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IrisGo is seeking a Senior AI Engineer with extensive hands-on experience developing products powered by Large Language Models (LLMs) and Generative AI technologies. The role involves leading the design and development of advanced AI systems, from building prototypes to scaling production systems. The candidate will contribute to model selection, fine-tuning, evaluation, and safety mechanisms, and continuously improve prompt, RAG, and agent pipelines. The role requires staying at the forefront of GenAI developments and bringing innovative ideas into the product roadmap. The company is based in California and Taipei and is building an AI butler for the AI PC era.

VP of Marketing

Who we are:&nbsp;

AI workflow is broken. Digital work is buried under copy-paste routines, fragmented tools, and repetitive tasks that drain our time and focus.

 

We're building IrisGo — your AI butler for the AI PC era. It understands how you work, observes your context, and automates what you shouldn’t have to do. We’re a small team of engineers and builders driven to solve hard problems — from browser automation to computer use, from local LLMs to full workflow orchestration. We believe the future of productivity is ambient, intuitive, and immersive. Our goal: reclaim your time and focus, one automated task at a time.

 

Based in California and Taipei, we bring deep roots in full-stack engineering, machine learning, and product design. If you want to build the future of human-computer interaction, we’re hiring.

 

About the Role

We’re seeking a Senior AI Engineer with extensive hands-on experience developing products powered by Large Language Models (LLMs) and Generative AI technologies. This role is ideal for an engineer who brings a depth of experience in machine learning, a strong full-stack background, and a product-driven mindset.

 

You’ll help lead the design and development of advanced AI systems—from building prototypes to scaling production systems. The ideal candidate is excited by the challenge of applying cutting-edge AI in meaningful, user-focused ways, and thrives at the intersection of R&amp;D, engineering, and product.



<h3>What You’ll Do:</h3>
<ul class="posting-requirements plain-list">
<ul><li>Architect and implement scalable AI systems and applications powered by LLMs and multi-agent frameworks.</li><li>Lead end-to-end development efforts, including model integration, infrastructure design, and application logic.</li><li>Prototype and deploy GenAI applications that combine retrieval, tool use, reasoning, and interactivity.</li><li>Contribute to decision-making around model selection, finetuning, evaluation, and safety mechanisms.</li><li>Monitor AI/ML performance in production and drive continuous improvement of prompt, RAG, and agent pipelines.</li><li>Stay at the forefront of GenAI developments and bring innovative ideas into the product roadmap.</li></ul>
</ul>


<h3>What You Must Bring:</h3>
<ul class="posting-requirements plain-list">
<ul><li>4+ years of experience working in ML or AI engineering roles, ideally with a focus on NLP or GenAI.</li><li>Deep understanding of how modern LLMs work, including transformer architectures, finetuning, and evaluation.</li><li>Hands-on experience implementing and optimizing GenAI techniques such as: Tool/function calling, Multi-agent workflows, Retrieval-Augmented Generation (RAG), Finetuning or custom training (e.g., LoRA, PEFT), and Structured prompting and evaluation. </li><li>Proficiency with GenAI frameworks and tools (e.g., LangChain, LlamaIndex, Hugging Face, Haystack).</li><li>Experience integrating LLMs into real-world applications, including building internal tooling or customer-facing AI features.</li><li>Solid foundation in full-stack development or backend systems (Python, TypeScript, FastAPI, etc.).</li><li>Experience designing and deploying scalable APIs and cloud infrastructure (AWS, GCP, or Azure).</li><li>Proficient with databases (PostgreSQL, MongoDB, or vector DBs like Pinecone or Weaviate).</li><li>Comfortable working in agile product teams and balancing experimentation with shipping reliable code.</li><li>Strong Git/GitHub collaboration skills and comfort working with CI/CD workflows and containerization (Docker, etc.).</li></ul>
</ul>


<h3>Bonus Points:</h3>
<ul class="posting-requirements plain-list">
<ul><li>Experience working in a startup or research-oriented environment.</li><li>Prior exposure to open-source AI models (e.g., LLaMA, Mistral, Mixtral) and fine-tuning them.</li><li>Publications, technical blog posts, or demos of past AI work.</li></ul>
</ul>


#LI-DNI

 

#LI-Remote

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