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Algorithm Engineer Intern – Cross-Border Netting & FX Optimisation Engine

We are looking for an Algorithm Engineer Intern to design and evaluate the core clearing and optimisation mechanisms powering our cross-border settlement engine. Instead of processing every transfer independently, our system aggregates and matches multi-currency payment flows between SMEs. Your work will focus on building optimisation models and simulation frameworks to maximise internal netting efficiency while minimising external settlement costs and liquidity risk. You will work directly with the founding team on mechanism design in a low-liquidity, imbalanced environment.

AlgoRemoteInternPosted 03/03/2026
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Optimisation Engineer Intern (Clearing & Matching Algorithms)

Working Structure: Remote, flexible working hours Duration: 6 Months Compensation: Paid Internship

Key Responsibilities

  • Design and implement order-matching and aggregation algorithms to optimise the internal settlement of multi-currency obligations.
  • Optimisation Modelling: Frame the clearing problem as a linear programming or combinatorial optimisation challenge. Minimise the total value of payments that need to exit our system (i.e., minimise external settlement costs).
  • Constraint Handling: Incorporate real-world constraints into the algorithms, such as: settlement deadlines (T+0, T+1, T+2), minimum batch sizes for external FX execution, client-specific liquidity requirements, etc.
  • Cycle Detection: Develop algorithms to detect "payment cycles" or "closed loops" among multiple companies (e.g., A pays B, B pays C, C pays A) to enable multilateral netting.
  • Simulation & Backtesting: Simulate the algorithm's performance using historical transaction data. Measure key metrics such as Netting Efficiency %, Reduction in Gross Settlement, and Cost Savings.

Required Skills & Qualifications

  • Education: Pursuing a degree in Computer Science, Mathematics, Quantitative Finance, or a related area.
  • Strong Programming: Expert-level proficiency in Python. Must be comfortable with data structures and algorithms.
  • Optimisation Knowledge: Familiarity with Linear Programming, Integer Programming, or Graph Theory. Experience with optimisation libraries (e.g., PuLP, OR-Tools, Pyomo, or Gurobi) is a massive plus.
  • Experience or a strong interest in AI/ML and intelligent systems is a plus.
  • Analytical Mindset: Ability to translate a business problem ("save money on fees") into a mathematical objective function ("minimise sum of external flows subject to constraints").
  • Curiosity: Interest in how money moves around the world and the inefficiencies in the current banking system.
  • Able to start as soon as possible

What You Will Gain

  • Experience working in an early-stage startup, directly with the founding team
  • End-to-end ownership of optimisation experiments and simulation systems
  • Practical experience solving real-world financial infrastructure problems
  • The opportunity to shape a core infrastructure component before scale

About Us

Money Pasar is a Singapore-based B2B cross-border payment platform focused on SMEs in Southeast Asia, aiming to enable borderless payments. Traditional cross-border transfers rely heavily on pre-funded liquidity and correspondent banking networks, leading to high fees, slow settlement times, and capital inefficiency.

We are building an alternative infrastructure layer that uses internal matching mechanisms to reduce external FX execution and optimise capital usage. Our system functions more like an exchange than a traditional remittance provider, netting and settling multi-currency obligations between businesses.

We are currently in the MVP and pilot phase, working closely with early SME users to refine our clearing engine and optimisation models.