Partnering with mission-driven entrepreneurs to build Rocky Mountain technology companies of impact, utility, and value.

If you are passionate about solving impactful and real-world problems using data and artificial intelligence, then you have found the right team! As a Vice President, Applied Artificial Intelligence & Machine Learning Lead in Markets Operations, you will be at the forefront of innovation, developing cutting-edge technologies to support our Markets business. You will collaborate with software engineers, business stakeholders, and machine learning engineers and researchers to enable our business to scale and thrive.

Job responsibilities

• Formulate and implement AI solutions – Develop and drive the implementation of Artificial Intelligence solutions for complex problems in Markets Operations.
• Build Scalable AI Capabilities – Design and create robust, scalable, and reusable Machine Learning models and systems.
• Collaborate with Engineering Teams – Partner with software engineering teams to design and deploy AI services that integrate seamlessly with strategic systems and processes.
• Evaluate Model Performance – Design and implement intrinsic and extrinsic evaluation metrics to measure model performance in alignment with business goals.
• Deepen Business Understanding – Continuously enhance your understanding of the Markets business to develop practical and impactful solutions.
• Embed Feedback Loops – Establish robust feedback loops to power active learning and maximize model performance over time.
• Mentor and Guide Team Members – Provide technical mentorship and guidance to team members, sharing best practices and staying at the forefront of machine learning advances.
• Create Production-Grade Code – Create and maintain production-grade code for analysis and training pipelines..

Required qualifications, experiences, and skills

• Master’s or higher qualification in in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related highly quantitative field.
• Deep understanding of fundamental Machine Learning approaches.
• Practical experience with statistical data analysis and experimental design.
• Significant hands-on experience developing and deploying Data Science and ML capabilities in production at scale.
• Considerable experience in an applied Machine Learning or Data Science role.
• Strong experience with Python programming and common ML frameworks (e.g. pytorch, pandas, numpy etc) and MLOps platforms (e.g. Sagemaker).
• Effective verbal and written communication skills.
• Demonstrated ability to work on multi-disciplinary teams with diverse backgrounds.