Remote Lead DataOps & MLOps Platform Engineer

Ladders; United States; Remote; USD 125,000 - 170,000; Full time

Benefits offered by this job

Health, dental, vision insurance

Mental health support

Paid time off + parental leave + flex

401(k) with company match

Job summary

Ladders is seeking a Lead DataOps / MLOps to join a client leading in Finance & Insurance. The role shapes the operating model for data and ML pipelines, focusing on reliability, standardization, and automation at scale.

Remote work is offered with a compensation range of $124,500–$170,000 annually. You will partner with data engineering and ML teams to strengthen deployment practices, governance, and cost efficiency across Azure-based platforms.

Qualifications

• 8+ years in data, ML, or platform engineering.
• Demonstrated technical leadership and mentoring of engineers.
• Strong CI/CD expertise using Azure DevOps for data pipelines and ML models.
• Hands-on orchestration with Dagster and modern data stacks.
• MLOps experience with MLflow for model management and deployment.
• Proficient in infrastructure-as-code and Azure administration.
• Strong Python and SQL for automation.

Responsibilities

• Own the DataOps/MLOps platform and operating model for data and ML pipelines.
• Lead CI/CD standards and pipelines in Azure DevOps for deployment automation.
• Standardize orchestration processes using Dagster for pipeline management.
• Operationalize ingestion and transformation stacks including dlt and dbt.
• Establish foundations for MLOps with the ML engineering team using MLflow.
• Administer and govern the Databricks Lakehouse environment on Azure.
• Drive cost visibility and optimization across computing resources.

Skills

CI/CD with Azure DevOps

Dagster orchestration

MLflow for ML ops

Python

SQL

Azure cloud

Platform engineering

Tools

Azure DevOps

Dagster

MLflow

Databricks

dbt

Delta Live Tables

Job description

Ladders is seeking a Lead DataOps / MLOps to join a client leading in Finance & Insurance. The role shapes the operating model for data and ML pipelines, focusing on reliability, standardization, and automation at scale.

Remote work is offered with a compensation range of $124,500–$170,000 annually. You will partner with data engineering and ML teams to strengthen deployment practices, governance, and cost efficiency across Azure-based platforms.