Lead Machine Learning Engineer
Summary
Lead a team to deploy and monitor ML models using Kubeflow, TFX, and GCP, focusing on pipelines, CICD, and DevSecOps for enterprise clients.
Customer is expecting a lead the ML engineers to work closely with architects on building Deployment Environment and Enterprise Launching of a set of Models
Your responsibilities:
- Work closely with clients Data Team on building Deployment Environment and Enterprise Launching of a set of Models (Predictive/Text-Embedding/Foundation etc)
- Build the Deployment Maturity with ML pipelines
- Monitoring and Operations Support of the Models
- Work closely with the Client's Data Science Team and Process Innovation Team to understand and improve the ways of working.
Your Profile
- Professional Knowledge on building ML Pipelines in Kubeflow, TFX using vertex AI as Orchestration layer.
- SDLC Maturity on Model Deployment & Monitoring
- Professional Knowledge in Python
- Maturity in Model Deployments which includes Data Preprocessing, Optimization & Training, Serialization if needed.
- AB Testing of Models
- GCP Knowledge
- CICDCT of Models
- Expertise in implementing and maintaining Container Registry,Artefact Registry for the ML models.
- Expertise in Code coverage and static code analysis tools like Pylint.
- Expertise in CML (Continuous Machine Learning) to implement CICD in ML Models.
- DevSecOps knowledge
- External certification in ML/Data Science.