Senior Machine Learning Engineer

Posted 7 Days Ago
Be an Early Applicant
Singapore, SGP
In-Office
Senior level
Fintech • Payments • Financial Services
The Role
Design, build, deploy and operate an internal AI platform and agentic applications: retrieval/RAG, deployment CI/CD, monitoring, security-aware data access, and end-to-end ML microservice lifecycle. Provide architecture leadership, mentor engineers, and partner with InfoSec, product and data teams.
Summary Generated by Built In

About the Job:

You’ll work directly with the Head of AI Transformation to design, build, deploy and operate our internal AI platform. The scope is broad and designed to grow with you. In this role you will:

  • Build the platform’s foundation layers: retrieval and knowledge access over internal systems, an agent runtime and registry, and a governed data-access layer.
  • Build and operate the deployment platform that ships AI tools to business functions: scaffolding, CI/CD with built-in security checks, risk-tiered deploys, monitoring and rollback.
  • Build agentic applications and internal automation on top of the platform that streamline engineering and business workflows.
  • Favour open standards and reusable interfaces: assemble managed or open-source components for commoditised parts, and build only what is genuinely differentiated for us.
  • Own the end-to-end lifecycle of ML and agent microservices: planning, design, implementation, deployment and monitoring, in partnership with fellow engineers.
  • Write clean, efficient, reusable and maintainable code, and take ownership of existing codebases, systems and workflows.
  • Default to security and change-management thinking given the fintech, employee-data context, and partner closely with InfoSec, product, data scientists and business functions to define requirements.
  • Communicate clearly, translating complex technical concepts for both technical and non-technical audiences.
  • Grow with the role: as the platform and team mature, take on broader ownership across architecture, new capabilities and technical direction.

Additional scope: Senior MLE (SDE 3):

  • Drive architecture and technical direction across the platform’s layers and shared foundations (auth, integration interfaces, observability, deploy pipeline), built once and reused everywhere.
  • Guide and mentor engineers, and promote a culture of engineering excellence and continuous learning.
  • Lead planning and delivery of medium-to-large builds, and drive team productivity with sustainable development practices.

About You:

Must have:

  • Bachelor’s degree in Computer Science or equivalent practical experience.
  • Backend engineering experience: 4-7+ years (SDE 2), or 7+ years including technical leadership (SDE 3).
  • 3+ years of hands-on Python.
  • Strong with Flask/FastAPI, REST APIs, SQL, and at least one cloud (AWS/GCP).
  • Message queues (RabbitMQ, Kafka or SQS), Docker, and modern CI/CD practices.
  • Production monitoring and observability (e.g. Datadog, Grafana): tracking latency, errors and alerts on scalable backend systems.
  • Hands-on experience building LLM and agentic applications: RAG or retrieval pipelines, tool-calling and agent orchestration, and prompt engineering.
  • Excellent communication and cross-functional collaboration skills.
  • (SDE 3) Proven leadership planning and delivering medium-to-large software projects, plus mentoring.

Good to have:

  • Scaling chat-like platforms beyond 1,000+ active users: deep understanding of the architecture, performance and reliability challenges at that scale.
  • Deploying production-ready LLMs (via API and/or self-hosted models), with a solid grasp of observability, agentic concepts, memory, and token/prompt caching.
  • Streaming responses from backend to frontend: token streaming over Server-Sent Events (SSE), WebSockets or HTTP chunked transfer, delivering LLM output to the UI for responsive, real-time experiences.
  • Modern agent integration standards (e.g. Model Context Protocol) and building or integrating tool and agent interfaces.
  • Vector databases (pgvector, Pinecone, Weaviate) and embeddings.
  • Agent and LLM frameworks (LangGraph, LlamaIndex or similar) and enterprise search / RAG stacks.
  • Deploying ML models in production.
  • Integrating with enterprise tools and internal knowledge bases.
  • Experience in fintech or another regulated, security-sensitive environment.
  • Startup experience.

#LI-CT1

Skills Required

  • Bachelor's degree in Computer Science or equivalent practical experience
  • Backend engineering experience (4-7+ years for SDE2 or 7+ years including technical leadership for SDE3)
  • 3+ years of hands-on Python
  • Strong with Flask or FastAPI and building REST APIs
  • SQL proficiency
  • Experience with at least one cloud provider (AWS or GCP)
  • Experience with message queues (RabbitMQ, Kafka, or SQS)
  • Docker and modern CI/CD practices
  • Production monitoring and observability (e.g., Datadog, Grafana)
  • Hands-on experience building LLM and agentic applications (RAG/retrieval, tool-calling, agent orchestration, prompt engineering)
  • Excellent communication and cross-functional collaboration skills
  • Proven leadership delivering medium-to-large software projects and mentoring (SDE 3)
  • Scaling, deploying, and operating AI/agent platforms in security-sensitive or regulated environments
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The Company
1,707 Employees

What We Do

Kredivo Group is Southeast Asia’s leading provider of digital financial services through its brands Kredivo, KrediFazz and Krom. Kredivo is the leading digital credit platform in Indonesia and Vietnam that gives customers instant credit financing for ecommerce and offline purchases, and personal loans, based on real-time decisioning. Kredivo users can buy now and pay later across the entirety of Indonesia’s retail commerce network with one of the lowest interest rates amongst digital credit providers in the country. Krom Bank Indonesia (formerly known as Bank Bisnis Internasional, IDX: BBSI) is the group’s bank entity and the operator of the Indonesian neobank Krom. Kredivo Group is backed by leading financial and strategic investors such as Mizuho Financial Group, Square Peg Capital, Jungle Ventures, Naver Corp, Mirae Asset, Telkom Indonesia and Victory Park Capital among others

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