Top Machine Learning Jobs in Singapore

Develop and optimize data pipelines for ML systems, collaborate with cross-functional teams, build and tune ML models, and monitor model performance.

As a software engineer, you'll develop end-to-end data analytics and ML solutions, working with open-source tools and collaborating remotely with global teams.

Lead R&D initiatives for autonomous vehicles focusing on perception and prediction. Responsibilities include defining team direction, advising on technology solutions, prototyping, deploying solutions, and mentoring engineers. Drive business impact through technological advancements in self-driving capabilities.

Develop and optimize ML data pipelines for genomic products, collaborate with teams on AI/ML models, and standardize ML operations.

As a Machine Learning Engineer, you'll collaborate with data scientists to implement AI solutions, optimize models, and integrate applications for client devices.

Lead projects in generative AI and ML, develop production models, mentor team members, and collaborate with cross-functional teams to drive innovation and best practices.

Assist in pioneering research in AI and ML at Sahara AI, focusing on innovative model development and collaboration with tech leaders.

As an Applied Machine Learning Engineer Intern, you will develop deep learning algorithms for autonomous perception, optimize and deploy models, and ensure dataset quality for training.

The role involves developing and optimizing large-scale language models, deploying solutions, and engaging in advanced research techniques for improvements. Collaboration across teams and staying updated with industry advancements are also key responsibilities.

Develop and optimize algorithms for product matching and price comparison while improving algorithm robustness in a live business environment.

The Site Reliability Engineer will ensure ML systems operate efficiently, manage resources, and improve stability and disaster recovery across multi-cloud environments.

The role involves optimizing search quality using machine learning and NLP techniques, focusing on search ranking algorithms for user experience.

This role involves overseeing the ML lifecycle, developing and deploying models, mentoring team members, and collaborating on business requirements for AI solutions.