Role overview
At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.
If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.
THE WORK:
What you'll work on
- Build and operationalize conventional and generative AI based models to solve knowledge management, financial services and productivity related problems
- Design and implement scalable, auditable, and maintainable machine learning services at Ripple
- Collaborate with Ripple engineers and data scientists to build a premier AI platform
- Work closely with scientists and software as well as ML engineers to drive real-time model implementations and deliver novel and highly impactful features.
- Lead development of scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Mentor and coach junior team members
- Research and implement novel machine learning and statistical approaches.
What we're looking for
- Masters or PhD (preferred) in computer science, statistics, physics, or other quantitative field
- 10+ years of hands-on experience delivering production machine learning solutions to sophisticated business problems
- 5+ years demonstrated ability with Python and/or Java
- Broad machine learning experience including statistical modeling, time series analysis/forecasting and experimentation, bonus if in finance and trading domains, especially FX
- Experience with deep learning models, and ideally exposure to Generative AI
- Experience with cloud-based data processing and machine learning services and tools
- Experience recruiting and mentoring a premier team of applied scientists
- Excellent written and verbal communication skills, especially with non-technical senior leaders
- Attention to detail and a dedication to excellence
- An entrepreneurial problem solver with a bias for action