Machine Learning Engineer, AI Agent Platform

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: Bay Area preferred (3 days/week in our Mountain View office).

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 - One in-person technical interview is required for ALL candidates

• Intro call with Recruiting Team, 30m - Virtual
• General Interview with Hiring Manager, 30m - Virtual
• Coding/Algorithm/Data Structure Interview, 60m - In-person
• ML System Design Interview, 60m - In-person
• AI Agent Coding Exercise, 120m - In-person or Virtual
• Leadership Interview, 30m - In-person or Virtual

Note: We require at least one in-person technical interview before making our offer decision. For remotely located candidates, we may request you to visit the Mountain View HQ to meet the team.

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
• Generous parental leave
• Competitive PTO benefits

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.

$150,000-$250,000 (base & bonus)