Position Overview:
As a Machine Learning Engineering Specialist, you will be responsible for the design, development and monitoring of platforms that will help streamline the creation and deployment of data science solutions made by our Data Scientists. This professional will help us constantly improve our ML engineering practice, integrate recent technologies to existing/future architecture, and develop the technical expertise of the team.
What will be your responsibilities?
Work with our Data Scientists to optimize models and microservices serving the model. The MLE should know when to optimize the microservice vs the model.
Work with other Machine Learning Engineers to ensure AI/ML models are built to optimum performance and maintainability standards.
Design, develop, and maintain software packages for use by our Data Scientists to help improve their model development workflow.
Design, develop, and maintain microservices that will enable other teams to call our models as an endpoint.
Set standards on best practices for building microservices for our models.
Design, develop, and maintain CI/CD pipelines to improve the model development workflow of the team and decrease turnaround time for model deployment.
Design and implement platform tools and microservices.
Design and implement a reliable and scalable infrastructure for our platform tools and microservices.
Provide guidance on best practices for code and architecture of microservices and do code and architecture reviews to ensure adherence to best practices.
WHAT ARE WE LOOKING FOR?
With at least a bachelor's degree in any quantitative discipline (i.e. Computer Science, Computer Engineering, etc.)
Moderate experience (at least 2 years) in working with AWS or any Cloud providers (such as GCP or Azure).
Moderate experience in building continuous integration and continuous delivery using Gitlab CI, Jenkins, AWS Code Pipeline, etc.
Moderate Experience working with docker, Kubernetes, and other container management solutions.
Experience with infrastructure tools like Terraform and CloudFormation.
Strong Automation and Problem-solving skills.
Good programming skills (Python, R, Bash scripting).
Moderate Experience working in an Agile, Dev Ops, Test Driven Development environment.
Some experience with common data science tools, packages (Pandas, SKLearn, TensorFlow), and concepts.
Some experience with training machine learning models.
Having at least 2 years of experience in designing CI/CD pipelines
Having at least 2 years of experience in creating microservices
Having at least 1 year of experience in managing stakeholders