Top Machine Learning Jobs in Kuala Lumpur

The IT Analytical Engineer develops BI solutions, supports self-service analytics, and collaborates to model data from various sources, enabling actionable insights.

The Data Scientist develops data solutions to drive business decisions, applying analytics and machine learning. Responsibilities include performing analyses, designing experiments, collaborating with teams, and ensuring data-driven decision making.

Develop data solutions for business decisions by applying analytics, experimentation, and machine learning. Collaborate with teams to improve products and enhance decision-making processes.

The LLM Applied Scientist will develop and optimize AI models using Large Language Models for Generative AI applications, collaborating with data scientists to improve workflows and deliver business value.

This role involves extracting and transforming data, designing algorithms for insights, applying best practices in software engineering, and developing analytics platforms.

The Senior Data Scientist will lead the development of data solutions by applying analytics and machine learning to enhance business decisions and product value. Responsibilities include analyzing user interactions, conducting experiments, mentoring team members, and collaborating with product teams to drive data-driven outcomes.

Leading marketing strategies for the Carousell Group's platforms, managing user acquisition and brand positioning, optimizing marketing efforts, and fostering a data-driven culture within the organization.

As a Data Associate, you will capture and label product images, manage datasets, verify data quality, and maintain high labeling accuracy in a fast-paced environment.

The Field Application Engineer will serve as the primary technical contact for customers, focusing on implementing AI/ML hardware/software solutions, collaborating with teams, and ensuring customer success.

Lead the AI product strategy at Goodnotes, overseeing development across various AI initiatives and ensuring alignment with company vision.

The Data Scientist will conduct data mining, utilize machine learning for model building, analyze datasets, develop insights, and mentor team members.

Lead and develop a global Site Reliability Engineering (SRE) team, ensuring system reliability and performance while driving strategic initiatives and fostering collaboration.

Support the development and testing of speech-to-text systems by reviewing audio clips and ensuring accurate transcriptions while meeting deadlines.

The Data Annotator is responsible for labeling datasets, reviewing annotations for quality, collaborating with AI teams, and meeting annotation targets.

The Technical Consultant will drive process improvements using AI, support strategic client implementations, and innovate payroll solutions through technology.

The Mobile Engineer will develop features for the MoneyLion mobile app, support QA, troubleshoot issues, and enhance code performance.

The intern will engage in full-stack development, collaborating with teams, optimizing code, and exploring AI techniques, while learning Agile methodologies.

Lead the design and implementation of AI systems, focusing on building production ML pipelines, improving model performance, and mentoring other engineers.

The Machine Learning Intern will work on applied computer vision pipelines, experiment with ML models, write well-structured code, and participate in design sessions.

The MLOps Engineer deploys ML models, manages cloud infrastructure, develops APIs, and ensures efficient ML solutions through collaboration with data scientists and engineers.

As the founding Lead Machine Learning Engineer, you will define the technical direction for an AI application, build training pipelines, develop model architectures, and lead product strategies in a high-impact role.

As a founding Machine Learning Engineer, you will transform language models into impactful products, fine-tune models, design data pipelines, and collaborate on AI features, significantly influencing the product's technical direction.

As an AI/ML Research Engineer, you'll fine-tune models, design datasets, evaluate performance, and collaborate to launch AI features, shaping a new consumer product.

As an AI/ML Agentic Engineer, you'll design autonomous AI agents, build multi-agent systems, and deploy predictive models while collaborating with stakeholders and advancing AI strategies.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.