AI / ML Engineer
We are seeking an AI / ML Engineer to build AI-native risk workflows, model evaluation pipelines, and production ML systems that help financial institutions reason through complex risk decisions.
- This role is intended for candidates currently based in Malaysia and able to work without visa sponsorship.
- Proficiency in Bahasa Melayu is required (spoken and written).
- This is not a remote role. In-person client and team meetings in Klang Valley are required.
A Malaysia-based risk analytics SaaS startup.
We provide quantitative risk solutions and consulting services to financial institutions, including banks, asset managers, and insurance companies.
Our platform focuses on building industrial-grade quantitative risk engines across market risk, credit risk, liquidity risk, and climate risk, while actively integrating AI and machine learning into risk workflows. In addition to software delivery, we work closely with clients on model design, validation, stress testing, and regulatory-aligned analytics.
As a startup, we work as a small, tight-knit team. This is not an ordinary job. Every team member plays a meaningful role in shaping the product, supporting clients, and growing the company.
AI that survives real risk workflows.
You will work on AI systems that need to be explainable, testable, and useful in regulated financial workflows. The work spans:
You are not expected to know every AI technique, but you should have strong ML fundamentals, good engineering judgement, and a serious attitude toward evaluation.
This role goes beyond demos. You will work closely with founders, engineers, and clients to turn AI capabilities into dependable product features.
The successful candidate must be able to attend in-person meetings in the Klang Valley when required.
What you bring.
- Strong proficiency in machine learning, applied AI, statistics, computer science, or a related field.
- Experience with LLMs, retrieval workflows, classification, ranking, forecasting, or anomaly detection.
- Practical understanding of model evaluation, dataset design, error analysis, and monitoring.
- Ability to work with financial or market data is preferred; curiosity about risk management is required.
- Strong foundation in statistics, mathematics, computer science, or related fields.
- Proficiency in programming for analytical and system development work, especially Python.
- Basic awareness of software security, privacy, and reliability for AI systems is expected.
- Experience with MLOps, vector search, experiment tracking, or model serving is a plus.
- Strong problem-solving ability, with attention to detail and numerical accuracy.
- Ability to communicate clearly with both technical and non-technical stakeholders.
- Professional qualifications such as FRM, CQF or CFA (completed or in progress) are an advantage but not required.
Impact matters more than job titles.
- Strong technical curiosity and willingness to learn.
- Comfortable working in a small, fast-moving team.
- Takes ownership and responsibility for outcomes, not just tasks.
- Willing to work across disciplines when needed.
- Communicates clearly and works well with others.
- Understands that in a startup, impact matters more than job titles.
Real models. Real institutions. Real ownership.
- Direct impact Be part of a startup team where your work directly affects the product and company growth.
- Real models, real clients Work on real quantitative models used by financial institutions.
- Cross-disciplinary exposure Gain exposure across quantitative modelling, AI, engineering, and data pipelines.
- Build for production Learn how systems are built, secured, and improved in a real-world environment.
- Grow with the company Opportunity to grow with the company as it scales — both technically and professionally.
Sound like you? Let's talk.
Send your CV and a few lines on your strongest area. We read every application.