Senior Machine Learning Research Engineer
Skills
Computer ScienceAmazon KinesisBuilding SimulationCode ReviewData ScienceData StreamingDeep Learning
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- At least 5 years of experience building low latency 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
- In depth knowledge of statistical concepts such as univariate and bivariate distributions regression models and binomial models
- Advanced proficiency with C++ Rust or Go
- 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
Nice to have
- Strong interest in sports
- Prior experience in the sports betting industry
- Experience in building simulation or inference systems
Day to day
- Developing and designing low latency ML inference systems for real-time updates on the UD application
- Build internal tools and services to accelerate UD’s model building and deployment process
- Write sophisticated and fast low latency applications 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
- Research and keep up to date on emerging ML technologies and trends and focus on iteratively implementing them into Underdog’s engineering systems