Expression of Interest- Multimodal AI & Applied LLM Researcher

Recruit123 is currently partnering with an established deep-tech organization to hire a Multimodal AI & Applied LLM Researcher. This is an exciting opportunity to play a key role in an upcoming new product launch while managing and expanding a specialized proprietary model portfolio.

What you will be doing:

In this role, you will focus on establishing new model architectures, educating cross-functional teams on technical machine learning capabilities, and ensuring each product portfolio receives strategic algorithmic focus. Your main day-to-day responsibilities will include going beyond standard API integrations to design, train, and fine-tune proprietary, production-ready multimodal models that seamlessly process text, vision, and audio simultaneously. You will execute tailored model deployment and optimization strategies aligned with principal performance guidelines, analyze model layers to increase inference efficiency and reduce GPU costs, and build strong relationships with data engineers, software architects, and product leads. Additionally, you will handle data-driven engineering detailing around matrix multiplication and vector search algorithms, manage your daily schedule to balance multiple research and production pipelines, support technical engineering seminars, and gather market intelligence on global AI trends to keep development fully aligned with company targets.

What we are looking for:

We are seeking candidates with at least 1 year of experience in applied machine learning research, deep learning, or large language model (LLM) development. Because you will handle complex, multi-modal data frameworks and high-performance computing infrastructure, strong organizational and time-management skills are essential. You should be highly adaptable, deeply comfortable navigating underlying mathematical frameworks, and able to switch implementation strategies smoothly throughout the day. Excellent technical communication skills are required, including the ability to address architectural objections or optimize inference bottlenecks alongside core engineering teams using patience and hard performance data.

Contact Information

For inquiries or to submit your application, please reach out to:

• Recruiter: Lian Cher Chieh

• UEN: 202511044R

• License No.: 25C2810

• EA Registration No: R1217705