Remote ML Ops Engineer — Cloud Pipelines & MLflow

PAR Technology; Illinois; Remote; USD 120,000 - 170,000; Full time

Job summary

PAR Technology seeks an ML Ops Engineer to partner with a data science team, moving models from notebooks to monitored production. You will build pipelines, tune Spark jobs, wire CI/CD, and improve tests and documentation as part of a cloud-native, data-intensive SaaS environment on AWS.

The role emphasizes collaboration across teams, strong ownership, and the ability to adapt in a fast-moving setting, with exposure to MLflow, Terraform, Docker, and Databricks Workflows.

Qualifications

• Production data/ML systems experience with a CS-related degree or equivalent practical experience.
• Strong ownership, curiosity, and ability to work across cross-functional teams.
• Experience with CI/CD for data/ML pipelines and testing frameworks.
• Familiarity with Airflow, Databricks Workflows, and model registries.

Responsibilities

• Build and maintain automated data/ML pipelines in collaboration with teams.
• Tune Spark jobs, optimize CI/CD, and improve test coverage and observability.
• Implement data quality checks and lineage tracking for experiments.
• Maintain reproducible Python environments and IaC for reliable deployments.

Skills

ML Ops

Data pipelines

CI/CD

Python

Spark

Airflow

Databricks

Terraform

AWS

MLflow

Observability

Model registries

Education

Bachelor's degree in CS/Data Engineering or related field

Tools

Spark

Airflow

MLflow

Terraform

Docker

Databricks

Python

AWS

Job description

PAR Technology seeks an ML Ops Engineer to partner with a data science team, moving models from notebooks to monitored production. You will build pipelines, tune Spark jobs, wire CI/CD, and improve tests and documentation as part of a cloud-native, data-intensive SaaS environment on AWS.

The role emphasizes collaboration across teams, strong ownership, and the ability to adapt in a fast-moving setting, with exposure to MLflow, Terraform, Docker, and Databricks Workflows.