Machine Learning Engineer

As a Machine Learning Engineer at Goliath Partners, an early-stage AI fintech startup, you will design and ship production‑grade ML models, construct data pipelines and real-time decisioning APIs, and own projects from initial research through deployment. This onsite role is based in San Francisco, CA.

Compensation

Salary: USD 250,000 - 250,000 per yearly

Responsibilities

• Design and scale machine learning models focused on affordability, risk assessment, and predictive analytics.
• Develop data pipelines and APIs to bring ML capabilities into production at scale.
• Collaborate with product, data, and engineering teams to deliver customer-facing features.
• Experiment with diverse approaches and make informed decisions on when to apply ML versus alternative methods.
• Drive ongoing improvements in model performance, monitoring, and reliability.

Requirements

• Strong product mindset with a passion for solving real customer problems.
• Hands-on ML engineer capable of end-to-end work from research to production data pipelines.
• Proficiency in Python, modern ML frameworks, and distributed systems.
• High-quality standards while maintaining velocity and iterative delivery.
• Interest in operating within a high-ownership, early-stage startup environment.

Technologies

• Python

What you'll do

• Develop and scale ML models for affordability, risk, and predictive analytics.
• Build data pipelines and APIs that enable production-grade ML at scale.
• Work with product, data, and engineering teams to ship features for customers.
• Assess multiple approaches and apply ML where advantageous, selecting alternatives when appropriate.
• Enhance model performance, monitoring, and reliability through robust practices.

Who you are

• Strong product mindset with a passion for solving real customer problems.
• Hands-on ML engineer comfortable with end-to-end responsibilities (research, data pipelines, production).
• Experienced in Python, modern ML frameworks, and distributed systems.
• Commitment to high-quality work while delivering quickly and iteratively.
• Motivation to operate in a high-ownership, early-stage startup environment.