Remote MLOps Engineer — Production Data Pipelines on AWS

PAR Technology; Georgia; Remote; USD 125,000 - 160,000; Full time

Job summary

PAR Technology is seeking an ML Ops Engineer to join Bridg’s data science team. You will help move models from notebooks to production, building pipelines, tuning Spark jobs, and implementing CI/CD with strong observability and tests.

In a cloud-native environment on AWS with Snowflake-like data workflows, you’ll collaborate across teams and own parts of the data/ML lifecycle, ensuring reliable, scalable delivery.

Qualifications

• 2–4 years of experience building production data or ML systems.
• Bachelor’s degree in Computer Science, Data Engineering, or a related field (or equivalent practical experience).
• Highly motivated, curious, and capable learner with a strong sense of ownership and accountability.
• A strong communicator and collaborator who works well across cross‑functional teams.
• Comfortable in a fast‑moving environment — able to shift priorities, navigate ambiguity, and support a customer‑facing system.

Responsibilities

• Build pipelines, tune Spark jobs, and wire CI/CD for ML workflows.
• Maintain observability, tests, and documentation for production systems.
• Collaborate with data science teams and cloud infrastructure.
• Support deployment to AWS data services and downstream systems.

Skills

Python

Spark

CI/CD

Data pipelines

MLflow

Airflow

AWS

Education

Bachelor’s degree in Computer Science or Data Engineering

Tools

Docker

Terraform

Databricks

S3

EMR

Glue

Step Functions

Lambda

IAM

CloudWatch

Job description

PAR Technology is seeking an ML Ops Engineer to join Bridg’s data science team. You will help move models from notebooks to production, building pipelines, tuning Spark jobs, and implementing CI/CD with strong observability and tests.

In a cloud-native environment on AWS with Snowflake-like data workflows, you’ll collaborate across teams and own parts of the data/ML lifecycle, ensuring reliable, scalable delivery.