Applied AI Engineer

General Description

Argon is building an AI powered OS for pharma. We’re building deep integrations across pharma’s data systems to build a layer of artificial intelligence to power broad decision making assistance. We’re excited to enable the next generation of scientists and pharma companies to bring life saving therapies to market faster and more efficiently.

This role is right for you if you want to build hundred-step agents, design the future of human and machine interactions, and directly impact the rate of progress in both AI and human health.

We’re partnering with some of the biggest names in pharma and have strong early traction with a healthy pipeline to grow into. We are well funded and backed by top investors, including Y Combinator, Wireframe Ventures, and Crosslink Capital.

We value kindness, intensity, direct communication, intellectual honesty, and grit. Join us if you want to be productive, ship, and help build Argon AI.

This is an in-person role based out of our NYC offices.

Responsibilities

As a Founding Applied AI Scientist / Engineer at Argon, you will help lead our AI efforts. Your efforts will be focused on building domain specific AI and RAG systems on top of large pharma datasets. We are looking for individuals with past AI / ML experience that are excited about building the agentic pharma systems of the future.

1. Balancing product and research. You want to operate at the frontier of applied AI. You stay up to date with research on prompting techniques, model capabilities, domain specific finetuning

2. Master of prompts & agentic workflows. You’ll lead our efforts to get models to perform how we want them to. This includes getting the right tone & format but also enabling models with tool use, in-context-learning (ICL), and other techniques to get the very best out of the LLMs.

3. Building a proprietary dataset. Work with the team to commission the creation of pharma workflows specific datasets that can be used for continued pre-training, RLHF, in-context-learning (ICL), and other applications.

4. Create a fine-tuning strategy. Lead the team in thinking through domain-specific fine tuning and model training and deploy resources thoughtfully to help us achieve SOTA performance on pharma specific benchmarks

5. Create evaluations & benchmarks. Design and run the first even pharma domain specific benchmarks for model performance on very specific pharma operational tasks.

Who you are

1. You bridge research and product. You love to stay on top of the latest research for models, prompting techniques, and how best to utilize LLMs and other AI systems, but you are an engineer at heart. You want to deploy the latest research and build things.

2. AI native. You’ve been working with LLMs for the past few years and are comfortable working with vector databases, RAG systems, and prompting. You’re driven to stay up to date with SOTA techniques and models to get the most out of advances in AI.

3. Ambitious. You are excited about working at a fast growing venture backed start-up where you will lead and have initiative in managing major projects to completion.

4. A hacker. You build quickly, and you find your way to information. Constantly curious and have a serious bias towards action