Xaira Therapeutics
AI-native drug discovery — generative protein design and foundation models for biology
About Xaira Therapeutics
Funding & Growth
✓ Pros
- • Launched with $1B+ — one of the largest biotech launch rounds ever, giving genuine runway to do long-horizon AI research
- • Publishing is part of the job description for AI Scientist roles, not a side activity — Xaira explicitly lists it as a Key Responsibility
- • Three distinct technical tracks: BioMedical AI (foundation models, perturb-seq, multimodal), Computational Protein Design (generative protein/antibody design, Seattle ML platform), Biology & Drug Discovery (functional genomics, assay development)
- • AI in Residence program is a deliberate alternative to a postdoc — you work on real therapeutic programs, not a rotation project
- • Agentic AI work here is genuinely frontier: the Research Engineer role builds multi-step reasoning agents over omics + literature, not chatbots
✗ Cons
- • Almost all SSF roles are onsite — limited remote flexibility outside the Seattle ML Platform team
- • AI in Residence is a fixed-term program (6–12 months) with no guaranteed conversion to full-time
- • No named clinical-stage programs yet — this is a platform company; if you need to see a drug in patients within 2-3 years, it is too early
- • BioMedical AI and Computational Protein Design run as parallel tracks with different leadership — cross-division coordination is a known friction point at companies structured this way
- • Most ML roles expect deep research backgrounds (PhD or equivalent publication record) — strong ML engineers without biology depth will find fewer entry points
🏢 Working Here
Xaira launched in April 2024 with over $1B in committed funding incubated by ARCH Venture Partners and Foresite Labs.
The company is organized into three distinct research divisions that operate with significant independence: BioMedical AI builds foundation models over perturb-seq and single-cell data, multimodal models spanning imaging and omics, and agentic AI systems that autonomously integrate scientific literature, omics datasets, and clinical records into discovery workflows — the Research Engineer posting describes this explicitly as beyond LLM+RAG.
Computational Protein Design focuses on generative protein and antibody design against hard-to-drug targets, with the ML platform and infrastructure team based in Seattle.
Biology & Drug Discovery runs the experimental side — functional genomics, CRISPR-based perturbation screens, and high-throughput assay development that feeds data directly into the AI models.
The X-Scientist team bridges all three: software engineers building the tool-calling infrastructure, APIs, and workflow orchestration that let AI models connect to biological tools and datasets at scale.
Headquarters is 700 Gateway Blvd, South San Francisco, with ML Platform in Seattle and additional teams in London.
🧬 Bioinformatics Focus
Xaira's computational work is distributed across three technically distinct tracks.
BioMedical AI: foundation models trained on large-scale perturb-seq and single-cell datasets (transcriptomic, epigenomic, proteomic); multimodal generative models that treat image-based data and high-dimensional omics as complementary views of the same system; agentic AI systems that do multi-step reasoning, tool-calling, and hypothesis updating over biomedical knowledge sources.
Computational Protein Design: generative models for protein and antibody design against historically undruggable targets; ML platform engineering for distributing large-scale training jobs across thousands of GPUs across multi-cloud clusters.
A Bioinformatics-focused candidate would most likely land in BioMedical AI (single-cell/perturb-seq modeling) or the X-Scientist team (connecting model outputs to scientific workflows).
Software engineering experience with ML systems is valued across all tracks.
📈 Career Growth & Development
Publications
The program runs 6–12 months and is selective; it does not guarantee conversion but is intended to identify exceptional researchers for full-time roles. Compensation benchmarks against tech research labs, not pharma.
Career Tracks
Beyond that, the career path is typical of a well-funded research-stage company: track record and ownership determine trajectory more than title.
Overview
Xaira offers one concrete structured entry point — the AI in Residence program — which is explicitly designed as an industry alternative to a postdoc: a small cohort, direct mentorship from AI Scientists and drug discovery leads, and hands-on work on real therapeutic programs from day one. The three-division structure means specialists in perturb-seq modeling, protein design, and agentic AI are each building depth in a real subdomain rather than rotating through generalist roles.