MLOps Engineer

Velvetech; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Velvetech seeks a middle-level MLOps Engineer to manage end-to-end ML operations, focusing on deploying and optimizing LLM models for marketplace tasks. You will develop and optimize MLOps pipelines, automating workflows for model training, deployment, and monitoring.

Your role will involve managing data pipelines and ensuring efficient preparation of training data, which is critical for successful model performance.

Qualifications

• Middle-level MLOps engineer experience in deploying and optimizing ML workflows.
• Strong experience with cloud services and ML pipelines.
• Familiarity with LLMOps and open-source LLM tooling such as vLLM and BentoML.

Responsibilities

• Develop and optimize end-to-end MLOps pipelines for training, deployment and monitoring.
• Automate workflows for model training, deployment and monitoring and manage data pipelines.
• Prepare training data and maintain data quality for model performance.
• Focus on LLMOps, deploying and fine-tuning open-source LLM models to support marketplace tasks.

Skills

MLOps

LLMOps

Cloud services

Model deployment

Data pipelines

Model monitoring

Open-source LLMs

Tools

vLLM

BentoML

Job description

Velvetech seeks a middle-level MLOps Engineer to manage end-to-end ML operations, focusing on deploying and optimizing LLM models for marketplace tasks. Ideal candidates have strong experience with cloud services and MLOps pipelines.

As an MLOps Engineer at Velvetech, you will be responsible for developing and optimizing MLOps pipelines, automating workflows for model training, deployment, and monitoring. Your role will involve managing data pipelines and ensuring efficient preparation of training data, which is critical for successful model performance.

You will also focus on LLMOps, deploying and fine-tuning open-source LLM models using tools like vLLM and BentoML. Your efforts will directly contribute to building AI solutions for marketplace optimization, including dynamic price modeling and product data enrichment, which are essential for driving business value.