Machine Learning Engineer, AI Agent Platform

Arta Finance•Mountain View, CA

About The Position

Arta is on an audacious and incredibly rewarding mission: to pave the way for people everywhere to lead more successful financial lives. Arta leverages AI and sophisticated digital tools—once reserved for ultra-high-net-worth individuals—and makes them accessible to a broader global audience. Think of it as your own digital family office, combining intelligent investment strategies, alternative assets, private market access, and smart automation to help you grow and protect your wealth effortlessly. We value trust, teamwork, and adaptability. Think: intelligent investing, personalized portfolios, and real-time trading, all backed by robust data infrastructure. Arta is building the AI infrastructure for the next generation of wealth management. We partner with leading financial institutions to power strategic initiatives that create real competitive advantage, particularly in making high-quality, personalised advice scalable. Our platform enables intelligent agents to operate across core advisory workflows, from client servicing and suitability to portfolio research and analysis. These systems run in live, regulated environments and are embedded into how institutions serve their clients day to day. You will design and build production-ready agent systems that sit at the core of how financial decisions are supported and delivered.

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
You are located in or have a plan to relocate to the Bay area.

Nice To Haves

Experience with self-hosted models or enterprise AI deployments
Background in distributed systems or data infrastructure
Exposure to financial systems or high-stakes domains

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

Benefits

A competitive salary and benefits package, with ample opportunities for growth and advancement
A vibrant and dynamic work environment where innovation, collaboration, and continuous learning are highly valued
The opportunity to work with a diverse and talented team of industry experts, passionate about shaping the future of finance
Robust health insurance offering for you and your family
High deductible health plan available with health savings account contribution
20 weeks of parental leave
17 days PTO annually

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume