Asset Management — Expert AI Trainer (US)

Mentis Technology Solutions Inc.

Job Overview

Location

USA

Job Type

Contract

Full Job Description

📋 Description

• As an Expert AI Trainer in Asset Management, you will play a pivotal role in shaping the next generation of AI models by translating complex institutional investment processes into machine-readable logic, directly contributing to the advancement of AI in finance and helping bridge the gap between human expertise and artificial intelligence.
• Your day-to-day responsibilities will include analyzing and deconstructing investment workflows across equities, fixed income, and multi-asset portfolios; collaborating with AI engineers to label and structure training data based on real-world analyst and portfolio manager decisions; conducting side-by-side evaluations of human versus AI-generated investment theses, risk assessments, and portfolio recommendations; providing detailed feedback to improve model reasoning, accuracy, and alignment with institutional best practices; documenting edge cases and nuances in judgment that arise during model training; and participating in iterative sprints to refine model performance across asset classes and market conditions.
• Mentis Technology Solutions Inc. is a specialized AI training firm founded by former Lazard and Partners Group professionals, headquartered in London and San Francisco, dedicated to embedding deep domain expertise from finance, healthcare, and law into AI systems to create more reliable, interpretable, and valuable models for institutional use.
• You will work within a small, high-impact team of domain experts and AI specialists where your institutional knowledge directly influences model behavior, offering a unique opportunity to shape how AI understands and supports sophisticated investment decision-making while gaining firsthand experience in the forefront of AI applications in asset management.
• This role offers the chance to deepen your understanding of how AI interprets financial judgment, contribute to cutting-edge research in AI alignment and financial reasoning, and position yourself at the intersection of traditional asset management and emerging AI technologies—building skills that are increasingly valuable as firms integrate AI into research, portfolio construction, and client engagement.

🎯 Requirements

• 4+ years of experience at a major long-only institutional asset manager such as BlackRock, Vanguard, Fidelity, Capital Group, T. Rowe Price, Wellington Management, PIMCO, MFS, Neuberger Berman, Jennison Associates, Artisan Partners, or equivalent
• Senior Research Analyst or Portfolio Manager level expertise
• Deep knowledge of equities, fixed income, or multi-asset portfolio management processes
• Proven experience in fundamental analysis, writing investment commentary, and engaging with company management or issuers
• Familiarity with client reporting, risk attribution, and investment policy constraints
• Ability to commit 15+ hours per week with flexible scheduling

🏖️ Benefits

• Fully remote work with global flexibility—contribute from anywhere in the world
• Hourly compensation based on experience and expertise level
• Immediate start date with rolling onboarding—begin contributing quickly
• Opportunity to work directly with cutting-edge AI models shaping the future of institutional finance
• Influence the development of AI systems used in research, portfolio construction, and client communication at a mission-driven company founded by industry veterans

Skills & Technologies

Remote

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Mentis Technology Solutions Inc.

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About Mentis Technology Solutions Inc.

Mentis provides enterprise data-centric security solutions focused on dynamic data masking, sensitive data discovery, database activity monitoring, and compliance reporting. Founded in 2004, the company serves Fortune 500 organizations and government agencies worldwide, helping protect structured and unstructured data across relational databases, big data platforms, and mainframe environments through continuous classification, real-time masking, and risk analytics without altering source data or impacting performance.

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