Quantitative Developer (Machine Learning & AI)

About the position

Join Principal Asset Management’s Private Markets Research & Analytics team as a Quantitative Developer to scale machine learning and AI solutions that support investment decisions, risk management, and portfolio performance. You’ll work with investment professionals, quantitative researchers, data engineers, and software engineers to turn business needs and research models into reliable, production-ready solutions. You’ll have the opportunity to operationalize machine learning solutions that support investment decisions, build scalable, cloud-native ML workflows using AWS services such as Lambda, Step Functions, S3, and DynamoDB, develop data validation, feature engineering, model evaluation, and forecast-quality controls, support forecasting, risk management, portfolio optimization, and performance measurement across private-market strategies, integrate generative AI and large language models into secure business workflows and research platforms, accelerate experimentation, deployment, and adoption of scalable, audit-friendly AI solutions, evaluate emerging technologies that may strengthen Principal Asset Management’s competitive position, and contribute to internal research, technical thought leadership, and publications.

Responsibilities

• Operationalize machine learning solutions that support investment decisions
• Build scalable, cloud-native ML workflows using AWS services such as Lambda, Step Functions, S3, and DynamoDB
• Develop data validation, feature engineering, model evaluation, and forecast-quality controls
• Support forecasting, risk management, portfolio optimization, and performance measurement across private-market strategies
• Integrate generative AI and large language models into secure business workflows and research platforms
• Accelerate experimentation, deployment, and adoption of scalable, audit-friendly AI solutions
• Evaluate emerging technologies that may strengthen Principal Asset Management’s competitive position
• Contribute to internal research, technical thought leadership, and publications

Requirements

• Bachelor's degree in a STEM field plus 8+ years of related experience, or a Master's degree in a related field plus 2+ years of related experience
• Experience deploying and supporting production-grade machine learning or forecasting systems
• Strong Python skills and experience with Scikit-learn, TensorFlow, PyTorch, Spark ML, or similar frameworks
• Experience with ML operations, including orchestration, artifact management, automated evaluation, continuous integration and deployment, and cloud operations
• Knowledge of data structures, software architecture, data modeling, and scalable application design
• Ability to take ownership and move projects from concept through implementation
• Strong communication and collaboration skills across technical and business teams.
• Curiosity and a commitment to learning and applying new technologies

Nice-to-haves

• Experience operationalizing scenario-based or time-series forecasting models
• Experience integrating generative AI or large language models into secure workflows
• Knowledge of asset management, financial services, private real estate, or alternative investments
• Experience contributing to research publications, technical papers, or industry thought leadership

Benefits

• Bonus program
• Profit-share bonus plan
• Flexible Time Off (FTO)
• Comprehensive, competitive benefit offerings crafted to protect their physical, financial, and social well-being