LLM Algorithm Tech Lead (Intelligence Architecture & Applied LLM Systems) - Singapore

About Plaud Inc.

Plaud is building the world's most trusted AI work companion for professionals to elevate productivity and performance through note-taking solutions, loved by over 1,000,000 users worldwide since 2023. With a mission to amplify human intelligence, Plaud is building the next-generation intelligence infrastructure and interfaces to capture, extract, and utilize what you say, hear, see, and think.

Plaud Inc. is a Delaware-incorporated, San Francisco-based company pushing the boundary of human–AI intelligence through a hardware–software combination. With SOC 2, HIPAA, GDPR, ISO27001, ISO27701, and EN18031 compliance, Plaud is committed to the highest standards of data security and privacy protection.

To learn more about Plaud, please visit https://www.plaud.ai and follow along on Instagram, X, Facebook, LinkedIn, and YouTube.

Why You Should Join Us

Plaud is building the next generation intelligence infrastructure and interfaces to capture, extract, and utilize intelligence from what people say, hear, see, and think.

• Plaud is a bootstrapped, skyrocketing, profitable company with a $250M revenue run rate achieved in just three years.

• Define the next-gen paradigm for human-AI interaction.

• Gain exposure to cutting-edge AI for Pro tools and play a direct role in our global expansion.

• Work with passionate teammates who value innovation, collaboration, and customer success.

• Grow your career in a culture that champions continuous learning and fast career development.

• Market-competitive compensation, global exposure, and a vibrant, creativity-fueled work atmosphere.

About the Role

We are seeking an experienced LLM Algorithm Tech Lead to drive the design of AI intelligence architecture and lead the end-to-end application of large language models in real-world product environments. This role focuses on reasoning capability design, intelligent behavior frameworks, knowledge/RAG pipelines, inference optimization, and cross-team engineering collaboration.

You will architect the core intelligence layer behind next-generation AI products and ensure LLM capabilities can be reliably, safely, and efficiently applied in production.

Key Responsibilities

1. Intelligence Architecture Design

• Design LLM reasoning frameworks: task decomposition, structured reasoning, and decision logic

• Architect intelligent behavior modules including context handling, memory mechanisms, and proactive insights

• Define the capability roadmap and build modular, extensible intelligence components

1. Applied LLM System Development & Production Integration

• Lead the full lifecycle of LLM-powered features: requirement → design → prototyping → production

• Optimize model outputs for reliability, consistency, controllability, and domain suitability

• Implement hallucination mitigation strategies via prompting, constraints, and structured reasoning

1. Knowledge Integration & RAG Pipelines

• Build multi-source retrieval pipelines for structured and unstructured data

• Own chunking, embedding, reranking, and context-injection strategies

• Ensure RAG-enhanced reasoning is stable and production-grade

1. Inference Optimization & Model Strategy

• Evaluate and select LLMs (OpenAI, Claude, DeepSeek, Qwen, Llama, Gemini, Mistral)

• Build model-routing logic based on latency, cost, performance, and task type

• Work with engineering to optimize runtime, memory usage, and system availability

1. Cross-Functional Collaboration

• Partner with engineering, product, and data teams to deliver high-quality LLM features

• Define evaluation standards, monitoring metrics, fallback strategies, and safety constraints

• Lead issue investigation and optimization in production systems

Requirements

Must-Haves

• 5+ years of experience in NLP/LLM/AI development

• Strong expertise in prompt engineering, LLM reasoning design, and applied ML architecture

• Experience deploying LLM-powered features in production

• Familiarity with RAG/knowledge pipelines and hallucination mitigation

• Strong system thinking and ability to architect complex workflows

• Excellent communication and cross-functional collaboration skills

• Ability to work effectively in global, distributed teams

Nice-to-Haves

• Experience with personalization, memory systems, or agent workflows

• Familiarity with LLM eval pipelines and safety mechanisms

• Experience leading small technical teams

• Experience with large-model algorithm design or foundational model capability development (architecture, distillation, quantization, optimization)

• Experience in multi-modal reasoning or large-scale systems

Why Join

• Architect intelligence for next-generation AI products

• High autonomy in technical direction

• Work with top AI engineers across countries

• Influence global-scale intelligent systems