Machine Learning Engineer

Summary

Join Underdog, the fastest-growing sports gaming company, as a Machine Learning Engineer on the Data Platform team. You will develop and deploy advanced machine learning models and algorithms in a cloud environment, implementing end-to-end pipelines from data collection to deployment. You will build performance measurement frameworks, implement monitoring systems, and utilize various machine learning algorithms. Collaboration with engineering, product, data science, and quant teams is crucial. You will also mentor junior engineers and lead technical initiatives. This role requires at least 4 years of experience building scalable ML systems on a cloud environment and proficiency in various programming languages and technologies. Underdog offers competitive compensation, equity, and benefits.

Requirements

• At least 4 years of experience building scalable ML model training and inference systems on a cloud environment (e.g. AWS, GCP, Azure)
• Highly focused on delivering results for internal and external stakeholders in a fast-paced, entrepreneurial environment
• Excellent leadership and communication skills with ability to influence and collaborate with stakeholders
• Prior experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, and/or scikit-learn
• Familiarity with containerization and orchestration technologies such as Docker, Kubernetes, or ECS
• Experience with data streaming frameworks such as Apache Kafka, Apache Flink, or Kinesis
• Advanced proficiency with C++ and Python
• Advanced proficiency with SQL
• Experience with DevOps practices such as CI/CD pipelines, and infrastructure-as-code tools (e.g. Terraform, CDK)

Responsibilities

• Develop and deploy advanced machine learning models and algorithms on a cloud environment
• Implement end-to-end machine learning pipelines, starting from data collection, feature engineering, model training, evaluation, to deployment
• Build frameworks to measure model performance and accuracy in production environments, leveraging techniques such as parameter tuning and model optimization
• Implement and maintain monitoring, alerting, and logging mechanisms to ensure the health and accuracy of Underdog’s ML systems
• Utilize your understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, reinforcement learning, and ensemble methods, to build production systems
• Work closely with engineering and product teams to ensure seamless integration of machine learning services into Underdog’s data platform
• Collaborate with the data science and quant teams to deploy ML models into production systems
• 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
• Research and 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 simulation or 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