Top Machine Learning Jobs in Singapore

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.

Conduct research on 3D/4D scene reconstruction and generative AI, develop models, publish research, mentor junior researchers, and oversee project progress at NTU's College of Computing and Data Science.

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.

Own end-to-end ML projects focused on recommendation and LTV signals: develop, evaluate, and deploy models; build training/scoring pipelines; run A/B tests; monitor production models; collaborate with product and analytics; mentor colleagues.

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 Staff Machine Learning Engineer at Coupang Play will develop recommendation and personalization systems, manage data collection, and validate model performance.

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.

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

Senior Machine Learning Engineers design and develop scalable architectures for ML applications, collaborating with teams to ensure effective deployment and maintenance of ML systems while driving functional streams of work and mentoring engineers.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

The ML Systems Engineer will optimize distributed training systems, develop high-performance GPU kernels, and ensure efficient data pipelines for machine learning models.

The Senior Software Engineer will own the CDE platform, architect AI agents for ML workflows, and collaborate with ML Engineers to enhance productivity.

This internship involves building AI bots using reinforcement learning, running experiments on model performance, and researching new improvement methods.

The Applied AI Engineer will onboard customers onto Mistral AI products, ensure effective integration, collaborate on advanced AI applications, and improve product capabilities based on user feedback.

Lead MLOps efforts by designing, building, and maintaining ML pipelines, implementing CI/CD workflows, mentoring engineers, and ensuring data privacy and compliance.

The Senior Software Engineer will design and build an AI/ML platform, optimize performance for deep learning, and lead engineering initiatives.

The Power ML Engineer will adapt existing models for the Japanese power market, enhance forecasts by integrating market signals, develop new product features, and improve monitoring tools while collaborating with the product team.