Algorithm Engineer

ABOUT THE COMPANY

Our client is a digital freight platform that uses mobile internet, big data and artificial intelligence to help shippers and truck drivers match more efficiently and support the digitalisation of the logistics industry. Its platform serves more than 300 cities and over 100,000 routes.

WHAT YOU'LL DO

Develop and iterate the company’s core transaction-matching and marketing algorithms, driving continuous improvement across key business metrics.

Apply algorithms to improve user experience and overall business outcomes.

Independently deliver model-development submodules, including data processing, feature extraction, model training, deployment and monitoring.

Use data to identify gaps in models, mechanisms and strategies; propose improvements and drive them into production.

Work with senior technical colleagues to develop algorithmic improvements and innovations suited to the business.

REQUIREMENTS

Must Have

Fully bilingual in English and Mandarin, with the ability to communicate fluently in Chinese in a professional environment.

Bachelor’s degree or above in Computer Science or a related discipline.

Strong communication, learning agility, cross-team collaboration and execution.

Comfortable working onsite near Orchard Road, Singapore.

At least 1 year of relevant algorithm or machine-learning experience; experience in recommendation, search or advertising is strongly preferred.

Sound understanding of machine-learning principles and proficiency with mainstream machine-learning and deep-learning frameworks.

Strong programming fundamentals, logical thinking, data collection and analysis skills, and sensitivity to patterns in data.

Passion for algorithms, strong problem-solving ability, self-motivation and a high quality bar.

Ability to understand business and product requirements and translate them into practical model improvements.

Good to Have

Hands-on experience in causal inference, time-series forecasting, spatiotemporal data mining,

multi-task learning, online learning, reinforcement learning or operations research optimisation.

Experience deploying, monitoring and improving production machine-learning systems.