Responsibilities
- Lead the creation and maintenance of scalable machine learning systems on AWS, using tools such as AWS Sagemaker for training and deploying models efficiently.
- Partner with product teams to build minimum viable products for AI-powered features, enabling fast iteration and real-world validation.
- Build and improve monitoring and alerting systems for machine learning models to maintain performance, stability, and uptime.
- Assist marketing and other departments in adopting AI and ML technologies, including advanced generative AI applications, across various business functions.
- Provide technical support for production-level machine learning systems, including debugging, incident response, and participation in on-call duties.
- Develop and expand machine learning architecture to accommodate growing user demand, applying AWS expertise and ML engineering best practices.
- Guide team members through code reviews, mentorship, and knowledge-sharing initiatives to strengthen technical proficiency.
- Keep current with emerging trends in machine learning and AWS platform updates, promoting the integration of innovative technologies within the organization.
Responsibilities
- Lead the creation and maintenance of scalable machine learning systems on AWS, using tools such as AWS Sagemaker for training and deploying models efficiently.
- Partner with product teams to build minimum viable products for AI-powered features, enabling fast iteration and real-world validation.
- Build and improve monitoring and alerting systems for machine learning models to maintain performance, stability, and uptime.
- Assist marketing and other departments in adopting AI and ML technologies, including advanced generative AI applications, across various business functions.
- Provide technical support for production-level machine learning systems, including debugging, incident response, and participation in on-call duties.
- Develop and expand machine learning architecture to accommodate growing user demand, applying AWS expertise and ML engineering best practices.
- Guide team members through code reviews, mentorship, and knowledge-sharing initiatives to strengthen technical proficiency.
- Keep current with emerging trends in machine learning and AWS platform updates, promoting the integration of innovative technologies within the organization.
