Informacje o stanowisku

Salary range: 180-200 net / hour (B2B)

Kraków (hybrid, 6 days a month in the office)

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) 

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. 

Salary range: 180-200 net / hour (B2B)

Kraków (hybrid, 6 days a month in the office)

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) 

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. 

,[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 GCPs 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.  Requirements: GCP, BigQuery, Cloud, Storage, Airflow, AI, Terraform, Jenkins, Groovy, Python, PySpark, Docker, Spark, Java, CI/CD Pipelines, MLOps, DevOps, Cloud Composer, Security, Data engineering, Analytical skills

Praca Kraków

Kraków - Oferty pracy w okolicznych lokalizacjach