About Taxa

The last few years have seen a proliferation of maturing foundation models — AlphaFold, ESM, NT — that have started to learn what biology is.

Atop these models, the field is advancing into RL on in silico rewards (docking scores, predicted stability) or wet-lab rewards (assay readouts, fluorescence, growth).

Taxa believes the time has come to start training on what biology does. We have built the stack to measure exactly that— real, clinically verifiable rewards from interventional studies in humans at a cadence, scale, and resolution no one else has. How you learn from a signal like that is an open and exciting problem; reinforcement learning is the natural starting point, and we call our framing RLCVR: Reinforcement Learning from Clinically Verifiable Rewards.

Over the past four years, Taxa has built the first clinical stack capable of running this closed-loop end to end, starting with the skin microbiome:

1. Genetic engineering of intractable microbiome species — important species the rest of the field has struggled to work with.
2. Reliable delivery of these probiotics to humans — a delivery problem that has been a major barrier across the field.
3. High-throughput human study operations — interventional, longitudinal, at a cadence and cost no academic or pharma program approaches.
4. Strain-level shotgun metagenomics at scale to resolve microbiome perturbations at extreme resolution— read-level, not species-level.

The convergence of these four — engineered chassis, in situ delivery, study throughput, and strain-level resolution — drive what makes an RL loop with sufficient human-derived reward signal possible.

The Opportunity

We are looking for a talented expert in Bioinformatics to manage and operate large-scale -omics pipelines critical to our flagship projects. Top candidates are wizards at the infrastructure side of large-scale -omics analysis: building, optimizing, and maintaining existing and new pipelines that take raw data all the way to clean, analysis-ready data structures. You'll also help us build lightweight internal tools that keep metadata organized and accessible, connecting complex, high-throughput wet-lab and dry-lab workflows.

Required Qualifications

1. Ph.D. in bioinformatics, computer science, or a related field — or equivalent hands-on experience.
2. U.S. Citizenship, legal permanent residency, existing work authorization for this role.
3. Ability and willingness to work on-site at our San Francisco, California headquarters two or more days per week (this is a hybrid position).
4. Demonstrated experience building and maintaining large-scale bioinformatics pipelines in cloud environments, particularly AWS, including management of utilization, cost efficiency, and reliability.
5. Strong software engineering fundamentals: clean code, version control, testing, documentation.
6. Expertise in working with complex metadata across wet-lab and dry-lab contexts — and building tooling to manage it.
7. Proficiency in bacterial DNA informatics, including metagenomes and whole-genomes.
8. Exceptional organizational skills and high standards for quality control.

Experience in the following is highly desirable

1. Metabolomics or multi-omics from bacterial cultures and human-derived primary samples.
2. Designing efficient and robust protocols for liquid-handling robots.
3. Quantitative image processing, either microscopic or mesoscopic.

Transparent Compensation

✔️ Base salary — $150,000

✔️ Equity — Equity package as a core component of total compensation.

✔️ Benefits — comprehensive health, dental, and vision insurance.

✔️ Retirement — 401(k) plan with 6% employer match.

✔️ PTO — Unlimited