Early Warning is looking to build and deploy predictive models faster, more accurately, and more efficiently to help keep fraud and bad actors out of the banking system. This role is responsible for the platforms, tools, and processes that take models from ideas to production, serving predictions in real time.
Requirements
- Strong programming skills in Python and experience with Data Science and ML packages and frameworks.
- Experience with AWS services.
- Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD practices.
- Experience deploying models with MLOps tools such as MLflow, Kubeflow, or similar platforms.
- Expert understanding of data management, distributed computing, and software architecture principles.
- Proven experience delivering real-time models in production environments.
- Hadoop / Hive / Cloudera experience
- Distributed computing programming skills such as Spark
- Experience with Scala / Java programming languages
Responsibilities
- Designs, builds, and maintains scalable ML infrastructure and pipelines for model training, deployment, and monitoring.
- Optimizes orchestration processes to ensure efficient deployment and management of predictive models.
- Optimizes resource usage to minimize infrastructure expense while maximizing performance.
- Monitors and maintains the performance, security, and scalability of the ML infrastructure.
- Collaborates with data scientists and software engineers to streamline the ML lifecycle from development to production.
- Develops and maintains tools for data analysis, experimentation, model versioning, and artifact management.
- Creates robust monitoring systems to measure and trend model performance, detect model drift, and ensure optimal performance of models in production.
Other
- Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire.
- This position is ineligible for employment Visa sponsorship.
- Education and experience typically obtained through completion of a Bachelor's degree in Computer Science, Engineering, or a related field
- Minimum 5 years’ experience in Data Science, ML Engineering or ML Ops capacity.
- Background and drug screen.
