Responsibilities
- Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
- Write and maintain scalable, performant and secure code that can be shared across platforms
- Meaningfully contribute to the product and core backend systems by suggesting and executing improvements
- Improve engineering standards, tooling, processes and security
- Develop novel, accurate, and performant ML algorithms for use at scale
- Conduct metric-driven research experiments to improve model performance
- Provide mentorship to and help onboard junior ML engineers
- Collaborate cross-functionally with other teams
- Utilize OWASP top 10 techniques to secure code from vulnerabilities
- Maintain awareness of industry best practices for data maintenance handling as it relates to your role
- Adhere to policies, guidelines and procedures pertaining to the protection of information assets
- Report actual or suspected security and/or policy violations/breaches to an appropriate authority