About ADVANCE.AI
ADVANCE.AI is a leading AI and big data company in Asia, dedicated to solving digital transformation, fraud prevention, and process automation for enterprise clients. Established in 2016 and headquartered in Singapore, we combine deep local market knowledge with superior AI technology. Our expertise lies in natural language processing (NLP) and computer vision, assisting clients with chatbots, anti-fraud solutions, facial recognition, e-KYC, and optical character recognition (OCR).
Currently, we partner with over 1,000 enterprise clients across Southeast Asia, South Asia, and Mexico in sectors such as banking, financial services, fintech, payments, retail, and e-commerce. ADVANCE.AI was recognized as No. 1 on LinkedIn’s 2021 Top Startups List in Singapore.
As part of the Advance Intelligence Group, an AI-driven technology company with over 1500+ employees in 12 markets worldwide, we share a unified vision: to Advance with Intelligence for a Better Life—for our customers, colleagues, and communities.
Our culture is built on core values:
- We foster an INNOVATION mindset
- We achieve results with EFFICIENCY and excellence
- We take pride in the QUALITY of our work
- We uphold INTEGRITY in all we do
- We embrace COLLABORATION to work across business lines and borders
Job Responsibilities
- Build machine learning infrastructure that allows research scientists to move faster in every step of ML.
- Build and maintain automated pipelines for training, storage, validating, serving, and monitoring of ML models.
- Enable rapid experimentation and feedback loops in our model serving code to continuously improve.
Job Requirements
- Bachelor’s, Master’s, PhD degree or equivalent related professional experience.
- Minimum 3 years of software engineering experience.
- Proficiency with Python, preferably in an ML context.
- Familiarity with backend technologies, e.g., SQL Database, Nosql, cache, message queue, etc.
- Experience with Kubernetes is a must.
- Familiarity with CI/CD and DevOps concepts.
- Familiarity with tools in MLOps, such as KubeFlow, AWS Sagemaker, MLFlow, etc.
- Experience with training, evaluating, and deploying machine learning models is an added plus.