Ripple is hiring a

Web3 Applied Scientist, Liquidity (Summer 2022 Intern)

Ripple’s mission is to enable payments every way, everywhere for everyone. We believe connecting traditional financial entities like banks, payment providers and corporations with emerging blockchain technologies and users is the path to an open, decentralized, and more inclusive financial future. This Internet of Value gives any internet-enabled person, application or device access to financial services that are transparent, fast, reliable, and cheap. Delivering this vision is a challenge of massive scale spanning $155 trillion in annual cross border fiat payments and the $1.5 trillion market of digital assets that has grown 10X in the last year.

We are looking for interns to join our growing Liquidity Engineering teams charged with delivering a first-of-its-kind liquidity platform-as-a-service to transform Ripple’s global customers. By joining one of our teams, you will contribute in the following area: Applied Science. You will partner with teammates and across the Liquidity Engineering organization to build robust solutions that power our liquidity services at scale. You will contribute your own solutions and be mentored by other applied scientists, contributing to a culture of high standards and technical excellence. As a member of a new initiative, you must be passionate about inventing and delivering customer-focused solutions to ambitious and ambiguous challenges.

WHAT YOU’LL DO:

• Explore end to end ML modeling technique for new business problem
• Prototyping, building and productionizing machine learning models & systems to enable Ripple deliver liquidity to its customers, ensuring the best customer experience of the widest selection of assets at the best price
• Working with real time data streams, designing and extracting features to feed into our models
• Writing performant feature engineering scripts
• Designing unbiased and counterfactual estimators for offline evaluation of models
• Performing design and code reviews
• Collaborate with partner Liquidity Engineering teams and business stakeholders to build new capabilities to deliver liquidity to Ripple’s customers

Some examples of projects our Liquidity Engineering teams are tackling include:

• Launching Liquidity Hub, a liquidity platform for enterprises to easily and efficiently source digital assets.
• Playing a critical role helping to advance Ripple’s development and production infrastructure, including deployment, monitoring, instrumentation, and overall infrastructure management.
• Determining and delivering optimal liquidity for every customer in the world by contributing to the development of a cost-effective, robust, and scalable crypto trading platform
• Building end-to-end machine learning-enabled solutions that solve problems ranging, from forecasting supply and demand to optimizing routing across digital asset venues to pricing and risk management systems.
• Delivering scalable production machine learning services to solve our liquidity challenges by designing and implementing the infrastructure and tools to create and deploy production models.
• Building backtest research tools understand the dynamics of FX & Crypto markets based on data

WHAT WE’RE LOOKING FOR:

• Pursuing Masters or PhD program in Computer Science or another relevant technical field
• Coursework / intern experience with software engineering and/or applied machine learning
• One or more of the following:
• Demonstrates strength in CS fundamentals and advanced ML and statistics fundamentals
• Experience solving problems that involve machine learning or other quantitative techniques, including statistical modeling, time series analysis/forecasting and experimentation, bonus if in finance and trading domains, especially Crypto or FX.
• Knowledge of common ML frameworks and libraries (SKlearn, TensorFlow, PyTorch etc)
• Experience with cloud infrastructure, including platform tools like Kubernetes, container schedulers & runtimes such as Docker, Rkt, or OCI, or Infrastructure-as-Code (e.g. Terraform, CloudFormation, etc.)
• Experience analyzing large datasets and applying advanced featurization techniques.
• Excellent written and verbal communication skills
• Attention to detail and a commitment to excellence

WHAT WE OFFER:

• The chance to work in a fast-paced start-up environment with experienced industry leaders
• Opportunity to work in a highly talented cross-functional team of engineers, applied scientists and MLEs, which provides unique opportunity to collaborate and learn different skills
• A learning environment where you can dive deep into the latest technologies and make an impact
• Modern office in San Francisco’s Financial District
• Fully-stocked kitchen with organic snacks, beverages, and coffee drinks
• Weekly company meeting - ask me anything >
• Team outings to sports games, happy hours, game nights and more!

Apply Now: