Leverage the best available technology to protect our customers' attack surfaces by enhancing customer security and threat detection through AI/ML.
Requirements
- developing APIs with Flask or FastAPI, paired with strong Python knowledge
- Designing and integrating scalable AI/ML systems into production environments, CI/CD tooling, Docker, Kubernetes, cloud AI resource utilization and management
- Data pre-processing and feature engineering, model monitoring and evaluation
- AWS for hosting our research environments, data, and features
- EKS to deploy applications
- Terraform to manage infrastructure
- Python for analysis and modeling, taking advantage of numpy and pandas for data wrangling
Responsibilities
- Architect and manage the end-to-end design of ML production systems, including project scoping, data requirements, modeling strategies, and deployment
- Develop and maintain data pipelines, manage the data lifecycle, and ensure data quality and consistency throughout
- Assure robust implementation of ML guardrails and manage all aspects of service monitoring
- Develop and deploy accessible endpoints, including web applications and REST APIs, while maintaining steadfast data privacy and adherence to security best practices and regulations
- Share expertise and knowledge consistently with internal and external stakeholders, nurturing a collaborative environment and fostering the development of junior engineers
- Embrace agile development practices, valuing constant iteration, improvement, and effective problem-solving in complex and ambiguous scenarios
- Designing and integrating scalable AI/ML systems into production environments, CI/CD tooling, Docker, Kubernetes, cloud AI resource utilization and management
Other
- Share expertise and knowledge consistently with internal and external stakeholders, nurturing a collaborative environment and fostering the development of junior engineers
- Embrace agile development practices, valuing constant iteration, improvement, and effective problem-solving in complex and ambiguous scenarios
- A growth mindset - welcoming the challenge of tackling complex problems with a bias for action
- Strong written and verbal communication skills - able to effectively communicate technical concepts to diverse audiences and creating clear documentation of system architectures and implementation details
- Proven ability to collaborate effectively across engineering, data science, product, and other teams to drive successful MLOps initiatives and ensure alignment on goals and deliverables.
