Member of Technical Staff (Research Engineer)

The Role

Join Anthrogen's core research team to build the computational infrastructure powering de novo protein design at scale. You'll work directly on Odyssey—our 102B parameter multimodal protein language model—advancing the algorithms, systems, and experiments that enable AI-driven biologics discovery. This is hands-on research engineering: you'll bridge cutting-edge ML and wet-lab validation, moving proteins from model outputs to real-world function.

What You'll Do

• Develop and optimize training pipelines for large-scale protein language models, including our novel Consensus architecture (linear O(L) complexity) and discrete diffusion objectives
• Implement multimodal fusion of sequence, 3D structure, and functional data; work with our Finite Scalar Quantizer tokenization for structure encoding
• Build evaluation frameworks and benchmarks for de novo protein design, collaborating with wet-lab experiments to validate model predictions
• Scale infrastructure for API access and external collaborator workflows
• Contribute to both research publication and product development—this role spans papers and deployed systems

Who You Are

• Strong foundation in deep learning, transformers, or generative models; Python fluency non-negotiable
• Experience with large-scale model training (distributed training, optimization, inference)
• Comfort moving between theory and implementation; you can own a research problem end-to-end
• Curiosity about biology or protein science; you'll learn the domain rapidly and ask good questions
• Bonus: familiarity with protein structure prediction, language models, or synthetic biology workflows

Apply

Email with your background, recent work, and why you're excited about protein AI.