Lead MLOPs Engineer

Technology stack

•         GCP (must have!) , BigQuery, Cloud Storage, Apache Airflow, Cloud Composer,

·       Vertex AI, Dataproc, Compute Engine

•         CI/CD and Build tooling: Terraform, Terragrunt, Jenkins, Groovy, Crane, Kaniko

•         Python, PySpark, Docker, Jupyter, Apache Airflow, Spark, Java (optional, but would

·       be beneficial)

 

Key Responsibilities

•         Establish and maintain best practices for ML Ops. Including version control, CI/CD

•         pipelines and the Vertex Al Model Registry and End Points.

•         Implement MLOps tools to streamline model development, training, tuning,

•         deployment, monitoring and explain.

•         Deploy and Manage ML models on GCP's Vertex Al platform ensuring efficient and

•         scalable execution.

•         Identify and address performance bottleneck in ML models and pipelines.

•         Troubleshoot and resolve ML issues ensuring optimal model performance and

•         costs. Work Closely with Compliance Analytics data scientists to prepare and

•         preprocess data for model training and evaluation.

•         Assist in feature engineering and selection to ensure model performance

•         Develop techniques to visualize and explain model behavior ensuring model transparency and accountability in-line with PRA S51/23 guidelines.

•         Collaborate with infrastructure and DevOps teams to establish efficient deployment and scaling strategies.

 

Pipeline Development:

•         Build and maintain robust pipelines for model training, tuning and deployment leveraging components of Vertex Al and GCP tooling like Cloud Composer utilizing Python and Java and Big Query.

•         Implement automated monitoring and alerting to track model performance and identify potential issues.

•         Develop and maintain data quality checks and validation including reconciliations in-line with Data Quality and Retention Controls.

•         Implement robust security measures to protect sensitive data and models.

 

Required Skills and Experience:

•         Strong proficiency in ML Ops principles and tools.

•         Proficiency in data engineering and pipeline development.

•         Experience with GCP including Big Query, Cloud Composer and Vertex Al.

•         Strong problem-solving and analytical skills.

•         Strong proficiency in Python

•         Experience with Java would be beneficial.

To learn more about Antal, please visit www.antal.pl