Senior Algorithm Engineer / Algorithm Engineer

PDR Insurance Agency, LLC; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Our client, a high-growth international digital freight and logistics tech platform, is building its global hub in Singapore. Join an agile team designing high-concurrency, cross-border infrastructure from scratch.

You will own end-to-end ML systems, from routing and pricing to data pipelines and model deployment, with a stack centered on PyTorch/TensorFlow and Python/C++.

The role emphasizes cross-border localization and collaboration with global centers to tailor algorithms to varied markets.

Qualifications

• Bachelor’s degree or higher in a quantitative discipline (CS, math, OR, stats). PhD or Master’s is a strong plus.
• 2+ years of commercial experience in applied machine learning and algorithm design.
• Domain competencies in at least two fields: Geospatial data, time-series analysis, optimization/RL, causal inference.

Responsibilities

• Oversee end-to-end design of automated platform allocation logic, intelligent supply routing, and real-time valuation models.
• Drive data pipelines and model deployment using Spark/Flink; develop robust production-grade solutions.
• Analyze platform logs to identify friction points and optimize models to boost conversion and efficiency.
• Collaborate with global centers to adapt and scale core algorithms for diverse international markets.

Skills

Geospatial Data Engineering

Time-Series Analysis

Mathematical Optimization

Reinforcement Learning

Statistical Causal Inference

Uplift Modeling

Python

Education

Bachelor’s degree or higher in a quantitative discipline

Tools

PyTorch

TensorFlow

C++

Java

Golang

Job description

Our client is a high-growth, international digital freight and logistics technology platform. By leveraging advanced AI, cloud infrastructure, and predictive analytics, they build intelligent marketplaces that connect global shippers directly with freight networks to enable seamless, closed-loop transactions.

As part of their rapid international expansion across Southeast Asia and the Middle East, they are establishing their core global technology hub in Singapore. This is a rare opportunity to join an agile team building high-concurrency, cross-border infrastructure completely from scratch.

Key Responsibilities:

• Core Engine Optimization: Oversee the end-to-end design, refinement, and execution of automated platform allocation logic, intelligent supply routing, spatial-temporal search matching, and real-time dynamic valuation models.
• Predictive Pipeline Engineering: Autonomously drive the entire lifecycle of complex data systems—including spatial asset tracking data, predictive behavior modeling, feature engineering pipelines (Spark/Flink), and robust containerized production deployments.
• Data-Informed Diagnostics: Dive deep into platform transaction logs and operational flows to isolate algorithmic friction or drop-offs, executing strategic model changes to maximize platform conversion and supply-demand efficiency.
• Cross-Border Localization: Partner closely with global technology centers to adapt, fine-tune, and scale core algorithmic frameworks for highly fragmented international markets.

Requirements:

• Education: Bachelor’s degree or higher in a highly quantitative discipline (e.g., Computer Science, Data Science, Operations Research, Applied Mathematics, or Statistics). Ph.D. or Master’s is a strong plus.
• Experience: Minimum 2+ years of commercial experience in applied machine learning and algorithm design, with a proven track record in high-throughput architectures (e.g., High-Frequency Asset Dispatch/On-Demand Networks, Search Discovery, Personalized Recommendation Engines, or AdTech).
• Target Domain Competency (Strong foundation in at least two fields):
• Geospatial Data Engineering & Time-Series Analysis (route planning, asset tracking, ETA metrics).
• Mathematical Optimization & Reinforcement Learning (complex supply-demand balancing, elastic pricing, LP/MIP models).
• Statistical Causal Inference & Uplift Frameworks (user growth mechanics, dynamic incentive optimization).
• Technical Stack: Deep production experience with PyTorch or TensorFlow, alongside strong coding proficiency in Python, C++, Java, or Golang for low-latency model deployment.