AI/ML Data Engineer: Scalable Pipelines & Ops

Blackline Systems Inc; Los Angeles (CA); On-site; USD 145,000 - 182,000; Full time

Benefits offered by this job

Incentive programs

Benefits and wellness plans

Job summary

BlackLine is seeking a Software Engineer, AI/ML Ops in Los Angeles to design and optimize data pipelines powering AI-driven accounting agents. You will lead development of scalable data infrastructure, collaborating across teams to deliver reliable, high-performance systems.

Requirements include 2+ years in Python/Java/Scala, ML frameworks, orchestration tools, and production ML/LLM pipelines across GCP/AWS/Azure. Strong CI/CD, IaC, DevSecOps and containerization experience are expected.

Qualifications

• 2+ years of programming experience (Python/Java/Scala).
• Experience with ML frameworks and orchestration tools.
• Production ML/LLM pipelines across cloud ecosystems.
• Familiarity with LangChain and related runtimes.
• CI/CD, IaC, DevSecOps practices including testing and security.

Responsibilities

• Build and maintain PySpark ETL pipelines with high data quality and performance.
• Establish robust connections to client data sources via APIs and tools.
• Monitor pipeline performance, automate testing, and validate data accuracy.
• Implement performance improvements for large-scale datasets.
• Collaborate with stakeholders to integrate AI and big data tech.

Skills

Python

Java

Scala

TensorFlow

PyTorch

scikit-learn

Airflow

Kubeflow

Vertex AI

MLflow

GCP

AWS

Azure

LangChain

LangGraph

ADK

CI/CD

IaC

DevSecOps

Prometheus

Grafana

NewRelic

Docker

Kubernetes

Tools

FiveTran

Plaid

Airflow

Job description

BlackLine is seeking a Software Engineer, AI/ML Ops in Los Angeles to design and optimize data pipelines powering AI-driven accounting agents. You will lead development of scalable data infrastructure, collaborating across teams to deliver reliable, high-performance systems.

Requirements include 2+ years in Python/Java/Scala, ML frameworks, orchestration tools, and production ML/LLM pipelines across GCP/AWS/Azure. Strong CI/CD, IaC, DevSecOps and containerization experience are expected.