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Senior AI and Software Engineer

Summary

Architect and build an AI-driven logistics engine for a last-mile delivery network, designing distributed systems, ML pipelines, and real-time routing logic in Python on AWS.

Own the Architecture. Build the Intelligence. Scale the Network. uParcel operates one of Singapore’s largest last-mile delivery networks, and we are evolving our platform into a fully autonomous, AI-driven logistics engine. We’re hiring a Senior AI & Software Engineer to architect and build the core intelligence that powers real-time job assignment, routing efficiency, and driver-matching logic at scale. This is a high-impact engineering role for someone who wants to design distributed systems, build production-grade ML pipelines, and shape the technical direction of a fast-growing logistics platform.



Core Responsibilities



  • System Architecture & Backend Engineering

  • Architect and implement backend services using Python, Django, and modernmicroservice patterns

  • Design scalable, fault-tolerant systems deployed on AWS (EC2, ECS/Lambda,RDS, S3, CloudWatch, API Gateway, IAM, containers)

  • Build high-performance APIs for real-time decisioning, driver-job matching, andoperational workflows

  • Implement asynchronous processing pipelines using Celery, SQS, or equivalent



AI/ML Engineering



  • Lead the design and development of uParcel’s AI-driven job assignment engine,incorporating:

  • Real-time geospatial data

  • Driver availability, historical performance, and behavioral patterns

  • Delivery SLAs, urgency, and route constraints

  • Predictive ETA and load balancing models

  • Build ML pipelines for training, evaluation, and deployment (batch + real-timeinference)

  • Implement model monitoring, drift detection, and continuous retrainingworkflows



Data Engineering & Infrastructure



  • Design data schemas and pipelines to support high-volume event ingestion

  • Work with geospatial datasets, map APIs, and routing algorithms

  • Optimize query performance on relational and NoSQL datastores

  • Ensure observability across services (metrics, tracing, structured logs)



Technical Leadership



  • Drive architectural decisions and enforce engineering best practices

  • Conduct deep technical code reviews and mentor mid-level engineers

  • Collaborate with product, operations, and data teams to translate business logicinto deterministic, scalable systems

  • Own end-to-end delivery of features from design to production rollout



Required Technical Expertise



  • Strong computer science fundamentals: algorithms, data structures, distributedsystems

  • Expert-level proficiency in Python and production experience with Django

  • Deep understanding of AWS cloud architecture and infrastructure design

  • Experience building and deploying ML models in production environments

  • Strong knowledge of RESTful API design, microservices, and asynchronoussystems

  • Familiarity with geospatial computation, routing algorithms, or optimizationmodels

  • Experience with CI/CD pipelines, containerization (Docker), and IaC(CloudFormation)

  • Ability to reason about system performance, scalability, and reliability



Bonus Skills



  • Experience with reinforcement learning or real-time decision engines

  • Background in logistics, fleet optimization, or marketplace matching systems

  • Knowledge of graph algorithms, heuristics, or constraint-solving techniques

See also

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