Job Description

Sr. Machine Learning Engineer
Location: San Francisco, CA
Duration: 3+ Months Contract To Hire

Responsibilities:

As a machine learning engineer, you will help us productionize findings from data science into real-world applications. Your primary responsibility will be to develop and maintain production-quality software to host machine learning and statistical models, and make them available to our platform. You will also help build model training, publishing, and analytics pipelines for a multitude of machine learning models. In addition, you will validate model integrity and monitor performance while providing data scientists with tooling to accelerate their iteration cycles.

In the first 90 days you will:

• Write a new model server to predict repayment rates for returning customers given their previous repayment history
• Improve A/B testing framework to enable returning customer model testing in real-world scenarios
• Develop a method to optimize the allocation of funds across different population segments

OUR TECH STACK:

Our technology stack consists of modern tools; we are open to technologies and pick the right tool for the job:

• Python for Machine Learning e.g. (Scikit-learn and PyTorch)
• Python/Scala for data pipelines
• Scala/Java/Python for micro-services and APIs
• Swagger(OpenAPI) for API documentation
• Docker and Kubernetes to package and run services
• AWS for cloud infrastructure
• On-premise servers for data processing and extraction at our partners

Requirements:

• Degree in a relevant technical field or equivalent experience
• Two years of work experience building and deploying production machine-learned models
• Experience with modern machine learning frameworks like Scikit-learn, Torch or Tensorflow
• Understanding of statistical modeling
• Demonstrable history of building production-quality software infrastructure
• Experience programming in Python and Java
• Experience developing microservices