Machine Learning DevOps Engineer
Core
Developing platform and implementing fraud detection models within the banking sector.
Role type
Machine Learning DevOps Engineer
Builds
Data analytics platform and fraud detection models
Domain
Banking / Financial Services
Deliverable
production ML models
Required skills
Python, distributed computing (Spark 3.5+), cloud platforms (GCP, Azure), GitHub, Airflow/Cloud Composer, Spark/DataProc, Terraform, containerization, ML Ops, model deployment frameworks (Scikit-learn, Pandas, NumPy), code/compute optimization, unit testing
Preferred skills
code/compute optimization and tuning testing, handling large datasets for fraud detection, experience with other ML frameworks, Master's degree in CS/Statistics/Data Science, banking sector experience with fraud detection systems
Technologies
GCP, Azure, GitHub, Airflow, Cloud Composer, Spark, DataProc, Terraform, Scikit-learn, Pandas, NumPy
Responsibilities
Code/compute optimizations and unit testing, scheduling and distributing code on data analytics platform, working with shared model development codebase, assisting in model development and deployment, collaborating with data scientists, maintenance
Seniority
Senior, hands-on IC