MLOps Engineer: Deploy & Scale AI Pipelines

CliftonLarsonAllen LLP; Kansas City (MO); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Flexible PTO

Parental leave (up to 12 weeks)

Volunteer Time Off

Mental health coverage

Wellness stipend

Fertility benefits

Job summary

CLA, CliftonLarsonAllen LLP, is seeking a skilled Machine Learning Operations Engineer to join our Data Science Team. You will help design, deploy, and monitor ML models within a collaborative environment that values curiosity and growth.

You will work with data scientists and engineers to integrate pipelines, maintain automated workflows, and ensure scalable, secure ML infrastructure. This role offers growth in a top national professional services firm.

Qualifications

• Bachelor's degree is required.
• 2+ years' experience as a Data/ML Engineer.
• Experience collaborating with data scientists and engineers.

Responsibilities

• Assist with design and development of MLOps infrastructure for deployment, management, and monitoring of ML models.
• Collaborate with data scientists and engineers to ensure seamless integration of data science and engineering processes.
• Support maintenance of automated workflows and pipelines for efficient model deployment and monitoring.
• Troubleshoot and resolve issues with model performance, data pipelines, or infrastructure.
• Ensure security and scalability of MLOps infrastructure for large data volumes and models.
• Maintain documentation for MLOps processes and systems.
• Collaborate with cross-functional teams to translate business needs into technical requirements.
• Ensure compliance with data security and privacy regulations.

Skills

Python

SQL

Data pipeline design

ML model deployment

Monitoring & observability

DevOps fundamentals

CI/CD concepts

Education

Bachelor's degree

Tools

Jenkins

Git

Perforce

CI/CD tooling

AWS

Azure

GCP

Job description

CLA, CliftonLarsonAllen LLP, is seeking a skilled Machine Learning Operations Engineer to join our Data Science Team. You will help design, deploy, and monitor ML models within a collaborative environment that values curiosity and growth.

You will work with data scientists and engineers to integrate pipelines, maintain automated workflows, and ensure scalable, secure ML infrastructure. This role offers growth in a top national professional services firm.