Top Machine Learning Jobs in Singapore

The intern will conduct research on driving behavior, collaborate across teams, utilize large datasets, and publish results related to Machine Learning.

The AI/ML Engineer will design and implement AI-driven automation solutions, manage product backlogs, and develop machine learning models, leading initiatives to enhance IT processes through advanced technologies.

The role involves supporting AI/ML model development and deployment, collaborating with stakeholders, and adapting to evolving technologies in digital manufacturing.

As a Senior Machine Learning Engineer - Search, you'll design and deploy advanced search and recommendation models, focusing on user intent and enhancing the GoFood and GoPay platforms.

Assist with evaluating machine learning models for cybersecurity, collect and preprocess datasets, conduct experiments, and contribute to ML pipeline development.

The ML Engineer will build and scale large-scale data systems and pipelines, focusing on workload orchestration, dataset curation, and quality improvement techniques for machine learning models.

The Principal Machine Learning Engineer will design and implement AI systems for game development, manage complex workflows, and optimize production models using Python and AWS.

As an AI/ML Software Engineer at Finite State, you'll develop AI-driven security features, integrate systems, and collaborate across teams, contributing to cybersecurity solutions for connected devices.

The role involves designing, building, and deploying ML models for compliance at a crypto exchange, focusing on reliability, auditability, and collaboration with data scientists and compliance experts.

As an MLOps Engineer, design and maintain ML pipelines, automate deployments, collaborate with data scientists, and ensure model performance and governance.

Responsible for developing and deploying production-grade machine learning systems, optimizing pipelines, and collaborating with engineering teams. Focus on deep learning and scalable inference systems.

The Senior Machine Learning Engineer will build and maintain crucial ML systems, ensure production reliability, debug issues, and mentor fellow engineers, focusing on end-to-end ownership and collaboration.

As Technical Lead, you will own the execution layer of ML systems, ensuring they are deployable, reliable, and efficient while collaborating closely with application engineering.

Lead the research direction for A1's AI system focusing on context representation, reasoning, planning, and orchestration. Decide on model architectures and evaluation frameworks while ensuring safety and alignment. Guide exploration of advanced techniques and shape product intelligence. Requires deep machine learning experience and a founder-like mentality.

As Technical Lead for Machine Learning, you will own and manage ML systems, ensuring they are production-ready while collaborating with engineering to integrate solutions.

The AI/ML Architect will guide customers in implementing AI solutions on AWS, manage project delivery, and mentor other technical staff, requiring strong expertise in machine learning and AWS services.

This role involves designing and deploying AI/ML infrastructures using Snowflake, working with customers on technical solutions, and presenting to diverse audiences.

Develop and optimize large-scale machine learning infrastructure, collaborating with quantitative researchers, and enhancing platform capabilities for scalability and efficiency.

The Machine Learning Ops Engineer will bridge Data Science, AI Engineering, and Production Infrastructure by architecting solutions for MLOps lifecycle, managing AI tech stack, and optimizing costs.

As a Machine Learning Engineer, you will design, develop, and deploy AI solutions, collaborate across teams, and improve model performance to drive growth.

The role involves leading the ML Acceleration team, driving strategies for optimizing ML model training, recruiting and mentoring engineers, and collaborating across teams.