Sobre este puesto de Machine Learning Engineer, AI Agent Platform en Arta Finance
The Company
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.
The Role
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.
What You Will Do
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
Who You Are
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
Location: You are located in or have a plan to relocate to the Bay area.
Strong Plus
Experience with self-hosted models or enterprise AI deployments
Background in distributed systems or data infrastructure
Exposure to financial systems or high-stakes domains
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.
Interview Process
Introduction with Head of Talent, 30m
General & Domain Knowledge Interview with AI Researcher, 45m
Coding/Algorithm/Data Structures, 60m
AI Coding & Discussion Exercise with AI Researcher, 120m
System Design Interview with VP of Engineering, 60m
Co-founder Interview with Head of AI/CIO, 30m
Note: 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.
Interview Integrity Notice
To ensure a fair and accurate assessment, candidates are expected to complete all interview exercises independently, without the use of external assistance or AI tools. Arta may, with your consent, request that you share your full screen during technical portions of the interview to verify your work environment. Interviewers may also, with your consent, ask you to temporarily disable virtual backgrounds or filters to confirm your identity and maintain interview integrity. These steps are voluntary, used only for real-time verification, and do not involve recording, storing, or accessing any information beyond what you choose to display during the session.
What We Offer
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
Arta's Compensation Philosophy
We determine your salary based on factors including your interview performance, job-related skills, experience, and relevant education or training. Our offers are based on salary bands that are updated periodically using market benchmarks and consider geographic location as well (for example, higher cost regions like San Francisco or New York). If you are presented with an offer, we will review the base salary, benefits, number of options, notional option value and strike price. We would like to know if you accept our offer within 7 days.
Please keep in mind that the equity portion of your offer is not included in these numbers and represents a significant part of your total compensation.
IC I: $110,000-$180,000
IC II: $160,000-$230,000
IC III: $180,000-$300,000
