AI Engineer for Financial Services: LLMs & MLOps

AVALLIS FINANCIAL PTE. LTD.; Singapore; Presencial; SGD 110.000 - 180.000; Tempo integral

Resumo da vaga

Avallis Financial seeks a hands-on Engineer to deliver AI features and components from design through to product support. You will work across software, data, AI, integration and operations, using approved AI tools to improve delivery with human review, traceability and accountability at the center of every outcome.

Requirements include 3–5 years in financial advisory or CRM, plus 3+ years building ML frameworks and experience with LLMs and foundation models.

Qualificações

• 5+ years software engineering experience.
• 3+ years designing and delivering ML frameworks and LLMS.
• Experience with LLMs and foundation models for enterprise use.
• Cloud-native with Azure and related services.
• Strong Kotlin and Python programming skills.
• Experience with CI/CD for ML systems.
• IT/CS/Math/statistics degree or related qualification.
• Certifications such as Azure AI Cloud developer.
• Experience with large-scale data prep and SQL.
• Excellent communication to bridge business and tech.

Responsabilidades

• Deliver AI features from design through production support.
• Work across software, data, AI, integration and operations.
• Build secure, observable, and resilient AI pipelines.
• Review designs and code, mentor engineers, identify risks early.
• Create blueprints and roadmaps for AI transformation.
• Manage versioning, deployment, rollback, diagnostics and incident support.

Conhecimentos

Kotlin

Python

Data manipulation

LLMs

MLOps

Communication

Cloud-native

Security & privacy

Formação

Computer Science / IT degree

Math/Statistics degree

Ferramentas

TensorFlow

PyTorch

Azure ML

Docker

Kubernetes

SQL

Descrição da vaga

Avallis Financial seeks a hands-on Engineer to deliver AI features and components from design through to product support. You will work across software, data, AI, integration and operations, using approved AI tools to improve delivery with human review, traceability and accountability at the center of every outcome.

Requirements include 3–5 years in financial advisory or CRM, plus 3+ years building ML frameworks and experience with LLMs and foundation models.