AI/ML Engineer
GoTymeX (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 20–34 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Own the full ML lifecycle: design and optimize real-time and batch inference pipelines, then deploy and maintain models in a cloud-native, microservices-based banking platform.
- Build and evaluate models for use cases including fraud detection, credit scoring, transaction classification, personalization, and conversational AI; implement monitoring, A/B testing, and drift detection.
- Improve shared ML frameworks and workflows, and help ensure models are reliable and ready to scale across multiple markets.
Minimum Requirements
- Work Experience Required: 5+ years in machine learning engineering, data science, or related software development roles.
- Proven experience deploying and maintaining ML models in production environments.
- Strong Python and core ML library proficiency; understanding of algorithms, data structures, and distributed computing; experience with MLOps tools such as MLflow, Kubeflow, Airflow, Docker, Kubernetes, or CI/CD pipelines; familiarity with Spark, Kafka, or cloud data warehouses.
- Hybrid role based out of the Vietnam office; flexible arrangements are available for discussion.
Ideal Candidate Profile
- Has operated ML systems beyond experimentation, with practical experience in production monitoring, versioning, reliability, and performance over time.
- Consumer-product or fintech experience is a strong fit; the JD specifically prefers production ML experience in fintech, e-commerce, or large-scale consumer products.
- Can balance applied AI exploration—including LLMs and generative AI—with the constraints of deploying trustworthy models in financial services and scaling them across markets.