusable libraries, APIs, templates, and patterns.
• Collaborate with MLOps, DevOps, data engineering, and product teams.
• Implement monitoring for model performance, drift, and reliability.
• Ensure AI solutions meet security, privacy, compliance, and observability requirements.

Skills

Production-grade AI

RAG architectures

LLM applications

Python

PyTorch

Tools

Azure ML

Google Cloud

Databricks

APIs

Job description

4P Consulting Inc. seeks a senior Machine Learning Engineer III to build scalable AI products for enterprise deployment. The role emphasizes Retrieval-Augmented Generation, multi-agent systems, NLP, and model deployment on Azure or Google Cloud platforms.

Responsibilities include building modular AI components, coordinating with MLOps and data teams, and ensuring security and observability across products. The ideal candidate has hands-on AI/ML experience and strong software engineering skills.