Top Machine Learning Jobs in Singapore

As a Senior Machine Learning Engineer, you will collaborate with engineers and product teams to design and implement machine learning models, ensuring high-quality code and addressing business challenges through innovative solutions. Responsibilities include developing data pipelines and tracking emerging technologies.

The GCOA Enterprise Architect at Lilly is responsible for developing innovative technology solutions that enhance business productivity and efficiency. This role involves strategizing technology roadmaps, determining system architecture, aligning IT with business goals, and documenting processes through architectural models. The architect will work closely with stakeholders to ensure optimal technology usage and integrate emerging technologies into business processes.

The Senior Data Consultant leads teams to deliver data-driven projects for clients, formulating strategies and action plans, managing project delivery, and building customer relationships. They are problem solvers and project managers, skilled in adapting to diverse missions and leveraging data to drive business impact.

The AI Productivity Engineer role involves supporting the development and implementation of collaboration and conversational AI platforms within the company. The position is aimed at recent graduates, offering opportunities to learn about AI and software engineering, collaborate with IT teams, contribute to system integration, and improve employee experiences through AI-driven solutions.

As a Senior AI/ML Engineer, you will design, implement, and maintain machine learning algorithms and systems, collaborate with cross-functional teams, and integrate AI models into existing applications. You will advocate for best practices within the team while working in regulated environments, and ensure smooth operations by developing RESTful APIs and CI/CD pipelines.

The role involves full stack development, requiring expertise in both front-end and back-end programming. Key responsibilities include designing application architecture, developing software applications, ensuring performance, security, and compliance, as well as managing the software lifecycle from conception to completion.

As a Senior ML Engineer, you will lead projects concerning communication activities and machine learning for core business tasks. You will be responsible for developing ML models, collaborating with cross-functional teams, and sharing knowledge within your team. Your role involves ensuring projects progress from data to production while leveraging various ML tools and technologies.

As a Solutions Architect - AI/ML at Snowflake, you will build and deploy machine learning pipelines, work with technical teams and customers to design solutions, and utilize Snowflake features to enhance data science workflows. You will also need to present technical concepts to various audiences and maintain awareness of competitive technologies.