AI Operations Manager

Quantum Yield; Palo Alto (CA); On-site; USD 170,000 - 230,000; Full time

Job summary

Quantum Yield in Palo Alto, CA, seeks an AI Operations Manager to run day-to-day operations of its AI-driven trading and forecasting systems. You will manage production-grade models applying neural networks and NLP to market data for both automated and decision-augmented trading strategies.

You will coordinate between quantitative research, portfolio management, and trading, ensuring research hypotheses become robust, monitored, and risk-controlled in production.

Qualifications

• Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field.
• Hands-on experience applying neural networks and pattern recognition to financial markets or time-series domains.
• Practical knowledge of NLP techniques for analyzing macro research, news, or other financial text.
• Proficiency in Python or a comparable language used in algo-trading, quantitative finance, and ML, plus familiarity with PyTorch or TensorFlow.
• Experience building and deploying models in production, ideally in high- or medium-frequency algo-trading environments, including backtesting, simulation, and model evaluation.

Responsibilities

• Manage design, development, and optimization of AI-driven trading and forecasting models.
• Coordinate and prioritize activities across research, portfolio management, and trading.
• Translate research hypotheses into robust production implementations.
• Run simulations, backtests, and refine models based on performance metrics.
• Maintain and improve data pipelines, ensuring low-latency execution.
• Oversee model monitoring and risk controls for live systems.
• Support investor relations: prepare updates and materials explaining models and risk controls.

Skills

CS fundamentals

Neural networks

NLP techniques

Python

Production deployment

Backtesting & simulation

Distributed systems

Data pipelines

Investor communications

Writing skills

Education

CS/Engineering degree

Tools

PyTorch

TensorFlow

AWS

Job description

Quantum Yield is an AI-powered financial forecasting and scenario analysis platform built for investment professionals, strategists, and macro and micro traders. Our unified AI architecture pairs human judgment with machine intelligence across two areas: forward-looking macro scenario analytics, and end-to-end algorithmic trading at the market-microstructure level.

Portfolio managers, risk officers, and macro modelers use Quantum Yield to make faster, smarter, and more confident decisions. We combine advanced machine learning with practical financial insight to support high-impact investment workflows.

Role Description

As AI Operations Manager, you will run the day-to-day operation of Quantum Yield's AI-driven trading and forecasting systems. You will manage the design, build, and optimization of production-grade models that apply pattern recognition, neural networks, and NLP to market data. These models support both automated and decision-augmented trading strategies.

You will sit between quantitative research, portfolio management, and trading, setting priorities across the three. Your job is to make sure research hypotheses become robust, monitored, and risk-controlled systems in production.

You will also help tell Quantum Yield's story. You will support investor relations by preparing clear updates on how our systems work and perform, and you will contribute to company branding and communications, including our newsletter.

This is a full-time, on-site role based in Palo Alto, CA.

Responsibilities

• Manage the design, development, and optimization of AI-driven trading and forecasting models that integrate market data.
• Coordinate and prioritize activities and objectives across quantitative research, portfolio management, and trading.
• Translate research hypotheses into robust production implementations.
• Run simulations and backtests, and refine models based on performance metrics.
• Maintain and improve data pipelines, and ensure low-latency execution.
• Oversee model monitoring and risk controls for live systems.
• Support investor relations: prepare investor updates, performance commentary, and materials that explain our models and risk controls, and join investor meetings as needed.
• Contribute to company branding and external communications, including the company newsletter, website content, and thought‑leadership pieces on AI in markets.

Qualifications

Required

• Strong foundation in computer science and software development, including data structures, algorithms, and production‑grade coding practices.
• Hands‑on experience applying neural networks and pattern recognition to financial markets or similarly complex time‑series domains.
• Practical knowledge of natural language processing (NLP) techniques for analyzing macro research, news, or other financial text.
• Proficiency in Python or a comparable language used in algo‑trading, quantitative finance, and machine learning, plus familiarity with modern ML frameworks such as PyTorch or TensorFlow.
• Experience building and deploying models in production, ideally in high‑ or medium‑frequency algo‑trading environments, including backtesting, simulation, and model evaluation.
• Comfort working with large‑scale datasets, distributed systems, and cloud‑based development tools.
• Ability to coordinate and prioritize work across a multidisciplinary team, communicate technical concepts clearly, and adapt in a fast‑paced, research‑driven environment.
• Strong writing and presentation skills, with the ability to explain complex quantitative and AI concepts to investors and non‑technical audiences.
• Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience.

Preferred

• Understanding of debt and equity markets and their derivatives, macroeconomics, and portfolio or risk analytics.
• Prior work in quantitative trading or asset management.
• Experience with data engineering concepts.
• Experience in investor relations, fund communications, or financial content and newsletter writing.

Additional Job Application Terms

This job is part of LinkedIn’s Full‑Service Hiring beta program. Eligibility is limited to candidates located in and performing services in the United States, excluding those based in Alaska, Hawaii, Nevada, South Carolina, or West Virginia.

We’re committed to making our hiring process as smooth and timely as possible, and we understand that waiting to hear back can add to the anticipation. If you’re a potential fit, our team will reach out within two weeks to progress you to the next stage. If you don’t hear from us in that time, we encourage you to explore other opportunities with our team in the future, and we wish you the very best in your job search.