Senior AI and Software Engineer

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

Please complete assessment quiz on https://coderbyte.com/sl-candidate?promo=uparcel-9w359:software-engineer-le37qwwizk&invb=user813jshxz

uParcel has planned, matched and optimised millions of same day deliveries using our proprietary logistics technology platform. Backed by data and driven by an innovative decentralised clustering model, we provide the most efficient deliveries to consumers through artificial intelligence assignment of delivery jobs to our network of delivery partners.

In contrast to the traditional hub-and-spoke last mile delivery model, our point-to-point clustering model enable same day deliveries efficiently by removing the need for extensive packaging, warehouse sorting and reducing distance travelled for greater productivity.

Our vision is to become the leading logistics platform that enables greater resource sharing and optimized routing to move the world more sustainably.

We are currently present in Singapore and Malaysia, with expansion plans to the rest of the region.