Machine Learning Engineer

Goliath Partners is an early-stage AI fintech startup focused on real-time decisioning and data-driven risk analytics. This onsite Machine Learning Engineer role in San Francisco centers on designing and shipping production-ready ML models, building data pipelines and APIs, and steering end-to-end projects from research to deployment. The position offers a compensation of USD 250,000 per year.

Responsibilities

• Design and scale ML models that address affordability, risk, and predictive analytics.
• Build robust data pipelines and APIs to operationalize ML at scale.
• Collaborate with product, data, and engineering teams to deliver customer-facing features.
• Experiment with diverse approaches, identifying when ML is appropriate and when it is not.
• Drive continuous improvement in model performance, monitoring, and reliability.

What you’ll do

• Develop and scale ML models for affordability, risk, and predictive analytics.
• Architect data pipelines and APIs to bring ML into production at scale.
• Collaborate with product, data, and engineering teams to ship customer-facing features.
• Experiment with different approaches, knowing when to use ML—and when not to.
• Push forward innovation in model performance, monitoring, and reliability.

Who you are

• Strong product mindset with a passion for solving real customer problems.
• Hands-on ML engineer comfortable going end-to-end (research, data pipelines, production).
• Experienced in Python, modern ML frameworks, and distributed systems.
• High-quality standards but able to move fast and ship iteratively.
• Excited about working in a high-ownership, early-stage startup environment.

Requirements

• Strong product mindset with a passion for solving real customer problems.
• Hands-on ML engineer comfortable going end-to-end (research, data pipelines, production).
• Experienced in Python, modern ML frameworks, and distributed systems.
• High-quality standards but able to move fast and ship iteratively.
• Excited about working in a high-ownership, early-stage startup environment.

Technologies

• Python