Major Responsibilities:

- Support data scientists with AI/ML model development and deployment with an emphasis on auditability, versioning, and data security.

- Build and implement applications which makes use of AI/ML models

- Work with data scientists to ensure ML models are performing within the expected ranges of accuracy

- Lead Self Service AI (SSAI) initiatives by supporting the citizen data scientists

- Support AI/ML platforms like Sage Maker, SAS Viya or Dataiku

- Design data pipelines and engineering infrastructure to support our enterprise machine learning systems

- Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc.

- Facilitate the development and deployment of proof-of-concept machine learning systems.

- Develop and deploy scalable tools and services for our clients to handle machine learning training and inference.

- Take offline models data scientists build and turn them into a real machine learning production system.

- Experience in technologies, frameworks and architecture like Java or Python, Angular, React, Spring, Spring Boot, XML, JavaScript, JSON, Application Servers, CI/CD is required.

- Experience using AI/ML platforms such as Dataiku, Sage Maker or SAS Viya to deploy Models

- Ability to identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems.

- Understanding of the full system development lifecycle.

Mandatory Skills:

- Bachelor's Degree in Computer Science/Computer Engineering or equivalent years of experience.

- 1-3 years of experience developing software applications and exposure to Machine Learning

- Experience in technologies, frameworks, architecture, and design patterns.

- Strong coding skills in languages like Python and software engineering best practices.

- Experience in designing and building REST APIs and Microservices is required.

- Experience with Relational Databases, MySQL, In-Memory databases, NoSQL databases and writing SQL queries.

- Experience with AWS cloud technologies is a significant plus.

- Understanding of Machine Learning concepts, MLOps and experience using AI/ML platforms such as Dataiku, Sage Maker, or SAS Viya is a plus but not required.

- Responsible for implementation and operationalization of Self-Service AI Models.

- Experience customizing Conversation AI platforms is a plus.

- Ability to identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems.

- Design data pipelines and engineering infrastructure to support our enterprise machine learning systems at scale is a significant plus

- Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. is a significant plus.

- Support model development, with an emphasis on auditability, versioning, and data security.

- Facilitate the development and deployment of proof-of-concept machine learning systems.

- Develop and deploy scalable tools and services for our clients to handle machine learning training and inference.

- Take offline models data scientists build and turn them into a real machine learning production system.

- Ability to work in a team environment and seek guidance on tasks from senior developers and leads.

- Regular, predictable, full attendance is an essential function of the job. Must be willing and able to contribute to brainstorming sessions in a meaningful way.

- Willingness to travel as necessary, work the required schedule, work at the specific location required, submit to a background investigation (to include past employment, education, and criminal history) and drug screening are required.