Senior Data Scientist (AI/ML)

TL;DR

Senior Data Scientist (AI/ML): Developing end-to-end analytic solutions for Predictive and Prescriptive Analytics with an accent on Extreme Multilabel Classification and deep learning. Focus on building scalable production-ready solutions, fine-tuning LLMs, and optimizing models on GPU infrastructure.

Location: Hybrid in Kuala Lumpur, Malaysia

Company

hirify.global is a global consumer intelligence company that leverages AI and ML to provide comprehensive insights into consumer buying behavior and market trends.

What you will do

• Build scalable, production-ready data science solutions utilizing Tech & Durable Point-of-Sale data.
• Develop, fine-tune, and deploy state-of-the-art neural networks for Extreme Multilabel Classification.
• Collaborate cross-functionally with product managers, engineers, and stakeholders to transform business problems into actionable insights.
• Partner with MLEs and SREs to integrate and deploy models into live production pipelines.
• Mentor junior team members and working students, serving as a methodological expert.
• Conduct research to drive the development of product-focused Data Science solutions for the T&D business.

Requirements

• Degree in computer science, data science, statistics, or a related field.
• 5+ years of experience in a Data Science role.
• Expert knowledge of PyTorch and optimizing deep learning algorithms on GPU infrastructures.
• Experience with fine-tuning Large Language Models (e.g., HuggingFace).
• Proven ability to ship large-scale models to production environments.
• Professional working proficiency in English.

Nice to have

• Familiarity with other ML frameworks such as scikit-learn and TensorFlow.
• Experience with software engineering best practices including version control, Agile, and Scrum.
• Hands-on experience with GCP and productionizing models via REST API and containerization.

Culture & Benefits

• Flexible working environment with a hybrid work model.
• Ongoing training and opportunities for personal and professional growth.
• Access to LinkedIn Learning.
• Employee-Assistance-Program (EAP) and volunteer time off.
• Exposure to the latest digital technologies in a diverse, collaborative environment.