As Singapore’s longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.
Today, we’re on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia’s leading financial services partner for a sustainable future.
We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career.
Your Opportunity Starts Here.
About the Role:
We are seeking an experienced Senior AI Engineer to join our team and drive the development of scalable, production-grade AI solutions. The ideal candidate will combine deep expertise in artificial intelligence and machine learning with strong software engineering fundamentals, particularly in microservices architecture and multi-language development.
Responsibilities:
AI/ML Development
Design, develop, and deploy machine learning models and AI solutions that solve complex business problems.
Build and implement agentic AI systems with autonomous decision-making, reasoning, and task execution capabilities
Develop multi-agent systems that use tools, planning, and memory.
Build and optimise large-scale ML pipelines for training, evaluation, and inference.
Implement state-of-the-art algorithms in areas such as natural language processing, computer vision, recommendation systems, or predictive analytics
Conduct experiments, perform model evaluation, and iterate on ML solutions to improve performance.
Stay current with the latest AI/ML research and identify opportunities to apply emerging techniques.
Software Engineering & Architecture
Design and implement robust microservices architectures for AI/ML applications
Build scalable, maintainable, and well-documented code across multiple programming languages.
Develop RESTful APIs and event-driven systems to integrate AI capabilities into broader platforms
Ensure high availability, fault tolerance, and performance optimisation of AI services.
Implement CI/CD pipelines for automated testing and deployment of ML models.
Technical Leadership
Mentor junior engineers and data scientists on best practices in AI engineering and software development
Lead technical design discussions and contribute to architectural decisions.
Collaborate with cross-functional teams, including product managers, data scientists, and platform engineers.
Conduct code reviews and promote engineering excellence across the team
Drive technical innovation and champion the adoption of new tools and methodologies
Required Qualifications
Technical Skills
AI/ML Expertise – 5+ years of experience developing and deploying machine learning models in production environments
Agentic AI – Experience building autonomous AI agents with capabilities including tool use, reasoning, planning, and multi-step task execution
Programming Languages – Advanced proficiency in at least Python and Java.
Experience with Deep learning frameworks (TensorFlow, PyTorch), data processing (pandas, NumPy), ML libraries (scikit-learn), etc.
Experience with Spring Boot, microservices frameworks, and concurrent programming.
Microservices Architecture – 5+ years of hands-on experience designing and implementing microservices-based systems
ML Operations – Experience with MLOps practices, model versioning, monitoring, and deployment strategies
Cloud Platforms – Proficiency with AWS, GCP, or Azure ML services and infrastructure
Additional Technical Requirements
Strong understanding of distributed systems, message queues (Kafka, etc.), and event-driven architectures
Experience with containerization (Docker) and orchestration (Kubernetes)
Knowledge of database systems (SQL and NoSQL) and data engineering concepts
Familiarity with API design principles and RESTful services
Experience with version control (Git) and collaborative development workflows
Experience
Bachelor's or master’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience).
Proven track record of delivering complex AI projects from conception to production
Strong problem-solving abilities and analytical thinking
Excellent communication skills with the ability to explain complex technical concepts to diverse audiences
Experience working in agile development environments
Preferred Qualifications
PhD in Machine Learning, Artificial Intelligence, or related field
Experience with agentic AI frameworks (LangChain, AutoGen, etc.) and agent orchestration patterns
Hands-on experience implementing Agents patterns such as ReAct, Plain and Execute, etc.
Hands-on experience with advanced prompting techniques such as Chain-Of-Thought, etc.
Experience with transformer architectures and large language models (LLMs)
Knowledge of vector databases and retrieval-augmented generation (RAG) systems
Contributions to open-source AI/ML projects
Publications in top-tier AI/ML conferences or journals
Experience with real-time inference systems and model optimisation techniques
Knowledge of federated learning, edge AI, or distributed training
Familiarity with MLflow, Kubeflow, or similar ML platforms
Experience with multiple cloud providers and multi-cloud architectures
Experience with building LoRA/QLoRA, PEFT pipelines for enterprise-specific tuning
Experience implementing distributed training pipelines (Ray, FSDP, DeepSpeed, PyTorch Distributed, etc.)
