Informacje o stanowisku
Your new company
You will join global IT consulting company that specialises in transformational management and technology. After joining the organization, you will be supporting their clients from banking industry, in particular in cybersecurity area. Your expertise will help the client to build digital solutions that will allow customers to bank quickly, simply and securely.
In particular, you will become part of a team that is providing business controls over financial operations in particular trading and communications. The team is currently investing in Machine Learning tools to reduce false positives and improve their detection.
Your new role
As an MLOps Engineer, you will collaborate closely with team of Data Scientists to translate complex ML models into production solutions. You will be instrumental in building efficient and scalable Machine Learning pipelines on Google Cloud Platform while ensuring integration with our on-premises environments.
Your responsibilities will include:
- Establishing and maintaining best practices for ML Ops. Including version control, CI/CD pipelines and the Vertex Al Model Registry and End Points
- Implementing MLOps tools to streamline model development, training, tuning, deployment, monitoring and explain
- Deploying and Managing ML models on GCP's Vertex Al platform ensuring efficient and scalable execution
- Identifying and addressing performance bottlenecks in ML models and pipelines.
- Troubleshooting and resolving ML issues ensuring optimal model performance and costs. Working closely with Compliance Analytics data scientists to prepare and preprocess data for model training and evaluation.
- Assisting in feature engineering and selection to ensure model performance.
- Developing techniques to visualise and explain model behaviour ensuring model transparency and accountability in-line with PRA S51/23 guidelines.
- Collaborating with infrastructure and DevOps teams to establish efficient deployment and scaling strategies.
- Building and maintaining robust pipelines for model training, tuning and deployment leveraging components of Vertex Al and GCP tooling like Cloud Composer utilising Python and Java and Big Query.
- Implementing automated monitoring and alerting to track model performance and identify potential issues.
- Developing and maintaining data quality checks and validation including reconciliations in-line with Data Quality and Retention Controls.
- Implementing robust security measures to protect sensitive data and models.
What you'll need to succeed
- 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.
What you'll get in return
What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
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