Machine Learning Engineer

We're looking for a Machine Learning Engineer to join our Data Science team, who can build machine learning and statistical modeling frameworks from scratch, and assist with optimizing the different aspects of the modeling process.

Requirements

• Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
• Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
• Build, test, deploy and maintain production systems.
• Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
• Support maintenance and optimization of cloud-native EDW and ETL solutions.
• Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
• Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
• Use extensive experience to build, test, debug, and deploy production-grade components.
• Participate in development of database structures that fit into the overall architecture of Swish systems

Benefits

• Base salary: $165,000 - $195,000
• Swish Analytics is an Equal Opportunity Employer