Machine Learning Engineer, AI Agent Platform

Arta Finance is building AI infrastructure to make sophisticated financial tools and personalized wealth management more accessible. The Machine Learning Engineer will design and build production-ready AI agent systems, including orchestration, evaluation, deployment infrastructure, APIs, and reliability capabilities for regulated financial workflows.

Responsibilities:

• Design and implement agent architectures (tool use, planning, memory, orchestration)
• Build systems for LLM orchestration, prompt management, and workflow execution
• Develop evaluation frameworks for agent quality, reliability, and safety
• Create benchmarking pipelines to measure model and system performance over time
• Build infrastructure for self-hosted and multi-tenant deployments
• Design systems that operate under enterprise constraints (security, latency, cost)
• Develop APIs and platform abstractions for external partners
• Translate rapidly evolving LLM capabilities into stable, production-ready systems
• Partner with ML and product teams to integrate agents into real financial workflows
• Improve reliability, observability, and failure handling of agent systems

Requirements:

• 5+ years building production ML systems or backend systems for ML-powered products
• Hands-on experience with LLMs, agent frameworks, or applied ML systems
• Strong Python skills and experience with modern ML tooling
• Experience with agent systems, tool use, or LLM orchestration frameworks
• Experience building evaluation / benchmarking systems for ML or LLMs
• Experience designing systems beyond notebooks — APIs, services, pipelines
• Strong systems thinking: latency, reliability, failure modes, tradeoffs
• Experience with self-hosted models or enterprise AI deployments
• Background in distributed systems or data infrastructure
• Exposure to financial systems or high-stakes domains
• Bay Area preferred