Production ML Engineer: LLMs, RAG & MLOps on GCP

DeepHow; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

DeepHow is seeking an AI Engineer to own our AI pipeline end-to-end, taking over the production ML stack, harden it, and ship improvements fast. Day one, your focus is MLOps and production deployment making sure our models are fast, reliable, and cost-efficient at scale.

This is a build-and-ship role, not research. If you like turning prototypes into production systems that real users depend on, read on.

Qualifications

• 3–7+ years shipping ML/AI in production.
• Strong Python; PyTorch or TensorFlow.
• Hands-on with LLMs: prompting, fine-tuning, RAG, evals.
• MLOps: CI/CD for models, monitoring, cost optimization.
• Experience deploying on GCP or AWS (GCP preferred).
• Comfort with vector DBs, embeddings, and retrieval systems.

Responsibilities

• Deployment and scaling of LLM, VLM, and speech models in production (GCP).
• Latency, cost, and reliability optimization across the stack.
• RAG pipelines, prompting, and evaluation frameworks.
• Infrastructure and tooling to accelerate experimentation and shipping.

Skills

Production ML in production

Python

PyTorch or TensorFlow

LLMs prompting/fine-tuning/RAG

MLOps CI/CD monitoring

GCP or AWS deployment

Vector DBs embeddings retrieval

Education

Bachelor’s or Master’s in CS/Engineering or related field

Tools

GCP

AWS

VectorDBs

PyTorch

TensorFlow

Job description

DeepHow is seeking an AI Engineer to own our AI pipeline end-to-end, taking over the production ML stack, harden it, and ship improvements fast. Day one, your focus is MLOps and production deployment making sure our models are fast, reliable, and cost-efficient at scale.

This is a build-and-ship role, not research. If you like turning prototypes into production systems that real users depend on, read on.