Machine Learning Engineer, AI Agent Platform

Arta Finance

. Design and implement agent architectures for tool use, planning, memory, and orchestration .

Posted 9/25/2026full-timeMountain View • California • United StatesMid-LevelSenior💰 $110,000 - $205,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing agent architectures for LLM orchestration and workflow execution, with a strong focus on building reliable, production-ready ML systems. Proficient in developing APIs and evaluation frameworks while ensuring systems operate under enterprise constraints.

Highest-signal resume keywords

Production ML Systems DevelopmentLLM Orchestration FrameworksPython ProgrammingAPI Design and DevelopmentEvaluation and Benchmarking Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningLLMsAgent FrameworksBenchmarking PipelinesAPIsSystems ThinkingReliability EngineeringTool UseBackend Systems DevelopmentMulti-Tenant Deployments

Tools & Technologies

Modern ML ToolingDistributed SystemsData InfrastructureSelf-Hosted ModelsEnterprise AI Deployments

Industry Keywords

Financial WorkflowsHigh-Stakes DomainsEnterprise SecurityLatency ConstraintsCost Constraints

Tech Stack

Tools & technologies

Distributed SystemsPython

About the role

Key responsibilities & impact

Design and implement agent architectures for tool use, planning, memory, and 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 operating under enterprise security, latency, and cost constraints
Develop APIs and platform abstractions for external partners
Translate evolving LLM capabilities into stable, production-ready systems
Partner with ML and product teams to integrate agents into financial workflows
Improve reliability, observability, and failure handling of agent systems
Ship systems operating in live financial environments for institutional clients and end users

Requirements

What you’ll need

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 or benchmarking systems for ML or LLMs
Experience designing APIs, services, and pipelines beyond notebooks
Strong systems thinking regarding latency, reliability, failure modes, and tradeoffs
Bay Area preferred, with 3 days/week in the Mountain View office; exceptional remote candidates on the West Coast considered
Experience with self-hosted models or enterprise AI deployments is a strong plus
Background in distributed systems or data infrastructure is a strong plus
Exposure to financial systems or high-stakes domains is a strong plus

Benefits

Comp & perks

Competitive salary and benefits package
Opportunities for growth and advancement
Vibrant and dynamic work environment
Continuous learning opportunities
Robust health insurance for you and your family
High deductible health plan with health savings account contribution
Generous parental leave
Competitive PTO benefits
Equity/options as a significant part of total compensation