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Machine Learning Engineer (AI Agent Platform)

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Onsite

Machine Learning Engineer (AI Agent Platform)

Arta Finance

Machine Learning Engineer (AI Agent Platform)

Skills

PythonMachine LearningAI

2 months ago

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Important information


Contract type:

Permanent

Salary:

$110,000 – $205,000 / year

Location:

United States

Work mode:

Onsite

Published on:

21 October 2026

What they need


  • 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
  • Build the AI Agent Platform
  • 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
  • Enable Enterprise Deployment
  • 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
  • Bridge Research → Production
  • 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
  • What Makes This Role Different:
  • This is not a research or prototype-focused role
  • You will be responsible for shipping systems that operate in live financial environments. Your work directly supports institutional clients and real end users at some of the largest and fastest-growing financial institutions, not internal demos
  • If you’re motivated by making agent systems work reliably at scale, in complex and regulated settings, this role will be a strong fit

Benefits

  • We have a robust health insurance offering for you and your family

  • High deductible health plan available with health savings account contribution

  • Complimentary One Medical membership for individuals and dependents

  • 20 weeks of parental leave

  • 15 days PTO annually plus national and company holidays

  • Remote-work friendly

  • Hands-on experience with LLMs, agent frameworks, or applied ML systems

  • Experience designing systems beyond notebooks — APIs, services, pipelines

  • Experience building evaluation / benchmarking systems for ML or LLMs

  • Strong Python skills and experience with modern ML tooling

  • Experience with agent systems, tool use, or LLM orchestration frameworks

  • Strong systems thinking: latency, reliability, failure modes, tradeoffs

  • 5+ years building production ML systems or backend systems for ML-powered products

  • Background in distributed systems or data infrastructure

  • Experience with self-hosted models or enterprise AI deployments

  • Exposure to financial systems or high-stakes domains

  • Introduction call with Recruiting Coordinator, 30m - VIRTUAL

  • General Interview, 30m - VIRTUAL

  • Coding/Algorithm/Data Structure Interview, 60m - VIRTUAL

  • ML System Design Interview, 60m - IN PERSON

  • AI Agent Coding Exercise, 120m - IN PERSON or VIRTUAL

  • Culture Interview, 30 min - IN PERSON or VIRTUAL

  • We require at least one in-person interview before making our offer decision. For remotely located candidates, we may request you to visit the Mountain View HQ to meet the team. Depending on your location, you will meet our team member based in NY/New Jersey

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