LLM Data Scientist/Algorithm Engineer – Top Talent Program

Posted 7 hours ago

This is a fully remote position, open to applicants in Singapore, +4 more countries.

πŸ“‹ Description

β€’ Take charge of the complete LLM pipeline, from data preparation to real-world production applications.

β€’ Create, refine, and enhance prompts across various products and languages.

β€’ Develop and sustain Retrieval-Augmented Generation QA/search systems linked to diverse knowledge bases.

β€’ Implement and manage LLM services utilizing vLLM/SGLang inference architectures in multi-GPU or clustered setups.

β€’ Design, execute, and oversee multi-agent LLM architectures using frameworks like LangGraph, CrewAI, and AutoGen.

β€’ Establish evaluation pipelines leveraging automatic metrics and human feedback to assess prompt and model quality, as well as bias and hallucination rates.

β€’ Work collaboratively with product and customer service teams to incorporate AI models into conversational chatbots.

β€’ Stay updated with the latest research, write technical blogs, and enhance existing architecture.


⛳️ Requirements

β€’ A Master’s Degree or higher in Computer Science, Data Science, or a related discipline.

β€’ Minimum of 2 years of experience in deep learning/NLP.

β€’ At least 1 year of hands-on experience with LLMs, including SFT, DPO, RAG, quantization, or inference optimization.

β€’ Proven expertise in prompt engineering and tuning, encompassing few-shot design, structured prompting, prefix-/p-tuning, reward re-ranking, and safety filtering.

β€’ Practical experience in constructing and deploying multi-agent LLM workflows.

β€’ Familiarity with agent-orchestrator patterns, shared memory, long-horizon planning, and guard-rail design.

β€’ Strong proficiency in English and Chinese communication skills.


🏝️ Benefits

β€’ Attractive salary and comprehensive company benefits.

β€’ Remote-first, work-from-home setup.

β€’ Opportunities for professional growth and ongoing learning.

β€’ Independence in a dynamic and innovative environment.

β€’ Collaboration with top-tier talent in a user-focused global organization.

β€’ A results-oriented workplace.

β€’ Chance to influence the future of finance.

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