ML Engineer

Opportunity

We are seeking a ML Engineer to join our team. As the Machine Learning Engineer working in Advanced Analytics team, you will be in a high impact role. You will be supporting multiple businesses and functions with their data science initiatives.  

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 Sage Maker, SAS Viya or Dataiku to deploy Models is a significant plus but not required.
• 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.
• Other projects/tasks as assigned.
  

Qualifications needed

• 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.
• As part of Advanced Analytics team you will be 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.