FanDuel is looking for a Machine Learning Engineer to join their growing team and help design, build, and deploy machine learning systems that power real-world applications. The role involves bringing models from experimentation to production and ensuring they perform reliably at scale, contributing across the ML lifecycle.
Requirements
- Proficiency in Python, with exposure to ML libraries (Scikit-learn, TensorFlow, or PyTorch).
- Solid understanding of data structures, algorithms, and software engineering principles.
- Hands-on with SQL and comfortable working with large datasets.
- Familiarity with distributed computing (Apache Spark preferred).
- Exposure to ML deployment & monitoring practices or strong interest in learning them.
- Experience with cloud services (AWS preferred, GCP or Azure also valuable).
- Experience with containerization (Docker, Kubernetes is a plus).
Responsibilities
- Collaborate with data scientists to implement and optimize machine learning models for production use.
- Develop and maintain pipelines for data preparation, training, and model deployment.
- Build tools and services to support real-time and batch inference workloads.
- Implement monitoring and alerting to track model performance and detect issues such as data drift.
- Write maintainable, testable code and follow best practices in version control and documentation.
- Help automate training, deployment, and retraining workflows using ML Ops tools.
- Build and optimize ML pipelines and feedback loops for our flagship recommender systems.
Other
- 2–4 years of experience in software engineering, machine learning, or data science.
- Translate product and business requirements into ML-driven solutions.
- Participate in agile workflows, including sprint planning, code reviews, and design discussions.
- Work with engineers and analysts to ensure data integrity and efficient feature computation.
- Employees may be required to perform other such duties as assigned by the Company.
