MLOps Engineer

We re looking for a GCP ML/MLOps Engineering Specialist who is experienced in designing and implementing ML applications at scale in production for our ML Engineering team. The team is a cross-functional team and has ML Engineers and Software Engineers, and closely works with data scientists and data engineers in designing, building and operationalizing AI/ML models.

Roles and Responsibilities:

• As a ML Engineering Specialist, you will be a key stakeholder and owning responsibility in designing and architecting end to end ML solutions
• Operationalize ML models, NLP, Computer Vision and other type of models.
• End to End model lifecycle management, starting from feature extraction to monitor machine learning models using high end tools and technologies.
• Design & implementation of DevOps principles in Machine Learning
• Model quality assurance, governance, and monitoring
• Integrate models as part of business applications via APIs.
• Execute best practices in version control and continuous integration / delivery.
• Collaborate with data scientists, engineers, and other key stakeholders.
• Work well in a fast-paced cross-functional environment

Mandatory Skills/Requirements:

• Experience in implementing machine learning life cycle one of Vertex AI along with other GCP services.
• Experience with Machine learning frameworks, libraries, and agile environments.
• Experience implementing GCP AI services in business applications.
• Experience with various model deployment strategies
• Experience with Python and SQL is must. Understanding of distributed frameworks such as Spark, Dask, Ray etc. is a plus.
• Experience with version control tools such as Git, Bitbucket etc.
• Knowledge on Docker, Jenkins, Kubernetes, and other DevOps tools
• Knowledge on Infra-as-a-Code via ARM or Terraform templates.
• Familiarity with Large Language Models and Operationalization of foundation models on cloud platforms will be a plus.
• Outstanding analytical and problem-solving skills.