We believe that great scientists should do great science.
Labs waste months to learn and code pipelines that are obsolete for the next experiment. Mithrl’s “digital agents” create on-demand custom workflows using natural language – in minutes. So that scientists can focus all their time to conduct higher-quality experiments.
Founded by two scientists, we are a venture-backed, fast-growing startup located in the heart of San Francisco. We are very well capitalized and have customers in the US and Europe. We are backed and advised by some of the most sought-after biotech legends (including the former CEO of Roche.)
Who are you?
- You are a hungry and ambitious engineer, eager to define your early career through fundamental AI research and applied ML
- You thrive in challenging environments and are passionate about innovative technologies - applying your research to real world, painful problems
- You must be a grinder — and would be thoughtful about every opportunity you land
What you will do
- First and foremost - contribute significantly to the engineering culture. We deliver a high product velocity and believe shipping is winning
- Develop and deploy foundational models (GPT, Claude 3.5, Llama 3.1, etc.)
- Fine-tune open-source models to meet specific project (module) requirements
- Host and manage open-source models in AWS
- Design and build agentic systems to automate complex tasks and processes (for instance, check this article out)
- Implement and optimize Retrieval-Augmented Generation (RAG) systems for our agentic systems
- Stay up-to-date with the latest advancements in AI and machine learning to ensure our solutions remain cutting-edge
- Participate in code reviews, provide constructive feedback, and contribute to a culture of continuous improvement
What you need to succeed
- Proven experience with foundational models (GPT, Claude, and LLaMA)
- Hands-on experience hosting and managing open-source AI models
- Strong proficiency in Python
- Experience with fine-tuning AI models to optimize performance for specific applications
- Familiarity with different RAG systems and their implementation
- Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
- Strong communication skills and the ability to articulate complex technical concepts to non-technical members
- Preferred background in data science and experience with data preprocessing, feature engineering, and model evaluation
- Ability to work in-person in San Francisco
