Ripples mission is to enable payments every way, everywhere for everyone. We believe connecting traditional financial entities like banks, payment providers & corporations with emerging blockchain technologies & users is the path to an open, decentralized, & 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, & cheap. Delivering this vision is a challenge of massive scale spanning $155 trillion in annual cross border fiat payments & the $1.5 trillion market of digital assets that has grown 10X in the last year.

We are looking for a Senior Software Engineer, Machine Learning Operations to join a new team charged with determining & delivering optimal liquidity for every customer in the world in a cost-effective, robust & scalable manner. Candidates will partner closely with applied scientists & engineers to build out a ML infrastructure to enable delivering scalable production machine learning services to solve these liquidity challenges. You will be responsible for the design & implementation of the infrastructure & tools to create & deploy production models. Ideal candidates will have a track record of technical excellence in designing, building & delivering reliable solutions as part of a team. As a member of a new initiative, you must be passionate about inventing & delivering customer-focused solutions to ambitious & ambiguous challenges.

WHAT YOU'LL DO:

• Be an entrepreneurial builder, working up & down the data stack, mixing data engineering, machine learning & software engineering to jumpstart this new initiative.
• Design & build effective, user-friendly infrastructure to enable scalable, auditable, compliant & maintainable machine learning services at Ripple.
• Collaborate with machine learning engineers, software engineers & product managers to develop platform to support ML workflows including experimentation, training & production operations
• Build & maintain systems with an infrastructure-as-code approach
• Establish & manage the cloud stack (AWS or GCP or Databricks) required for ML resources
• Design & implement tools & processes for the entire ML Ops including model development, model deployment, model serving, model monitoring & experimentation.

WHAT WE'RE LOOKING FOR:

• Degree in computer science or other quantitative field; masters or PhD preferred
• 5+ years software engineering experience with 3+ years developing production machine learning systems preferred
• Experience with general cloud Infrastructure & concept of infrastructure as code
• Experience with machine learning lifecycle platforms (Kubeflow, MLflow) & cloud data services (GCP, AWS)
• Experience with machine learning frameworks tools like scikit-learn, TensorFlow, or PyTorch
• A collaborative coder, comfortable with Git & code reviews
• Excellent written & verbal communication skills
• Attention to detail & a commitment to excellence

WHAT WE OFFER:

• The chance to work in a fast-paced start-up environment with experienced industry leaders
• A learning environment where you can dive deep into the latest technologies & make an impact
• Competitive salary & equity
• 100% paid medical & dental & 95% paid vision insurance for employees starting on your first day
• 401k (with match), commuter benefits
• Industry-leading parental leave policies
• Generous wellness reimbursement & weekly onsite programs
• Flexible vacation policy - work with your manager to take time off when you need it
• Employee giving match
• Modern office in San Franciscos Financial District
• Fully-stocked kitchen with organic snacks, beverages, & coffee drinks
• Weekly company meeting - ask me anything style discussion with our Leadership Team
• Team outings to sports games, happy hours, game nights & more!