Base: not specified; bonus/equity: bonuses, commis...
Hybrid
Scalable data pipelines
Feature engineering for ml
Python and java programming
As an ML Data Engineer, you will build and scale an AI-driven decisioning system that delivers hyper-personalized client experiences, ensuring the right action, at the right time, through the right channel, with the right offer, content, and placement
Job Summary
As an ML Data Engineer, you will build and scale an AI-driven decisioning system that delivers hyper-personalized client experiences, ensuring the right action, at the right time, through the right channel, with the right offer, content, and placement.
You will work end to end across the ML lifecycle, from data and features through to deployed, monitored, and continuously improving models, bridging cutting-edge research and production systems to deliver measurable, AI-driven value.
Become part of a team that thinks progressively and works collaboratively, with a comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable.
Matching Summary
As an ML Data Engineer, you will build and scale an AI-driven decisioning system that delivers hyper-personalized client experiences, ensuring the right action, at the right time, through the right channel, with the right offer, content, and placement.
Salary
Base: Not specified; Bonus/Equity: Bonuses, commissions, stock options where applicable; Benefits: Flexible benefits and comprehensive Total Rewards Program
Skills & Requirements
Must-have
Scalable data pipelines
Feature engineering for ML
Python and Java programming
ML lifecycle management
AWS cloud platform
DevOps and CI/CD tooling
AI-driven automation
Nice-to-have
Collaboration and communication skills
Hybrid cloud computing
Business process automation
End-to-end ML workflow experience
Productionizing experimental ML models
Key Requirements
Bachelor’s degree in Computer Science or related field
3+ years professional data or software engineering experience
Experience with Spark, Airflow, feature stores, ML platforms
Strong foundation in data and software engineering
Experience with DevOps and CI/CD tools like Jenkins and GitHub Actions