Member of Technical Staff - Applied AI Engineer - Core Capabilities

What you'll do

• Develop, adapt, and post-train biological models; build frameworks to evaluate their performance and understand their capabilities and limitations.
• Create and curate datasets with computational biologists, and collaborate with software engineers on scalable model training and evaluation infrastructure.
• Contribute to the research and development roadmap, communicate results, and work with customers and external collaborators.

What they ask for

• Experience with data-centric development and evaluation of ML models.
• High proficiency in Python and deep learning libraries such as PyTorch.
• Experience with cloud computing platforms such as AWS and distributed systems.
• Strong understanding of probability and statistics.

Nice to have

• Experience with language-model training, reasoning agents, time-series modeling, biological or other noisy heterogeneous data, ML-centric bioinformatics, or structure-based tools such as AlphaFold.
• Experience building data pipelines and training infrastructure, designing and evaluating ML ideas, or contributing to open-source projects.

Tools

Python, PyTorch, AWS, AlphaFold

AI focus

Applies and evaluates AI/ML models for biological threat assessment and precision biologics design, including adapting and post-training biological frontier models.