Experience with integrating continuous feedback loops to improve the model incrementally
Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry-leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.
Skills Required
- 5+ years of experience developing and deploying machine learning models in production environments
- Experience building autonomous AI agents with tool use, reasoning, planning, and multi-step task execution
- Advanced proficiency in Python and Java
- Experience with TensorFlow, PyTorch, pandas, NumPy, and scikit-learn
- Experience with Spring Boot, microservices frameworks, and concurrent programming
- 5+ years of hands-on experience designing and implementing microservices-based systems
- Experience with MLOps practices, model versioning, monitoring, and deployment strategies
- Proficiency with AWS, GCP, or Azure ML services and infrastructure
- Strong understanding of distributed systems, message queues such as Kafka, and event-driven architectures
- Experience with Docker and Kubernetes
- Knowledge of SQL and NoSQL database systems and data engineering concepts
- Familiarity with API design principles and RESTful services
- Experience with Git and collaborative development workflows
- Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience
- Proven track record of delivering complex AI projects from conception to production
- Strong problem-solving abilities and analytical thinking
- Excellent communication skills for explaining complex technical concepts to diverse audiences
- Experience working in agile development environments
- PhD in Machine Learning, Artificial Intelligence, or a related field
- Experience with agentic AI frameworks such as LangChain or AutoGen and agent orchestration patterns
- Experience implementing ReAct, Plan and Execute, or similar agent patterns
- Experience with advanced prompting techniques such as Chain-of-Thought
- Experience with transformer architectures and large language models
- Knowledge of vector databases and retrieval-augmented generation systems
- Contributions to open-source AI or machine learning projects
- Publications in top-tier AI or machine learning conferences or journals
- Experience with real-time inference systems and model optimization techniques
- Knowledge of federated learning, edge AI, or distributed training
- Familiarity with MLflow, Kubeflow, or similar ML platforms
- Experience with multiple cloud providers and multi-cloud architectures
- Experience building LoRA, QLoRA, or PEFT pipelines for enterprise-specific tuning
- Experience implementing distributed training pipelines using Ray, FSDP, DeepSpeed, or PyTorch Distributed
- Experience integrating continuous feedback loops to improve models incrementally
What We Do
OCBC is the longest established Singapore bank, formed in 1932 from the merger of three local banks, the oldest of which was founded in 1912. It is now the second largest financial services group in Southeast Asia by assets and one of the world’s most highly-rated banks, with an Aa1 rating from Moody’s. Recognised for its financial strength and stability, OCBC is consistently ranked among the World’s Top 50 Safest Banks by Global Finance and has been named Best Managed Bank in Singapore by The Asian Banker. OCBC and its subsidiaries offer a broad array of commercial banking, specialist financial and wealth management services, ranging from consumer, corporate, investment, private and transaction banking to treasury, insurance, asset management and stockbroking services. OCBC’s key markets are Singapore, Malaysia, Indonesia and Greater China. It has more than 570 branches and representative offices in 19 countries and regions. These include about 300 branches and offices in Indonesia under subsidiary Bank OCBC NISP, and over 90 branches and offices in Mainland China, Hong Kong SAR and Macau SAR under OCBC Wing Hang. OCBC’s private banking services are provided by its wholly-owned subsidiary Bank of Singapore, which operates on a unique open-architecture product platform to source for the best-in-class products to meet its clients’ goals. OCBC's insurance subsidiary, Great Eastern Holdings, is the oldest and most established life insurance group in Singapore and Malaysia. Its asset management subsidiary, Lion Global Investors, is one of the largest private sector asset management companies in Southeast Asia.
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