Area

In Data Science Platform Squad, we Build and maintain a generic, scalable and govern platform for Data Science model of online models to enable an automated, compliant and efficient Model Life Cycle process. We use technologies like Open-Shift to build Containerized platform for Hosting Model execution & Deployment.

Our squad is responsible for hosting Python statistical and machine learning models, primarily serving the Data Science communities who develop these models on behalf of various enterprise domains within the bank. We manage AAPF (Advanced Analytical Platform for Fraud), which works alongside CMDEP (Containerized Management Deployment and Execution platform) to execute machine learning models for scoring payment transactions for fraud, including e-banking domestic/international and District International models deployed in CMDEP. Additionally, we are tasked with transforming the current On-Prem infrastructure into a Cloud-Native platform.

As a MLOps IT Platform Engineer, you will work closely with the Product Owner and Chapter Lead in a “2 in a box” model, using agile methodologies. You will be responsible to develop and maintain scalable ML pipelines on futured MLOps platform built on AWS and Databricks. You will be tasked with ensuring seamless and automated transition of models from development to production using CICD workflows, implement the infrastructure as code. You will ensure that our machine learning models operate reliably, efficiently and at scale.

Mission

• Implement automated pipelines for model training, validation and inference
• Build and maintain CI/CD workflows using Github actions to ensure model code is versioned and seamlessly deployed to production
• Utilize tools like MLflow for model tracking, versioning and deployment
• Use terraform to provision and manage scalable secure infrastructure required for ML workloads
• Leverage docker containers to build, deploy and manage containerized ML models

Skills

• Minimum of 2 years of practical experience in MLOps platform to build model development deployment, execution and maintenance of ML pipelines
• In-depth knowledge of AWS services and Databricks
• Proficiency in Python, Pyspark
• Experience in CI/CD tools Terraform and container orchestration
• Problem-solving and debugging skills
• Understanding and practical experience with PubSub and Kafka streaming services would be beneficial
• Upper-Intermediate English skills

We offer:

We will ensure that exact salary offered for you will be based on your qualifications, competencies, professional experience and requirements for the corresponding job function (salary range from 3280 EUR to 4920 EUR gross EUR/monthly).

Your title in job contract will be IT Platform Engineer.

Dinesh Chaudhari