ML Engineer

Role Overview

Design and implement AI systems that automate complex accounting and financial workflows. Collaborate with cross-functional teams to develop product interfaces and agent interaction systems. Contribute to AI product development spanning machine learning, backend systems, and full-stack engineering.

What You Will Do

Design context ontologies, build data pipelines, optimize agent workflows, and analyze long-running agent trajectories. Build scalable AI-powered systems capable of handling complex real-world operational workflows.

Why It Might Be a Fit

Ideal for those with strong computer science and systems engineering fundamentals, experience building and deploying machine learning or AI-powered systems, and high execution velocity in ambiguous startup environments.

Requirements

• Strong computer science and systems engineering fundamentals
• Experience building and deploying machine learning or AI-powered systems in production environments
• High execution velocity with the ability to iterate quickly in ambiguous startup environments
• Strong understanding of machine learning workflows, AI tooling, and modern engineering practices
• Experience working with AI-assisted development tools and workflows
• Strong communication skills with the ability to explain technical concepts clearly
• Demonstrated ownership mindset and ability to drive projects independently from idea to production
• Comfortable working across infrastructure, ML systems, and product engineering layers
• Strong problem-solving abilities and systems thinking across interconnected technical domains

Benefits

• Meaningful equity package with strong upside potential
• High ownership engineering culture with significant technical influence
• Opportunity to work on cutting-edge AI systems and agent infrastructure
• Fast-moving, collaborative startup environment
• Strong emphasis on sustainable pace and long-term team performance