AI/ML Engineer

Management Level Definition:

Contributions impact technical components of HPE products, solutions, or services regularly and sustainable. Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Provides expertise and partnership to functional and technical project teams and may participate in cross-functional initiatives. Exercises significant independent judgment to determine best method for achieving objectives. May provide team leadership and mentoring to others.

What you will do:

• Experiment, design, develop and maintain machine learning models and pipelines with a high potential for value and scale.  
• Collaborate with other ML engineers, data scientists, product managers, and other engineers to ensure successful implementation of machine learning solutions. 
• Perform research and testing to develop or customize machine learning algorithms; conduct model training and evaluation as needed; integrate, test, tune and monitor the solutions developed.  
• Research and evaluate new technologies and tools for machine learning. 
• Maintain and update existing machine learning systems. 
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.  
• Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models. 
• Leads the project team for design and development of complex products and platforms, including solution design, analysis, coding, testing, and integration for building efficient, scalable and robust cloud subsystems.
• Reviews and evaluates designs, test plans, and develops code for compliance with cloud design and development guidelines and standards.
• Provides tangible feedback to improve product quality and mitigate risks.
• Represents the engineering team in various technical forums and provides guidance and mentoring to less-experienced team members.
• Drives innovation and integration of new technologies into projects and activities in the software systems design organization.
• Analyzes science, engineering, business, and other data processing problems to develop and implement solutions to complex application problems, system administration issues, or network concerns.

What you will need:

• Bachelor's or master's degree in computer science, engineering, information systems, or closely related quantitative discipline.
• Typically, 7-15 years experience.

Knowledge and Skills:

• Strong programming skills in Python & preferrable familiar with Golang
• Understanding microservice architecture and how they can be built in a containerized, Kubernetes-managed environment is central to all modern cloud-native applications.
• Designing and integrating software systems running on multiple platform types into the overall architecture.
• Evaluating forms and processes for software systems testing and methodology, including writing and executing test plans, debugging, and testing scripts and tools.
• Excellent written and verbal communication skills. Ability to effectively communicate product architectures and design proposals at senior management levels.