AI Engineer 1

Job Title

AI Engineer

About Millennium

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.

Meet the Team

The AI/ML team is part of Millennium’s Information Technology organization, which is core to the health and growth of the firm. The team develops AI/ML solutions and supporting technology for portfolio managers, researchers, risk managers, and other business functions, applying techniques such as large language models, deep learning, reinforcement learning, and other machine learning approaches. The team also builds the data and AI/ML infrastructure needed for data wrangling, feature stores, deployment frameworks, model measurement, and retraining.

What You'll Do

• Partner with business stakeholders, quantitative teams, and market researchers to understand complex problem spaces and identify high-impact AI/ML opportunities.
• Experiment with, iterate on, and productionize AI/ML solutions that support research, modeling, risk, and trading-related use cases.
• Build supporting data and AI/ML infrastructure, tools, and frameworks for data preparation, deployment, measurement, and model retraining.

What You Bring

• Strong knowledge of current AI and machine learning advancements, including LLMs, deep learning, reinforcement learning, and related techniques.
• Strong computer science fundamentals and software engineering capabilities.
• Proficiency in Python and at least one additional programming language, such as Java, C++, or C#.
• Experience with cloud computing platforms, such as AWS, Azure, or Google Cloud.
• Experience using LLMs and techniques such as prompt engineering, parameter-efficient fine-tuning, and fine-tuning.
• Ability to build and evaluate AI models and tools using quantifiable metrics.
• Strong problem-solving and communication skills, with the ability to work independently and collaboratively with technical and business stakeholders.
• Experience working in a fast-paced, startup-like environment; an advanced degree in Computer Science, AI, Machine Learning, or a related field, financial-services AI experience, and 3+ years of relevant experience are preferred.