Top Machine Learning Jobs in Singapore

The role involves leading ML and MLOps initiatives, designing and deploying solutions on AWS while ensuring architecture governance and managing complex model/data pipelines to support Data Scientists. Strong communication and collaboration skills are essential to work with stakeholders and present technical information effectively.

The Staff Software Engineer will design and develop innovative AIOPS solutions, lead the team in AI code and implementation, and mentor junior members. Responsibilities include building scalable AI processing systems, resolving complex problems, and engaging in technical workshops for software integration.

As a Software (ML Product) Engineer at iterative.ai, you will enhance user workflows for DVC, collaborate with technical product managers, and improve MLOps practices within ML teams. Responsibilities include optimizing the tool’s usability and driving projects like dvclive, emphasizing software engineering skills and communication.

The Software Engineer (AI/ML) is responsible for both front and back end programming, designing application architecture, and ensuring application performance and integration with various frameworks. They will collaborate with teams to deliver projects from conception to completion and explore new technologies within Industry 4.0 digital solutions.

The Solutions Architect will design and implement cloud architecture solutions focusing on Ubitus, Tencent Cloud, and AWS. Responsibilities include cloud services integration, providing technical leadership, collaborating with customers on AI requirements, and maintaining technical documentation. The role also involves customer engagement through workshops and training, alongside travel for support and industry events.

The Software Developer I will design, develop, and implement software products for business projects, collaborating with teams and stakeholders. Responsibilities include coding, testing, quality assurance, and maintaining documentation while staying updated on new technologies and best practices.

The AI/ML and MLOps Field Engineer at Canonical will assist global companies in adopting AI using open source technologies on cloud infrastructures, primarily focusing on Linux and Kubernetes. Responsibilities include architecting cloud solutions, engaging in customer interactions, and solving complex data architecture problems using various data technologies.

The Solutions Architect - AI/ML at Snowflake will design and deploy AI/ML solutions for clients, ensuring successful implementation of data science pipelines using Snowflake's features. This role is technical and collaborative, focusing on customer needs, knowledge transfer, and continuous improvement of Snowflake products.