Machine Learning Engineer

Summary

Join Underdog, the fastest-growing sports gaming company, as a Senior Machine Learning Engineer. You will design and develop low-latency machine learning inference systems for real-time application updates. Responsibilities include building internal tools, writing efficient application code, and measuring model performance. You will also mentor junior engineers and lead technical initiatives. This role requires extensive experience in building low-latency systems, proficiency in C/C++, Rust, or Go, and familiarity with various ML platforms and data streaming frameworks. Underdog offers competitive compensation, including a base salary range of $150,000-$190,000 plus equity, along with benefits such as unlimited PTO, parental leave, a home office allowance, and comprehensive health insurance.

Requirements

• At least 5 years of experience building low latency systems on a cloud environment (e.g. AWS, GCP, Azure)
• Advanced proficiency with C/C++, Rust, or Go
• Familiarity with SQL
• Strong proficiency with SageMaker, Databricks, and/or comparable ML platforms
• Highly focused on delivering results for internal and external stakeholders in a fast-paced, entrepreneurial environment
• In depth knowledge of statistical concepts such as univariate and bivariate distributions, regression models, and binomial models
• Experience with data streaming frameworks such as Apache Kafka, Apache Flink, or Kinesis
• Familiarity with containerization and orchestration technologies such as Docker, Kubernetes, or ECS
• Excellent leadership and communication skills with ability to influence and collaborate with stakeholders

Responsibilities

• Develop and design low latency Machine Learning (ML) inference systems to enable real time updates on the UD application
• Build internal tools and services to accelerate UD’s model building and deployment process
• Write low latency application code that are sophisticated and fast for complex, data science infrastructure
• Build frameworks to measure and analyze model performance and accuracy in production environments
• Mentor junior engineers, lead technical initiatives, and drive results in a fast-paced, dynamic environment
• Lead code reviews, provide constructive feedback, and evangelize best practices to maintain code and data quality
• Keep up to date on emerging ML technologies and trends and focus on iteratively implementing them into Underdog’s engineering systems

Preferred Qualifications

• Strong interest in sports
• Prior experience in the sports betting industry
• Experience in building low latency systems or ML inference systems

Benefits

• Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
• 16 weeks of fully paid parental leave
• A $500 home office allowance
• A connected virtual first culture with a highly engaged distributed workforce
• 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents