ML-Driven Infra Engineer: Scale Data Pipelines & Models

Harrison Clarke; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Harrison Clarke is looking for engineers to join their rapidly growing AI company in San Francisco, California. In this role, you'll work at the intersection of product, data, and machine learning, building systems that directly impact model quality and user experience.

You’ll focus on large-scale user interaction data, designing pipelines, and improving data quality while collaborating with product and ML teams. This position offers the opportunity for high ownership and impact in a fast-paced environment.

Responsibilities

• Build systems that capture, process, and structure large-scale user interaction data.
• Design pipelines that feed data back into model training and evaluation loops.
• Improve data quality, reliability, and observability across the platform.
• Work closely with ML and product teams to translate insights into better outputs.
• Help scale infrastructure that powers a rapidly growing global product.

Skills

Backend engineering experience (Python, Go, or similar)

Experience working with data pipelines, ETL systems, or large-scale datasets

Familiarity with distributed systems and high-throughput architectures

Interest in machine learning systems or data-driven products

Product mindset

Comfort in fast-moving, ambiguous environments

Job description

Harrison Clarke is looking for engineers to join their rapidly growing AI company in San Francisco, California. In this role, you'll work at the intersection of product, data, and machine learning, building systems that directly impact model quality and user experience.

You’ll focus on large-scale user interaction data, designing pipelines, and improving data quality while collaborating with product and ML teams. This position offers the opportunity for high ownership and impact in a fast-paced environment.