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 modern
microservice 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, and
operational 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‑time
inference)
Implement model monitoring, drift detection, and continuous retraining
workflows.
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 logic
into 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, distributed
systems
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 asynchronous
systems
Familiarity with geospatial computation, routing algorithms, or optimization
models
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
