Senior AI/ML Engineer: Production ML & RAG Systems Lead

Bain & Company; Atlanta (GA); Hybrid; USD 141,000 - 154,000; Full time

Job summary

Bain & Company in Atlanta is seeking a Senior ML Engineer to lead production ML systems, embedding/pipeline work, and LLMOps. You will own the model and prompt lifecycle, collaborate with data science and engineering teams, and help scale Bain’s proprietary data and software solutions for private equity clients.

The role emphasizes production readiness, observability, and cross-functional collaboration in a hybrid work environment with at least one day in the office per week.

Qualifications

• Bachelor’s degree in CS, Engineering, ML, DS, or a related field.
• 6+ years of experience building and operating production ML systems.
• Experience owning the model and prompt lifecycle end-to-end (packaging, registry, rollout, monitoring).
• Experience building/operating production RAG or retrieval systems end-to-end.
• Strong Python and production-grade coding standards.

Responsibilities

• Build, deploy, and operate production inference and serving systems for models, embeddings, and re-rankers.
• Own the model and prompt lifecycle in MLflow: packaging, registry governance, promotions, rollout, rollback.
• Build and operate LLMOps tooling and retrieval pipelines end-to-end.
• Design and maintain evaluation frameworks and monitoring dashboards.
• Mentor engineers on production ML and LLMMOps best practices.

Skills

Strong Python for production ML

Ownership of model and prompt lifecyle

RAG/retrieval systems experience

Production ML monitoring/observability

Mentoring mid-level engineers

Education

Bachelor’s degree in CS/Engineering/ML/DS/Statistics

Tools

Docker

Kubernetes

MLflow

Databricks/AWS cloud platforms

Job description

Bain & Company in Atlanta is seeking a Senior ML Engineer to lead production ML systems, embedding/pipeline work, and LLMOps. You will own the model and prompt lifecycle, collaborate with data science and engineering teams, and help scale Bain’s proprietary data and software solutions for private equity clients.

The role emphasizes production readiness, observability, and cross-functional collaboration in a hybrid work environment with at least one day in the office per week.