Staff AI/ML Ops Engineer — Scalable ML Pipelines

BlackLine; Pleasanton (CA); Hybrid; USD 245,000 - 307,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation & incentive p

Career development & leadership

Job summary

BlackLine is seeking a Lead Data Engineer in Pleasanton, CA to design and optimize data pipelines powering AI-driven accounting agents. You will lead scalable data infrastructure and collaborate across teams to deliver high quality data for ML/AI initiatives.

You will oversee PySpark ETL pipelines, API integrations with client sources, and reliability testing. The role emphasizes governance, scalability, and close partnership with data science and product teams.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, or related field.
• Proven experience designing and operating large-scale data pipelines.
• Strong Python, SQL, and data modeling skills.
• Experience with ETL/ELT, data quality, and reliability practices.

Responsibilities

• Lead data pipeline development using PySpark ETL pipelines.
• Establish robust connections to client data sources via APIs and tools like FiveTran and Plaid.
• Monitor pipeline performance, automate testing, and ensure data accuracy.
• Collaborate with cross-functional teams to evolve data infrastructure and AI workflows.
• Drive scalability improvements and governance for ML/AI systems.

Skills

PySpark ETL pipelines

Data pipeline development

API integrations

Data quality

Performance optimization

ML/AI systems collaboration

Education

Bachelor's or Master's degree in CS/Data Science

Tools

FiveTran

Plaid

MLflow

Weights & Biases (W&B)

Kubeflow

LangChain

Job description

BlackLine is seeking a Lead Data Engineer in Pleasanton, CA to design and optimize data pipelines powering AI-driven accounting agents. You will lead scalable data infrastructure and collaborate across teams to deliver high quality data for ML/AI initiatives.

You will oversee PySpark ETL pipelines, API integrations with client sources, and reliability testing. The role emphasizes governance, scalability, and close partnership with data science and product teams.