Senior ML Engineer: LLMOps & Production Systems

Bain & Company; Houston (TX); Hybrid; USD 148,000 - 162,000; Full time

Job summary

Bain & Company is seeking a Senior ML Engineer to own production ML systems, deployment, and LLMOps. You will collaborate with Data Scientists, Data Engineers, and the Agent/AI squad to deliver reliable model and retrieval services across platforms in a hybrid work environment.

This role focuses on building scalable inference services, governance for model lifecycles, and robust monitoring with OpenTelemetry and Prometheus, ensuring fidelity and efficiency in production.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Machine Learning, Data Science, Statistics, or related field.
• 6+ years of experience building and operating production ML systems.
• Experience owning the model and prompt lifecycle end‑to‑end (packaging, registry, promotion, rollout, monitoring, rollback).
• Experience building production RAG or retrieval systems end‑to‑end, including embedding and retrieval and evaluation.
• Collaborative work with Data Science, Data Engineering, and Product teams to ship ML capabilities.
• Strong Python for production ML with production-grade code (tests, linting, typing).

Responsibilities

• Core ML Systems Deployment, Serving, and Operations (80%).
• Own the model and prompt lifecycle in MLflow from packaging to rollback.
• Build and maintain LLMOps tooling for versioning, config, and caching.
• Develop production RAG and retrieval pipelines end‑to‑end.
• Design evaluation frameworks and monitoring for drift and latency.
• Collaborate with Agent/AI squads to serve outputs into agent workflows.

Skills

Python

MLflow

LLMOps

Cloud platforms

Docker

Kubernetes

LangChain

LlamaIndex

Education

Bachelor’s degree in Computer Science or related field

Tools

Databricks

AWS

LangChain

LlamaIndex

Prometheus

OpenTelemetry

Job description

Bain & Company is seeking a Senior ML Engineer to own production ML systems, deployment, and LLMOps. You will collaborate with Data Scientists, Data Engineers, and the Agent/AI squad to deliver reliable model and retrieval services across platforms in a hybrid work environment.

This role focuses on building scalable inference services, governance for model lifecycles, and robust monitoring with OpenTelemetry and Prometheus, ensuring fidelity and efficiency in production.