Careers
Work at Syntic.
We are 26 people across the world building two things that don't exist anywhere else together: a frontier AI model built entirely from scratch, and a biotechnology company using that model to accelerate the science of cellular rejuvenation.
Syntic AI powers a consumer assistant, an enterprise AI workforce platform, and a computational biology engine for protein engineering and gene therapy design. Syntic Life is our biotechnology subsidiary, developing gene therapy platforms aimed at restoring cellular health and addressing the biology of age-related disease.
We hire slowly and deliberately. We don't hire to fill headcount. We hire when we find someone who changes what's possible for the team. If that sounds like you, read on.
Open roles
Two companies. One team. Work that matters on both sides.
Syntic AI and Syntic Life operate as a unified organisation. The people building the model work alongside the people applying it to biology. The computational biologists inform what the AI team builds next. The AI engineers understand the science well enough to build tools that actually work in a lab context. That cross-disciplinary proximity is why we can move as fast as we do.
AI Engineering
Build the inference layer, the training pipeline, the Workforce dispatch plane, the Syntic assistant, and the infrastructure underneath all of it. We pretrain our own model from scratch — that means real pretraining infrastructure, real evaluation harnesses, real alignment work, and real production systems serving customers across six continents.
We have open roles across ML engineering, backend infrastructure, frontend, and model serving. You ship into production. There are no demo tracks. The model you work on is the model our customers use tomorrow.
What we're specifically looking for right now: engineers with experience in large-scale model training infrastructure, inference optimisation, and distributed systems at the scale frontier model serving requires. Experience with pretraining pipelines, RLHF, or evaluation methodology is a strong signal.
AI Research
We train our frontier model from scratch — pretraining, alignment, evaluation, safety, and the computational biology specialisation that powers Syntic Life's discovery pipeline. Research at Syntic ships into the model and the platform. We publish openly when we can. You work on the actual frontier, not on fine-tuning someone else's foundation.
What we're specifically looking for right now: researchers with backgrounds in large language model pretraining, alignment techniques, evaluation methodology, or — critically — the intersection of AI and biological systems. Experience applying ML to protein structure, gene expression modeling, or cellular pathway simulation is directly relevant to where we're going.
Computational Biology — Syntic Life
The biotechnology subsidiary applying our model to the science of cellular health.
Syntic Life is our biotechnology subsidiary, developing gene therapy platforms aimed at restoring cellular health and addressing the biology of age-related disease. We are in preclinical development, building a modular gene expression platform based on episomal DNA plasmids and regulated gene expression constructs designed to modulate key pathways involved in aging, metabolism, and cellular resilience.
Syntic AI is the discovery engine. Syntic Life is the therapeutic execution platform. The feedback loop between them — AI hypothesis, gene construct design, preclinical validation, data back into the model — is what makes this scientifically credible and operationally fast.
What we're specifically looking for right now
Computational Biologist / Bioinformatician
You model protein behaviour, cellular signalling pathways, and gene expression dynamics. You're comfortable working at the intersection of wet-lab biology and computational systems. Experience with protein structure prediction, pathway simulation, or gene therapy design is directly relevant. You don't need to have worked at a biotech — you need to understand the science deeply enough to build computational tools that a bench scientist will actually trust.
Molecular Biologist / Gene Therapy Scientist
You work in preclinical development. You understand episomal delivery systems, plasmid design, transient gene expression, and the regulatory pathway from preclinical to IND. Experience with cellular models, rodent models, or non-human primate research is relevant. You care about doing this correctly — clean data, reproducible results, regulatory-ready documentation.
Biomarker and Translational Scientist
You bridge the gap between preclinical findings and clinical relevance. You design biomarker strategies, interpret expression data, and think carefully about what "working" means in the context of aging biology. Experience with epigenetic clocks, proteomics, or metabolomics is a strong signal.
Syntic Life technologies are currently in preclinical development and are not approved for human use. All research is conducted in compliance with applicable regulatory and ethical standards.
Across both companies
The teams that keep everything running.
Go-to-Market
Sales, solutions engineering, marketing, and partnerships. The people who help customers understand what an AI Workforce actually looks like in production — and get it live inside ninety days. We sell to operators who need things to work, not to buyers who want a demo. As Syntic Life develops, Go-to-Market will also cover scientific partnerships, research collaborations, and the biotech relationships that matter for clinical translation.
Operations
People, finance, legal, and platform operations. The team that keeps a 26-person company running cleanly while we operate a frontier AI model, two product surfaces, customers across six continents, and a preclinical biotechnology program. High ownership. Low bureaucracy. No one here does work that doesn't matter.
Apply
Don't see your exact role?
We don't always post every role we'd hire for — especially on the Syntic Life side, where the right person is rare and the search is specific. If you think you belong here, send us a note. We read every one.
How to apply
Email careers@syntic.ai with the following — no more, no less:
- Who you are and what you're best at — one paragraph, specific
- What you'd build or own at Syntic — one to two paragraphs, specific to our work, not generic
- Evidence of the work — links to repos, papers, datasets, products, results, or whatever shows what you've actually done. For biotech roles, relevant publications or preprints are welcome.
- Which role or discipline — you're applying for
No CV required at this stage unless you want to send one. No cover letter template. No recruiter screen. The people making hiring decisions read these directly. We reply to the ones that are real, usually within a week.
For Syntic Life scientific roles specifically: if you're a researcher with relevant work in epigenetics, gene therapy, protein engineering, or aging biology — and you're not sure whether what you're working on maps to what we're building — send a note anyway and describe your research. The intersection might be closer than you think.
We don't move fast and break things. We build frontier AI from scratch and we do preclinical biology correctly. Both take patience, rigour, and the confidence to do things the hard way when the hard way is the right way. If that's how you work, we'd like to hear from you.
careers@syntic.ai