Staff Machine Learning Engineer

April 2

Apply Now

Get a free AI resume review

Underdog Fantasy

WebsiteLinkedInAll Job Openings

Underdog Fantasy is one of the fastest-growing fantasy sports companies on the market.

sports • gaming • fantasy

201 - 500

Description

• As a Staff ML Engineer on the Data Platform team, you’ll be developing and deploying 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

Requirements

• At least 7 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 Go, Python, or other OOP languages (at least 2) • Advanced proficiency with SQL • Experience with DevOps practices such as CI/CD pipelines, and infrastructure-as-code tools (e.g. Terraform, CDK) • 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